Ultra-wideband (UWB) Remote Sensing and Radar Imagingcradpdf.drdc-rddc.gc.ca/PDFS/unc36/p521851.pdf · DRDC Ottawa TR 2004-081 i Ultra-wideband (UWB) Remote Sensing and Radar Imaging

Ultra-wideband (UWB) Remote Sensing and Radar Imaging

Senglee Foo, Alan Walsh and Satish Kashyap

Defence R&D Canada √ Ottawa TECHNICAL REPORT

DRDC Ottawa TR 2004-081 May 2004

DRDC Ottawa TR 2004-081 i

Ultra-wideband (UWB) Remote Sensing and Radar Imaging

Senglee Foo, Alan Walsh, Satish Kashyap

Defence R&D Canada – Ottawa Technical Report DRDC Ottawa TR 2004-081 May 2004

© Her Majesty the Queen as represented by the Minister of National Defence, 2004

© Sa majesté la reine, représentée par le ministre de la Défense nationale, 2004

DRDC Ottawa TR 2004-081 i

Abstract

The ultra-wideband (UWB) signals have an inherent fine resolution in time and good penetration into many common materials. Used in conjunction with a time-reversal algorithm such as the back projection method, UWB radars are versatile RF imaging tools for remote sensing of objects hidden behind obstacles such as wall, sand and snow. DRDC Ottawa has conducted theoretical and experimental studies of the UWB radar imaging in various areas using the stepped-frequency method.

The method has been successfully applied in detecting and imaging targets hidden behind walls of various types, including detection of human subjects buried in the snow. A cross-correlated time-reversal algorithm was developed for the UWB image reconstruction. This algorithm enables UWB imaging radars to locate and resolve objects behind a wall at a standoff position. In comparison to the standard back projection scheme, this algorithm produces images of superior quality with better cross-range resolution. It is also demonstrated that by cross-correlating the array elements with a reference element located further away from the array center, this algorithm is capable of improving the cross-range resolution of the radar images to the pulse-width of the UWB signal.

Résumé

Les signaux en bande ultra-large (UWB) se caractérisent par une haute résolution temporelle et une bonne pénétration dans de nombreux matériaux d’usage courant. Utilisés conjointement avec un algorithme respectant le renversement du temps, p. ex. la méthode de rétroprojection, les radars UWB sont des outils d’imagerie RF polyvalents pour la télédétection d’objets cachés derrière des obstacles comme des murs, du sable et de la neige. RDDC Ottawa a effectué des études théoriques et expérimentales sur l’imagerie radar UWB dans divers domaines en utilisant la méthode des fréquences échelonnées.

Cette méthode a été appliquée avec succès pour la détection et l’imagerie de cibles cachées derrière des murs de divers types, y compris pour la détection de sujets humains ensevelis sous la neige. Un algorithme de corrélation croisée respectant le renversement du temps a été élaboré pour la reconstruction d’images UWB. Cet algorithme permet à des radars imageurs UWB de localiser et de résoudre des objets derrière un mur à distance de sécurité. Comparativement à la formule de rétroprojection courante, cet algorithme produit des images de qualité supérieure avec une meilleure résolution latérale. Il est en outre démontré qu’en effectuant la corrélation croisée des éléments du réseau avec un élément de référence situé plus loin du centre du réseau, cet algorithme permet d’améliorer la résolution latérale des images radar en la portant à la largeur d’impulsion du signal UWB.

ii DRDC Ottawa TR 2004-081

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DRDC Ottawa TR 2004-081 iii

Executive summary

From November 2002 to Oct 2003, DRDC Ottawa conducted a series of experiments on through-wall radar imaging using the stepped-frequency UWB technique. This work includes indoor through-wall imaging, snow penetration, standoff remote sensing of human subject, mine detection and high resolution UWB. The results demonstrate that the UWB technique can indeed penetrate various common materials with moderate propagation losses. A UWB radar with an average power in the order of a few hundreds milliwatts is sufficient to detect a human subject behind drywall at a distance up to 30m, and more than 8m for a brick-on-concrete wall. Furthermore, it is also shown that a UWB radar with an average power in the order of just a few milliwatts can be used to locate a human subject buried under snow of up to a few metre in depth. The experiments also touched on the subject of the mine detection; however, this work remains in an early stage. Results indicate that further work is required in this area to study detection of mines that are composed primarily of plastics materials.

In this study, back projection algorithms are used to form the radar images. It is shown that the standard back projection technique works well for imaging in a short range relative to the aperture size of the receiver array. For larger distances, the target images suffer from loss in the cross-range resolution. A cross-correlation time reversal algorithm was developed to remedy the cross-range resolution problem for standoff imaging. This algorithm eliminates the smearing of images in the cross range inherited in the standard back projection scheme. It is shown that by cross-correlating array elements with a remote element, the cross-range resolution of the image can be improved to near the pulse-width of the UWB signal.

Senglee Foo, Alan Walsh, Satish Kashyap. 2004. Ultra-wideband (UWB) remote sensing and radar imaging. DRDC Ottawa TR 2004-081. Defence R&D Canada - Ottawa

iv DRDC Ottawa TR 2004-081

Sommaire

De novembre 2002 à octobre 2003, RDDC a effectué une série d’expériences en imagerie radar transmurale en utilisant la technique UWB des fréquences échelonnées. Ces travaux portent sur l’imagerie transmurale intérieure, la pénétration de la neige, la télédétection de sujets humains à distance de sécurité, la détection de mines et la haute résolution UWB. Les résultats montrent que la technique UWB peut effectivement pénétrer divers matériaux d’usage courant avec des affaiblissements de propagation modérés. Un radar UWB ayant une puissance moyenne de l’ordre de quelques centaines de milliwatts est suffisant pour détecter un sujet humain derrière une cloison sèche à une distance allant jusqu’à 30 m, et à plus de 8 m dans le cas d’un mur en brique et béton. De plus, on montre qu’un radar UWB ayant une puissance moyenne de l’ordre de seulement quelques milliwatts peut servir à détecter un sujet humain enseveli sous la neige à une profondeur allant jusqu’à quelques mètres. Les expériences ont également touché le domaine de la détection de mines; toutefois, ces travaux n’en sont qu’à leurs débuts. Les résultats indiquent que d’autres travaux sont nécessaires dans ce domaine afin d’étudier la détection des mines qui sont composées principalement de matériaux plastiques.

Dans la présente étude, des algorithmes de rétroprojection sont utilisés pour former les images radar. On montre que la technique de rétroprojection courante fonctionne bien à une faible distance par rapport à la taille de l’ouverture du réseau de récepteurs. Pour de plus grandes distances, les images des cibles sont dégradées par l’affaiblissement de la résolution latérale. Un algorithme de corrélation croisée respectant le renversement du temps a été élaboré pour remédier au problème de la résolution latérale dans le cas de l’imagerie à distance de sécurité. Cet algorithme élimine la persistance des images en résolution latérale découlant de la formule de rétroprojection courante. On montre que la corrélation croisée des éléments du réseau avec un élément éloigné peut améliorer la résolution latérale des images radar en la rapprochant de la largeur d’impulsion du signal UWB.

Senglee Foo, Alan Walsh, Satish Kashyap. 2004. Ultra-wideband (UWB) remote sensing and radar imaging. DRDC Ottawa TR2004-081. R & D pour la defense Canada - Ottawa

DRDC Ottawa TR 2004-081 v

Table of contents

Abstract........................................................................................................................................ i

Résumé ........................................................................................................................................ i

Executive summary ................................................................................................................... iii

Sommaire................................................................................................................................... iv

Table of contents ........................................................................................................................ v

List of figures ........................................................................................................................... vii

List of tables .............................................................................................................................. xi

1. Introduction ............................................................................................................................ 1

2. Ultra-Wideband (UWB) Radar Imaging ................................................................................ 2 2.1 Gaussian modulated sinusoidal UWB ..................................................................... 2 2.2 Characterization Method ......................................................................................... 3 2.3 Measurement Method.............................................................................................. 5 2.4 Image reconstruction ............................................................................................... 6

3. Ultra-Wideband Remote Sensing ......................................................................................... 15 3.1 Introduction ........................................................................................................... 15 3.2 Indoor through-wall imaging................................................................................. 15 3.3 Snow penetration ................................................................................................... 24 3.4 Stand-off through-wall imaging ............................................................................ 34 3.5 Mine detection ....................................................................................................... 53

4. High Resolution UWB radar imaging .................................................................................. 61 4.1 Concept study ........................................................................................................ 61 4.2 High resolution imaging case study....................................................................... 64

vi DRDC Ottawa TR 2004-081

5. Discussion............................................................................................................................. 68

6. Conclusions .......................................................................................................................... 69

References ................................................................................................................................ 70

List of acronyms ....................................................................................................................... 72

DRDC Ottawa TR 2004-081 vii

List of figures

Figure 1. Gaussian modulated sinusoidal UWB pulse ............................................................... 2

Figure 2. Frequency spectrum of a Gaussian modulated sinusoidal UWB pulse....................... 3

Figure 3. Computation of near-field array response................................................................... 7

Figure 4. Range profile of standard back projection image...................................................... 10

Figure 5. Azimuth beam pattern of standard back projection image........................................ 10

Figure 6. Range profile of cross-correlated back projection image.......................................... 11

Figure 7. Azimuth beam pattern of cross-correlated back projection image............................ 11

Figure 8. Range profile of intra-pulse cross-correlated BP image ........................................... 12

Figure 9. Azimuth beam pattern of intra-pulse cross-correlated BP image.............................. 12

Figure 10. Range profile of non-coherent cross-correlated BP image ..................................... 13

Figure 11. Azimuth beam pattern of non-coherent cross-correlated BP image........................ 13

Figure 12. Layout of indoor through-wall imaging test set-up................................................. 15

Figure 13. Antenna chamber .................................................................................................... 16

Figure 14. Target chamber........................................................................................................ 16

Figure 15. Equipment set-up .................................................................................................... 17

Figure 16. Measured and calculated path losses....................................................................... 18

Figure 17. Simulated E [email protected] ........................................................................................ 20

Figure 18. Measured E Field @7.8m....................................................................................... 20

Figure 19. Simulated radar range profile.................................................................................. 21

Figure 20. Measured radar range profile .................................................................................. 21

Figure 21. Simulated UWB pulse Reflected From the Drywall ............................................... 22

Figure 22. Measured UWB pulse Reflected From the Drywall ............................................... 22

Figure 23. Simulated 2D radar image....................................................................................... 23

viii DRDC Ottawa TR 2004-081

Figure 24. Measured 2D radar image ....................................................................................... 23

Figure 25. Layout of snow penetration test set-up ................................................................... 24

Figure 26. Equipment set-up for the snow penetration experiment.......................................... 25

Figure 27. Front end of the snow pile....................................................................................... 25

Figure 28. Rear view of the snow pile...................................................................................... 26

Figure 29. Verification test set-up for the snow experiment .................................................... 27

Figure 30. Equipment set-up for the verification test ............................................................... 27

Figure 31. Measured range profile of verification test set-up................................................... 28

Figure 32. Computed radar image of the verification test set-up ............................................. 28

Figure 33. Measured range profile of two spheres and one cylinder in snow .......................... 29

Figure 34. Computed radar image of two spheres and one cylinder in snow........................... 30

Figure 35. Measured range profile of a plastic sphere, a metallic sphere and a cylinder ......... 31

Figure 36. Computed radar image of a plastic sphere, a metallic sphere and a cylinder.......... 31

Figure 37. Snow penetration test with human subject .............................................................. 32

Figure 38. Range profile of human target................................................................................. 33

Figure 39. Radar image of human target .................................................................................. 33

Figure 40. UWB pulse for stand-off remote sensing................................................................ 34

Figure 41. Frequency spectrum of stand-off UWB Pulse......................................................... 35

Figure 42. Layout of standoff imaging of a trailer ................................................................... 35

Figure 43. Range profile of the stand-off imaging of trailer .................................................... 36

Figure 44. Radar image of the trailer........................................................................................ 36

Figure 45. Range profile of trailer with two cylinders (V-pol) ................................................ 37

Figure 46. Radar image of trailer with two cylinders (V-pol) .................................................. 37

Figure 47. Range profile of trailer with two cylinders (H-pol) ................................................ 38

Figure 48. Radar image of trailer with two cylinders (H-pol) .................................................. 38

DRDC Ottawa TR 2004-081 ix

Figure 49. Range profile of trailer with background subtraction (V-pol) ................................ 39

Figure 50. Radar image of trailer with background subtraction (V-pol) .................................. 39

Figure 51. Range profile of trailer with background subtraction (H-pol) ................................ 40

Figure 52. Radar image of trailer with background subtraction (H-pol) .................................. 40

Figure 53. Range profile of the drywall with two cylinders..................................................... 41

Figure 54. Back projection image of drywall with two cylinders ............................................ 42

Figure 55. Cross-Correlated BP image of drywall with two cylinders..................................... 42

Figure 56. Layout diagram: drywall with a cylinder and a barrel ............................................ 43

Figure 57. Range profile of drywall case with a cylinder and a barrel..................................... 43

Figure 58. Back projection image of drywall with a cylinder and a barrel .............................. 44

Figure 59. Cross-correlated BP image of drywall with a cylinder and a barrel ....................... 44

Figure 60. Layout diagram: drywall with a human and a cylinder........................................... 45

Figure 61. Range profile of drywall @20m with a human and a cylinder ............................... 45

Figure 62. Back projection image of drywall @20m with a human and a cylinder ................. 46

Figure 63. Cross-correlated BP image of drywall @20m with a human and a cylinder .......... 46

Figure 64. Range profile of drywall @25m with a human and a cylinder ............................... 47

Figure 65. Back projection image of drywall @25m with a human and a cylinder ................. 48

Figure 66. Cross-correlated BP image of drywall @25m with a human and a cylinder .......... 48

Figure 67. Layout diagram of standoff test at building 14 ....................................................... 49

Figure 68. Range profile of building 14 @7m (H-pol)............................................................ 50

Figure 69. Range profile of building 14 @7m (V-pol)............................................................ 50

Figure 70. Radar image of building 14 @7m (V-pol) ............................................................. 51

Figure 71. Range profile of building 14 @27m (V-pol).......................................................... 52

Figure 72. Radar Image of building 14 @27m (V-pol) ........................................................... 52

Figure 73. Layout diagram of mine detection .......................................................................... 53

x DRDC Ottawa TR 2004-081

Figure 74. Test set-up of mine detection .................................................................................. 54

Figure 75. Type #1 mine........................................................................................................... 55

Figure 76. Type #2 mine........................................................................................................... 55

Figure 77. Type #3 mine........................................................................................................... 55

Figure 78. Range profile of mine detection .............................................................................. 56

Figure 79. Back projection image of mine detection................................................................ 56

Figure 80. Test set-up for mine detection (case #2) ................................................................. 57

Figure 81. Layout of mine detection (case #2) ......................................................................... 57

Figure 82. Range profile of mine detection (case #2) .............................................................. 58

Figure 83. Back projected image of mine detection (case #2).................................................. 58

Figure 84. Layout of mine detection (case #3) ......................................................................... 59

Figure 85. Range profile of mine detection (case #3) .............................................................. 60

Figure 86. Back projected image of mine detection (case #3).................................................. 60

Figure 87. High resolution array configuration ........................................................................ 61

Figure 88. Range profile with array center as reference channel ............................................. 62

Figure 89. Azimuth beam pattern with array center as reference channel................................ 62

Figure 90. Range profile with Reference Element as reference channel.................................. 63

Figure 91. Azimuth beam pattern with Reference Element as reference channel .................... 63

Figure 92. Layout of high resolution UWB Test ...................................................................... 65

Figure 93. Range Profile of high resolution test....................................................................... 65

Figure 94. Cross correlated BP image (array center as reference) ........................................... 66

Figure 95. Cross correlated BP image (Remote element as reference) .................................... 66

Figure 96. Intra-pulse cross correlated BP image (array center as reference) .......................... 67

Figure 97. Intra-pulse Cross correlated BP image (Remote element as reference) .................. 67

DRDC Ottawa TR 2004-081 xi

List of tables

Table 1. Comparisons of Beam patterns of BP images ............................................................ 14

Table 2. Comparisons of beam patterns ................................................................................... 64

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DRDC Ottawa TR 2004-081 1

1. Introduction

The Ultra Wideband (UWB) technology makes use of impulse signal with time duration typically below 1 nsec, which corresponds to a bandwidth in the GHz. The inherent characteristic of wide bandwidth leads to a fine resolution in time while the low center frequency gives a relatively good penetration into many common materials. As a result, UWB has found applications in many areas, such as short-range communications, ground probing radar, medical imaging, through-wall imaging, geo-location, etc [1][4][5][7].

The concept of the UWB has been used in electronic warfare since the early 1940s. Today, the technology has reached a new state of maturity with the new implementation of ultra wideband components as well as a better understanding of the UWB system characteristics. UWB is now believed to be one of the most promising technologies for building future radar systems with new and better capabilities, both for military and commercial applications. In the past, many UWB applications were conducted between 1 to 3 GHz [7]. However, the Federal Communications Commission (FCC) has recently also allocated 7500 MHz of spectrum for unlicensed use of ultra-wideband devices in the 3.1 to 10.6 GHz frequency band.

A stepped-frequency algorithm has been developed for the UWB modeling and measurement at DRDC Ottawa. This technique allows flexibility in tailoring of the UWB pulse shape and frequency spectrum to meet the criteria of the research and the application. Using UWB pulse with frequency spectrum between 800 MHz to 4 GHz, DRDC Ottawa has conducted various experimental and theoretical investigations in UWB imaging. This work includes through-wall detection and location of human subjects buried in the snow. A cross-correlation time reversal algorithm is also developed to improve the image quality of the UWB radars. By cross-correlating the receiver array with a remote reference channel, this algorithm is capable of improving the cross-range resolution by many folds.

2 DRDC Ottawa TR 2004-081

2. Ultra-Wideband (UWB) Radar Imaging

2.1 Gaussian modulated sinusoidal UWB A variety of UWB signals can be designed to make use of the available UWB spectrum. This study uses a Gaussian modulated, monocycle sinusoidal pulse. This type of signals can be represented by the following mathematical expression:

)(sin])(21exp[

2)( 2 µ

σµ

πσ−⋅

−−⋅= xxAxf p (1)

Here 0f is the center frequency, A is the amplitude factor, σ is the standard deviation, µ is the mean of x ( tfx oπ2= ), and p is the order of the sinusoidal signal. This particular type of UWB signal has a power distribution spectrum that is well suited for stepped frequency applications. Fig. 1 and 2 show the UWB waveform and the frequency spectrum of a typical single cycle, gaussian modulated, sinusoidal, UWB pulse ( 1,GHz45.1,,10,8.0 ===== pfA oπµσ ).

Figure 1. Gaussian modulated sinusoidal UWB pulse


Figure 2. Frequency spectrum of a Gaussian modulated sinusoidal UWB pulse As indicated in the Figure 2, this UWB signal has a bell shape curve with approximately 70% to 80% of the total signal power bounded within 800 MHz and 3.7 GHz. The truncation of frequency points in the stepped frequency algorithm is based on the 70% to 80% power criterion.

2.2 Characterization Method

Characterization of UWB signals is typically conducted in the time domain using broadband antennas and a high-speed oscilloscope. This study uses stepped-frequency technique. Measurement in the frequency domain allows characterization of the UWB signals without distortion from the system components since the frequency characteristics of these components can be eliminated through a system calibration process. Other advantages of conducting the UWB measurements in the frequency domain include the elimination of the need for expensive impulse antennas, and only low transmit power is required due to higher sensitivity and wider dynamic range in the receiver. In addition, the stepped-frequency technique allows the flexibility of varying the transmit pulse shape and the frequency spectrum to suit the needs of the research, if necessary. This method allows close correlation between measurements and EM modeling. A UWB modeling using the geometrical optics (GO) technique has been developed at Defence Research & Development Canada (DRDC) [9]. The measurement results are first verified against the GO model.


The modeling method is based on the 3-D shooting-and-bouncing-ray (SBR) geometrical optics (GO) and physical optics (PO) method [9]. A general multi-layered dielectric flat-plate formulation is used to account for these phenomena at an interface. The directions of the reflected and the transmitted components at the interface of any two media change according to the well-known Snell’s laws of reflection and refraction, and can be calculated using the

dyadic reflection ( R ) and transmission (T ) coefficients as follows:

[ ] [ ])()( ri

rr QERQE ⋅= (2)

[ ] [ ])()( ri

rt QETQE ⋅=

Here the incidence field iE , reflected field rE and the transmitted field tE at the reflection point rQ are decomposed into two orthogonal components which are perpendicular and parallel to the plane of incidence as follows:

[ ]

=

⊥i

ii

EE

E // , [ ]

=

⊥r

rr

EE

E // , [ ]

=

⊥t

tt

EE

E // (3)

The dyadic surface reflection and transmission coefficients of a multi-layered dielectric plate are:

=R

Γ

Γ

⊥00// =

⊥

⊥i

r

i

r

EE

EE

0

0//

// =

0

0

0

0

0

0

AB

CD (4)

=T

⊥TT0

0// =

⊥

⊥i

t

i

t

EE

EE

0

0//

// =

0

010

01

A

C

Here the parameters of the multi-layer dielectric materials, oA , oB , oC , and oD are computed using the recursive ABCD equations. Scattered field re-radiated by a target can be expressed in terms of the radiation integral over the current induced on the surface of the target, i.e. the induced vector potentials A and F. The target surface So is sub-divided into N smaller areas such that the vector potentials can be integrated numerically in terms of the local field quantities Ei, Hi, and the field interpolation function αi(x,y,z):

r

eArj

π

β

4

−

= ×n̂ ∫∫ ′′⋅⋅

So

rrjSo SdeH )ˆ(β

re rj

π

β

4

−

= ∑=

×N

iiQn

1

ˆˆ (5)

r

eFrj

π

β

4

−

−= ×n̂ ∫∫ ′′⋅⋅

So

rrjSo SdeE )ˆ(β

re rj

π

β

4

−

−= ∑=

×N

iiPn

1

ˆˆ (6)

where

=iQ̂ [ ] SdezyxH rrji

Sii ′⋅ ′⋅⋅∫∫ )ˆ(),,( βα (7)

=iP̂ [ ] SdezyxE rrji

Sii ′⋅ ′⋅⋅∫∫ )ˆ(),,( βα (8)


The resultant far-field values can be approximated in terms of the tangential vector potentials as follows: tantan),( FA EEE +=φθ = rFjAj ˆˆˆ ×−− ωεηωµ (9)

= φηθη φθθφˆ)(ˆ)( AFAF −++−

To simulate a UWB signal in frequency domain, a large number of frequency points are required. Inverse discrete-Fourier-transform (DFT) is implemented to convert these frequency-domain results to range profile for each receiver. Radar images are constructed by summing range profiles of the receivers using a time reversal algorithm.

2.3 Measurement Method Measurements are performed in stepped-frequency mode using a vector network analyzer (VNA) such as the HP8510C with an 8515A S-parameter test set. The relative amplitude and phase of the forward scattering parameter S21 are collected over a frequency range to form reflectivity profiles of the test range. The finite number of frequency points necessitates a truncation in the frequency spectrum of the UWB. The frequency points were selected such that a minimum of 80% of the total radiated power is preserved. The unused frequency points are padded with zero values during the inverse Discrete Fourier Transform (DFT) to form the corresponding range profile. The time step and total number of DFT points are selected to accommodate the maximum distance. For instance, for a fixed time step of 38.52ps, 1501 DFT points are required to image a 2-way range of 17.3m and 1801 points are required for 20.8m.

Before the actual measurement, values of the scattering parameter S21 are calibrated relative to a THRU calibration. The calibration is performed with the transmit antenna and the receive antenna spaced at a fixed distance of typically 90cm. After the calibration, the collected frequency data is weighted by the complex coefficients of the UWB signal during the post processing in forming the corresponding range profile for each receiver. The calibration path length is also taken into account during the range profile processing. The calibration effectively removes frequency dependence of all RF components including that of the LNA, antennas, cables and connectors. It also sets the reference amplitude and phase of the S21 to unity at the given reference path length. In a typical indoor environment, maximum variation in amplitude and phase of the reference S21 value can be maintained to well within ±0.1dB in amplitude and ±1.0deg in phase. Furthermore, during calibration, a 20dB attenuator is inserted at PORT1 of the VNA to ensure the linear operation of the LNA and the VNA. This 20dB attenuation is removed during data collection. The distortion due to the insertion of this 20dB attenuator is well within ±0.1dB in amplitude and ±3 deg in phase over the UWB frequency range. This distortion can also be compensated during the signal processing stage.


2.4 Image reconstruction A range profile is formed for each receiver element by performing an inverse DFT of the corresponding measured reflectivity profile. A 2-D radar image of the target field can then be reconstructed by time reversing and summing of the range profiles. Two time-reversal algorithms are used here for the image reconstruction: (1) Standard back projection (BP), and (2) Cross-correlated back projection. The standard back projection method is a common algorithm used in the field of medical imaging. This method correlates the spatial coordinates of the transmit antenna, receive antennas and the pixels of the images to the range profiles of the receivers. For single-look applications (linear array at one view angle), the back projection works well for a range that is short in relation to the overall aperture size of the receiving array. For larger distances, the back projection algorithm tends to produce smear images in the cross range. The cross-correlated back projection developed here improves the cross-range resolution of the images and is better suited for radar imaging at larger distances. The standard back projection algorithm is well documented in the literatures [10-12] and will not be described here. This section gives the derivation of the cross-correlated back projection algorithm. This method gives a better cross-range resolution by cross correlating range profiles of the receivers with that of a reference channel. This algorithm can be performed in two ways: (1) point-to-point cross-correlation, (2) intra-pulse cross-correlation. The point-to-point cross-correlation correlates the range profiles of the receivers to that of the reference channel on a point-to-point basis. The intra-pulse cross-correlation is a coherent integration process that correlates the range profiles of the receivers within the pulse duration with that of the reference channel. This method has the added advantage of providing an additional integration gain and, therefore, also improves the signal-to-noise ratio of the radar images. This method can prove to be significantly advantageous if the UWB pulse is designed to provide significant compression gain. The cross-correlation back projection method is a near-field extension of the far-field definition of the time-domain cross-correlation array factor [8]. Based on the far-field definition and by reciprocity, radar image at a pixel can be reproduced by cross correlating the range profiles of the receivers with that of a reference channel. This method produces a signal at the pixel location that is proportional to the coherent sum of all the components of the cross correlation between the reference and the rest of the elements. Effectively, it time gates and integrates correlatable energies from each element with respect to the reference channel. The resulting signal effectively eliminates the smearing distortion inherent in the standard back projection algorithm. In the time reversal process, signals recorded at the receiver array are time reversed and re-emitted into the medium. Effectively, for each given image location, the back projection method performs a near-field integration over the array aperture. According to definition of the time-domain array factor given in [8] and by reciprocity, given a signal function f(t) radiated by a linear array at an incidence angle θ (measured from the array center), the total signal s(t) at distance R can be expressed as a convolution of the signal f(t) and the near-field impulse response h(t) of the array:

∫∞

∞−−= ττθ dthtfRs )()(),( (10)


The near-field impulse response of the array is determined by the aperture weighting function and the pixel distance measured from the center of the array, R. Fig. 3 shows a uniform, equally spaced, linear receiver array with N elements and inter-element spacing d, with the transmitter located at (xt,yt). The Cartesian coordinates of the image location (xi,yi), the transmitter distance Rt and the receiver distance r can be expressed in terms of the distance R and the scan angle θ as follows: 0sin xRxi +⋅= θ (11)

0cos yRyi +⋅= θ

22 )()( titit yyxxR −+−=

20

20 )()( yydxxr ii −+−−=

θsin// ⋅+= dRr

δθβ −= , )(tan 1

oi

oi

yydxx

−−−

= −δ

Figure 3. Computation of near-field array response

n*d (x0,y0)

(xi,yi)

(xt,yt)

X

Y

θ

r R=T/2

Rt

Tx Antenna

Rx Antenna

r//

δ β

Rx Array Center


For an N-element uniform array, the near-field impulse response can be represented by N delta functions:

∑−

=

−=−1

0)()(

N

ntth τδτ , where )sin(1 rndR

ctTx ∆+++= θτ (12)

Here, c is the speed of light, N is the total number of receiving array elements, d is the element spacing, cRt tTx /= is the transmitter propagation delay, r∆ is the near-field correction factor for element n and can be expressed as follow:

)1cos

1()sin(// −⋅+=−=∆β

αndRrrr (13)

Substituting (12) into (10) gives the back projected signal at image location (R,θ):

∑−

=

=1

0)(),(

N

nntfRs θ , where )sin(1 rndR

ctt Txn ∆+++= θ (14)

The function )( ntf represents the range profile of the array element n. For a point target at the distance R, this can be represented by a delta function,

)()( Rnn tttf −= δ , where )(1tR Rr

ct += (15)

This particular case has a significant meaning. By varying the incidence angle θ, equation (14) traces out a path that forms a point response for a target located at distance R, for each element n. The sum of all these point responses forms the impulse response of the radar image at the distance R. Each of these point responses is an arc moving along a slightly different path and intercepts other responses only at the target location. A coherent sum is formed where the point responses of elements intersect. One of the defects of this algorithm is that each of these point responses smears the beam pattern of the image in the azimuth direction and therefore limits the image resolution and target dynamic range in the cross range. The larger the distance of the image pixel measured from the array center, relative to the overall array dimension, the worse is the smearing distortion. As a remedy to the problem, we propose a cross-correlated back projection scheme. This method eliminates the smearing of images by cross correlating each individual point response of the array elements to that of a reference channel. Ideally, it is preferable to have a point response of the reference element intercepts the point responses of the other elements at a large subtend angle. If the reference point response is near orthogonal to all other point responses, the cross-range resolution of the resultant image will be determined by the time duration of the UWB pulse rather than the azimuth beam pattern of the array. This practically eliminates the smearing effects of the azimuth beam patterns. In this study, the center element (n=N/2) is taken as the reference channel. This is an arbitrary choice and is not an optimum case. The near-field intra-pulse cross-correlated signal function p can be computed using the following cross correlation formula:


∑=

⋅=M

N RStfRp0

2/ ),()(),(τ

θθ , where TrNdc

tt TxN ⋅+∆+⋅+= τθ )sin2

(12/ (16)

M is the total number of sample points in the UWB pulse, T is the sampling period, and )( 2/Ntf represents the range profile of the reference element. Note that point-to-point cross

correlation is a special case of the intra-pulse cross correlation where M=1. Using (14) and (16) one obtains,

∑∑=

−

≠=

⋅=M

nN

N

Nnn

tftfRp0

2/

1

2/0

)()(),(τ

θ (17)

Given the sampling period T and the pulse duration M, the intra-pulse cross-correlated near-field image can be expressed in terms of the time step k:

∑ ∑−

≠= =

⋅=1

2/1 0

2/ )()(),(N

Nnn

n

M

N kfkfRpτ

θ (18)

where TtrndR

cTTtk Txn

n +∆++== )sin(1 θ

τθ ++∆+⋅=′

=TtrNd

cTTtk TxN

N )sin2

(12/2/

Note that this expression arbitrarily assumes the center element as the reference. This does not represent an optimum case for the image quality. In fact, it will be demonstrated in a later section that a high-resolution imaging is possible by using a reference channel that is far away from the array center. Equation (18) represents the image at the given distance R and incidence angle θ, which is a time-reversed coherent sum of all the cross-correlated signals. This equation gives an optimum image when there are no geometrical errors such as the transmit and receive antenna positions in the measurement system. When significant errors are anticipated in the measurement systems, it may be necessary to perform a non-coherent sum to avoid cancellation due to phase errors of the measurement system, i.e,

∑ ∑−

≠= =

⋅=1

2/1 0

2/ )()(),(N

Nnn

M

nN kfkfRpτ

θ (19)

For example, consider a linear array consisting of N=33 receiving elements, equally spaced at an inter-element spacing d=15.24cm. The transmitted pulse is a typical Gaussian modulated, sinusoidal, UWB pulse ( 1,GHz5.1,,100,8.0 ===== pfA onnn πµσ ). The total pulse duration is about 700ps. With a time step of 41.6667ps, the total number of samples per pulse is M=17. A target is assumed at R=10m along the center axis of the receiver array. The antenna beam pattern in the azimuth angle and the range profile at distance R are computed using different algorithms: (1) Standard back projection (BP), (2) Point-to-point cross-correlated back projection, (3) Intra-pulse cross-correlated back projection, (4) Non-coherent cross-correlated back projection. Fig. 4 to 11 show the results.


Figure 4. Range profile of standard back projection image

Figure 5. Azimuth beam pattern of standard back projection image


Figure 6. Range profile of cross-correlated back projection image

Figure 7. Azimuth beam pattern of cross-correlated back projection image


Figure 8. Range profile of intra-pulse cross-correlated BP image

Figure 9. Azimuth beam pattern of intra-pulse cross-correlated BP image


Figure 10. Range profile of non-coherent cross-correlated BP image

Figure 11. Azimuth beam pattern of non-coherent cross-correlated BP image


Direct comparisons of these results reveal that the cross-correlated BP gives a sharper image in terms of the range resolution in both the down-range and the cross-range. These results assume that the center element of the array is the reference element for the correlation. These results can be significantly improved by using a remote reference element. This algorithm will be discussed in a later section. The standard back projection without cross correlation tends to produce image with higher side lobes, both in azimuth and in time. The non-coherent BP produces an image with a broad beamwidth and slow roll-off in the beam shape. The intra-pulse cross-correlated BP image tends to have a better resolution in the cross range due to a sharper azimuth beam pattern. With this particular UWB pulse function, the range resolution in the down range is approximately twice as wide in comparison to the straight cross-correlated BP image. However, it is possible to design a UWB pulse that also gives a compressed gain from the cross correlation and therefore also gives a better resolution in the down range. This topic is beyond the current scope of work and is a subject for future work. The resolution of the image in the cross range is determined by the azimuth beam pattern. In the multiple objects scenario, images of the larger objects tend to be smeared by its beam shapes and sidelobe levels (SLL) as one tries to lower the threshold level to locate smaller targets. Therefore, the beam shapes of the images also determine the ratio between the smallest target and the largest target that can be identified by radars. Table I compares the beam parameters of the four cases:

Table 1. Comparisons of Beam patterns of BP images

PARAMETER CASE I CASE II CASE III CASE IV

10dB Beamwidth 3.0 deg 3.0 deg 3.0 deg 16.0 deg

1st Null 4 deg 4 deg 4 deg N/A

Max Sidelobe level -6 dB -17 dB -18 dB -12 dB Footnote: Case I is standard back projection (Fig. 5) Case II is cross-correlated back projection (Fig. 7) Case III is intra-pulse cross-correlated back projection (Fig. 9) Case IV is non-coherent cross-correlated back projection (Fig. 11)

These results show that the cross-correlated BP image has a sharper beam shape in the cross range and smaller SLL. For this particular UWB pulse shape, the intra-pulse cross-correlated BP does not seem to have significant advantage over the cross-correlated BP case in the cross-range resolution. However, it does give an additional 6 dB of integration gain, which can contribute toward the overall improvement on the image signal-to-noise ratio (SNR). The non-coherent BP image tends to have a much larger beamwidth. In this case, the beamwidth is approximately eight times larger than the coherent case. This suggests that one should use the coherent BP unless measurement errors are too high.


3. Ultra-Wideband Remote Sensing

3.1 Introduction Our UWB through-wall measurements started in November 2002. This work started with indoor propagations and continued on to preliminary work on location of objects, including human subjects, buried in the snow. The system was then upgraded to standoff remote sensing and mine detection work. At present, the typical operating range of our UWB imaging radar is limited to 10m. For the standoff imaging, the overall range of the UWB measuring system was extended to 30m with an average transmit power of 1 watt. Finally, a high-resolution image reconstruction technique was also explored using the cross correlation BP method.

3.2 Indoor through-wall imaging The stepped-frequency UWB algorithm is first tested using an indoor facility. Fig. 12 shows the layout of the measurement set-up. The test range is divided into two chambers by a drywall. The dimensions of the chambers are approximately 7.14m (L) x 4m (W) x 2.43m (H) and 1.68m (L) x 4m (W) x 2.43m (H). The exterior walls are concrete (18cm, εr=7.0, tanδ=0.064). The drywall (1cm drywalls εr=2.75,tanδ=0.04, spaced at 10cm) is located at 1.68m from the front wall of the chamber. Fig. 13 and 14 show details of the test chambers. During the imaging measurements, the transmit and the receive antennas are located in the smaller chamber (Antenna chamber) while targets are placed in the larger chamber (Target chamber). Test equipment is set outside the test chamber. Measurements are made with the transmit antenna located at the center axis of the chamber and fixed at a distance of 1.3m away from the drywall. Receiver arrays are formed along the concrete wall behind the transmit antenna location.

Concrete

Con

cret

eC

oncr

ete

Con

cret

e

Dry

wal

lWin

dow

ConcreteDoor Door Concrete

HP 8510CNetworkAnalyzer

Transmitter

Target 3

Cylinder

Cylinder

Sphere

Receiver

LNA

15.24

OtherReceiverLocations

1300

16818 12 18714

403

Target 2

Target 1

121.92

Height = 243cm

All dimensions are in cm

91.44

91.44

213

201.5

243.84

Figure 12. Layout of indoor through-wall imaging test set-up


Figure 13. Antenna chamber

Figure 14. Target chamber

Drywall

Antennas

Target#2 Target#1

Ref Sphere


Fig. 15 shows a block diagram of the equipment configuration. The transmitter and receiver antennas are broadband double-ridge waveguide horns, ETS-EMCO Model 3115. The antenna gain of these horns is between 8 to 10dBi and half-power beamwidth of 50 to 60 deg within the operating frequency range. With the current VNA configuration, the maximum available transmit power from the VNA is approximately –10dBm. With a low noise amplifier (LNA, NF=3.0dB) at the front-end of the receive antenna, the instantaneous dynamic range of the system is approximately 90dB. By using a 20dB attenuator during calibrations, the overall dynamic range is improved to over 100 dB, which should allow detection of a human-size target at a distance of more than 20m. Values of the scattering parameter S21 are measured relative to a THRU calibration which is performed with the transmit antenna and the receive antenna spaced at a fixed distance of 90cm. Each frequency data is then weighted by the complex coefficients of the UWB signal. This data is then further processed using in-house software to produce the corresponding range profile for each receiver. The calibration path length (90cm) is taken into account during the range profile processing. The calibration effectively removes frequency dependence of all RF components including that of the LNA, antennas, cables and connectors. It also sets the reference amplitude and phase of the S21 to unity at the given reference path length. In a typical indoor environment, maximum variation in amplitude and phase of the reference S21 value can be maintained to well within ±0.1dB in amplitude and ±1.0deg in phase. Furthermore, during calibration, a 20dB attenuator is inserted at PORT1 of the VNA to ensure the linear operation of the LNA and the VNA. This 20dB attenuation is removed during data collection. The distortion due to the insertion of this 20dB attenuator is well within ±0.1dB in amplitude and ±3 deg in phase over the UWB frequency range. This distortion can also be compensated in the post processing.

CPU

ShortCable

Post-Processing

LongCable

Tx AntennaEMCO Model

3115

Rx AntennaEMCO Model

3115

Up to 15m of indoortest environment

LNA

DC Power Supply

HP 8510CNetworkAnalyzer

Figure 15. Equipment set-up


For these measurements, the parameter values S21 were collected over a frequency range from 850.54MHz to 3733.73MHz to form reflectivity profiles of the test range. Measurements were performed in stepped-frequency mode with 201 frequency points. With the time step fixed at 38.52ps, this setup allows profiling of a 2-way range up to a maximum distance of 17.3m with 1501 DFT points, and up to 20.8m with 1801 DFT points.

The path loss of the test range is first investigated by measuring the forward propagation field strength along the center axis of the test chamber at 60.96cm spacing. Fig. 16 shows the measured path loss. By comparing to a theoretical free-space path loss (1/r2), the measured losses are estimated to be 0.4-0.5dB for the drywall and approximately 4-5dB for the concrete wall.

Figure 16. Measured and calculated path losses

Fig. 17 and 18 show the simulated and the measured electric field strength with the receive antenna placed at 640cm from the drywall (780cm transmit-receive spacing). The difference in amplitude scale by a factor of 10 is a result of the use of 20dB attenuator during calibration.


Both results show similar potential false targets at larger distances due to multipath in the test chamber.

Figs. 19 and 20 show the simulated and measured range profiles of the received signals in through-wall radar mode. In this case, a sphere (D=42.5cm) is located at the target#1 position as shown in Fig. 12. Again, there is a scale difference due to the use of 20dB attenuator. However, the scale factor is now 100 instead of 10 because of the two-way propagation in the radar mode. The GO simulation agrees well with the measurement result. Both methods correctly located targets at their locations within a few centimeters. Figs. 21 and 22 compare the simulated and measured UWB pulses reflected from the drywall. The two results show similar pulse shapes and both methods show the wall thickness to be approximately 12cm (24cm 2-way).

Figs. 23 and 24 give simulation and measured 2D radar images constructed using range profile data generated by the GO ray-tracing and stepped-frequency measurement. In this case, all three targets are used: a sphere (D=42.5cm) and two cylinders (D=22cm, L=2.12m). These images are formed by back projection using the range profile data. Both results show targets at the same positions. In the single-look imaging (one transmit location), the drywall is shown as a curved surface because of its close proximity to the transmitter.

These results show that the high-frequency approximation (GO) modeling method agrees well with the measurements. This technique has the advantage of being able to take into account the frequency-dependent characteristics of the walls. Through a system calibration process, this method is capable of detecting UWB pulses without introducing signal distortion that may be caused by the frequency variation of the system components.


Figure 17. Simulated E [email protected]

Figure 18. Measured E Field @7.8m


0.0E+00

5.0E-04

1.0E-03

1.5E-03

2.0E-03

2.5E-03

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0

Range [m]

Am

plitu

de

Target at 2.13mfrom drywall

D

Drywall

Figure 19. Simulated radar range profile

Figure 20. Measured radar range profile


Figure 21. Simulated UWB pulse Reflected From the Drywall

Figure 22. Measured UWB pulse Reflected From the Drywall


Figure 23. Simulated 2D radar image

0.05

0.51

0.97

1.43

1.90

2.36

2.82

3.28

3.74

4.21

4.67

5.13

5.59

6.05

6.52

6.98

7.44

7.90

8.37

8.83

9.29

9.75

-2.26

-1.71

-1.16

-0.60

-0.05

0.51

1.06

1.62

2.17

0.00E+00

1.80E+00

3.60E+00

5.40E+00

7.20E+00

9.00E+00

Distance [m]

Cro

ss R

ange

[m]

Target#1

Target#2

DrywallBack Wall

Targer#3

Figure 24. Measured 2D radar image


3.3 Snow penetration The snow penetration experiments started in Jan 2003. These experiments were conducted at the front of the building 39 at DRDC Ottawa and are considered as preliminary studies on the subject of search and rescue operations in snow covered environment. The objective is to determine if a UWB radar can be suitably used as a remote sensing device to penetrate through a thick layer of snow and locate objects including human subjects. Fig. 25 shows the experiment layout. Fig. 26 shows the transmit and the receive antennas including the measurement equipments, which were located just inside the building 39. The door opening was covered with a large plastic sheet to shield the test equipment from the outdoor environment. Fig. 27 and 28 show the front- and the rear-view of the snow pile that was approximately 8’ wide, 8’ high and 17’ in length. An 8’x8’ plywood (1/2” thick) was used to support the snow at the front end of the snow pile.

Figure 25. Layout of snow penetration test set-up


Figure 26. Equipment set-up for the snow penetration experiment

Figure 27. Front end of the snow pile

Plastic shield Plywood

Tx Antenna

Rx Antenna

Snow


Figure 28. Rear view of the snow pile

This test set-up was first verified using two targets located behind the plywood before the snow was put in place. Fig. 29 and 30 shows the verification test set-up. The first target was a sphere located 0.9144m (3’) behind the plywood along the center axis. The second target was a cylinder, which is not shown in the figure, and was approximately 1.2192m (4’) behind the sphere and 0.6096m (2’) offset to the left side (view from the front) of the sphere.

The transmit antenna was located at a fixed position near the center axis of the door opening. The center of the receiver array was set at 6 inches behind and above the transmit antenna position. The receiver array was formed by manual scanning of the receive antenna at 6 inch spacing up to a maximum distance of +/-30 inches from the receiver array center. The VNA was located inside a shielded chamber to avoid interference from the radiation from the backlobe of the antennas. To further improve the amplitude and phase stability of the test set-up, the LNA and the RF cables (heliax) were wrapped in plastic sheet to provide additional thermal shielding from the cold temperature.

Building 39

Target#3


Figure 29. Verification test set-up for the snow experiment

Figure 30. Equipment set-up for the verification test

Plywood

Sphere

Tx Antenna Rx Antenna


Fig. 31 shows the measured range profile and Fig. 32 shows the computed 2-D radar image. The sphere and the cylinder targets are located within the predicted ranges and verify the test set-up.

Figure 31. Measured range profile of verification test set-up

Figure 32. Computed radar image of the verification test set-up


The experiment proceeded with three metallic targets. Target#1 and #2 were metallic sphere (D=42.5cm). Target#3 was a cylinder (L=2.12m, D=22cm). These targets were located as shown in the layout diagram (Fig. 25). The outdoor ambient temperature was approximately -15 deg C. The density of the snow was measured using a sample of the snow with a volume of 36x23x18cm. The total weight of the sample was 7.95 Kg (17.5 lbs), which translates to a density of approximately 533.4 kg/m3. Fig. 33 and 34 show the measured range profile and the computed radar image. Because the relative dielectric constant of snow is slightly higher than unity, these results are showing the apparent position of the targets.

Figure 33. Measured range profile of two spheres and one cylinder in snow


Figure 34. Computed radar image of two spheres and one cylinder in snow

So far, all targets are metallic. The next test was conducted with the second target (metallic sphere) replaced by a plastic sphere (D=42.5cm). The plastic sphere is made of a thin shell of fibre-glass (permittivity between 4.6 and 5.2). Fig. 35 and 36 show the corresponding measured range profile and the computed radar image. Notice that the echo signature of the plastic sphere is drastically different from that of a metallic sphere. A metallic sphere or cylinder tends to have a single spike at a fixed location, whereas the returned signal of the plastic sphere spreads over a range. Although the signal level of the plastic sphere is lower than that of a metallic sphere, it remains visible from the computed image.


Figure 35. Measured range profile of a plastic sphere, a metallic sphere and a cylinder

Figure 36. Computed radar image of a plastic sphere, a metallic sphere and a cylinder


The final case of the snow penetration experiments is a human subject. To accommodate a human subject, the second target (plastic sphere) was removed. A tunnel was dug from the right side of the snow pile (from the front view) near the second target location. The length of the tunnel was just sufficient to allow a human subject (approximately 6’). Fig. 37 shows the human subject in the tunnel. Fig. 38 and 39 show the measured rage profile and the computed radar image. Unfortunately, the limited accuracy of the set-up does not allow the use of coherent cross correlation BP for the image reconstruction. Instead the non-coherent BP is used in forming the radar image. Nevertheless, the results show that a human subject buried at this depth is clearly detectable using a UWB radar. Furthermore, the returned UWB signal from a human subject also differs from that of metallic objects. There are two distinct peaks for the human objects, one from the front surface and one from the back surface. These features can be used for target identification during a search and rescue operation. Further investigations are required on the subject to help identify a human subject from the other objects.

Figure 37. Snow penetration test with human subject

Human Subject


Figure 38. Range profile of human target

Figure 39. Radar image of human target


3.4 Standoff through-wall imaging Up to this point, the range of the experiment had been restricted to a maximum of 10m. One of the objectives of this study was to determine the feasibility of through-wall imaging at a remote distance. The challenge of UWB radar imaging at a remote distance are the cross-range resolution and the dynamic range of the receiver. The cross-range resolution is primarily set by the receiver array size. However, as discussed in section 2, the cross-range resolution can be further improved by using the cross-correlation BP. By inserting a medium power amplifier (1.2W) at the output of the VNA, the dynamic range of the set-up is further increased by more than 30 dB.

To accommodate for longer range (up to 30m) and to maintain approximately the same range resolution, a slightly different UWB pulse was used. More processing points and more frequency points are needed. The new UWB pulse is a Gaussian modulated sinusoidal with a slightly different function parameters ( 1,GHz5.1,,100,8.0 ===== pfA oπµσ ). This signal is similar to the previous UWB pulse; however, it has a larger time step (41.667ps) to allow for a longer range. Fig. 40 shows the UWB pulse and Fig. 41 shows the corresponding frequency spectrum. The frequency is stepped from 801.439 MHz to 4007.2 MHz. With the time step fixed at 41.667ps, this setup allows profiling of a 2-way range up to a maximum distance of 60.0m with 5001 DFT points.

Figure 40. UWB pulse for stand-off remote sensing


Figure 41. Frequency spectrum of stand-off UWB Pulse

The standoff through-wall imaging experiment was initially conducted at the building 39. A trailer was initially used to house the targets. It was stationed at approximately 26m away from the receiver array. A reference sphere was placed between the receiver and the trailer. Fig. 42 gives the layout of the measurement. The test was first conducted without target inside the trailer for verification of the test set-up. Fig 43 and 44 show the measured range profile and the computed radar image.

Figure 42. Layout of standoff imaging of a trailer


Note that there are strong reflections from the two I-beam support structures located just underneath the floor of the trailer. These echoes are relatively strong and are likely to over-shadow the returned echo from a target.

Figure 43. Range profile of the stand-off imaging of trailer

Figure 44. Radar image of the trailer


Nevertheless, the experiment proceeded with targets in place. Two cylinders were placed inside the trailers as shown in the layout diagram (Fig. 42). The measurement was conducted for both H- and V-polarization. Fig. 45 to 48 show the measured results.

Figure 45. Range profile of trailer with two cylinders (V-pol)

Figure 46. Radar image of trailer with two cylinders (V-pol)


Figure 47. Range profile of trailer with two cylinders (H-pol)

Figure 48. Radar image of trailer with two cylinders (H-pol)

In both the V-pol and the H-pol cases, targets are partially buried in the echos of the I-beam structures. The condition is more severe for the H-pol case. In either case, only the first cylinder is visible on the computed radar image. In an attempt to recover the target,


background subtraction is applied, i.e., the radar image of the trailer (without targets) is subtracted from the radar images of the trailer with targets. Fig. 49 to 52 show the range profile and radar image of the trailer with background subtraction.

Figure 49. Range profile of trailer with background subtraction (V-pol)

Figure 50. Radar image of trailer with background subtraction (V-pol)


Figure 51. Range profile of trailer with background subtraction (H-pol)

Figure 52. Radar image of trailer with background subtraction (H-pol)


With background subtraction, both targets are now visible in the V-pol case. However, the second target remains buried in the noise in the H-pol case. This indicates that the I-beam is likely to cause problems for the rest of the experiment. Therefore, the trailer was removed and an 8’x8’drywall was erected in place of the trailer. The experiment was repeated for the V-pol case with two cylinders behind the drywall. Fig. 53 shows the measured range profile. The two targets are clearly visible. Fig. 54 and 55 show the radar images computed using the standard back projection and the cross-correlation BP method. By comparing Fig. 54 and Fig. 55, it is evident that the cross-correlation BP image has a better cross-range resolution. The image of the first cylinder is smeared in the cross range and appears to be larger in the standard BP image. This is because the standard BP image has a wider beamwidth and the returned signal of the first cylinder is stronger compared to that of the second cylinder. As a result, the image of the first cylinder is broader in the azimuth direction as the threshold level is lowered to locate the second cylinder. This effect is not as severe in the cross-correlated BP image because the beamwidth of the cross-correlated BP image is narrower.

Figure 53. Range profile of the drywall with two cylinders


Figure 54. Back projection image of drywall with two cylinders

Figure 55. Cross-Correlated BP image of drywall with two cylinders


The effect of the reconstruction method on the cross-range resolution was further studied using targets of different sizes: a cylinder and a barrel. Fig, 56 shows the layout of the experiment. Fig. 57 shows the range profile. Fig. 58 and 59 show the computed radar images.

Figure 56. Layout diagram: drywall with a cylinder and a barrel

Figure 57. Range profile of drywall case with a cylinder and a barrel


Figure 58. Back projection image of drywall with a cylinder and a barrel

Figure 59. Cross-correlated BP image of drywall with a cylinder and a barrel


By comparing Fig. 58 and 59, again, it is evident that the cross-correlated back projection gives a sharper image and better resolution in the cross-range. Note that images of targets do not overlap in the azimuth direction in the cross-correlated BP image as in the standard BP image. Further investigation was carried out using a human and a cylinder. Fig. 60 shows the layout of the experiment. In this case, the distance between the receiver array and the drywall is set to approximately 20m. Fig. 61 shows the range profile. Fig. 62 and 63 show the computed radar images.

Figure 60. Layout diagram: drywall with a human and a cylinder

Figure 61. Range profile of drywall @20m with a human and a cylinder


Figure 62. Back projection image of drywall @20m with a human and a cylinder

Figure 63. Cross-correlated BP image of drywall @20m with a human and a cylinder


From the measured range profile (Fig. 61), the echo signal of the human subject is more than 10 dB below that of the cylinder, i.e., the ratio of signal strength between the two targets is more than 10dB difference. At this distance, if one tries to locate the smaller target using the back projection scheme, the image of the cylinder will be completely distorted in the cross range because of the azimuth beam shape. As shown in Fig.62, the image of the cylinder is badly distorted when the image of the smaller target (human) is made visible. This problem is much less severe in the cross-correlated BP image as shown in Fig. 63. Since the 10dB beam width of the cylinder is smaller in cross correlation BP case, both the barrel and human subject are clearly visible without severe distortion in the azimuth direction. Note that in the cross-correlated BP image, the human appears as an image with double spikes, as one would expect for a dielectric subject. One would expect that the problem becomes more severe at a larger distance. To verify this point, the experiment was carried out with the drywall moved to 25m (from receivers to the drywall). Fig. 64 shows the measured range profile. Again, the ratio of signal strength between the two targets remains in the order of 10dB. Fig. 65 and 66 show the computed radar images. In this case, the back projection algorithm is no longer able to resolve the targets. But the image quality is much improved by using the cross-correlation BP.

Figure 64. Range profile of drywall @25m with a human and a cylinder


Figure 65. Back projection image of drywall @25m with a human and a cylinder

Figure 66. Cross-correlated BP image of drywall @25m with a human and a cylinder


The next test represents a case of standoff remote sensing in a typical urban operation environment. The difficulty with this type of measurement is the added losses at the exterior wall of the building, which is typically made of brick or concrete. The one-way propagation loss of the wall is typically in the order of 10dB. In this case, Building 14 was chosen for the test. The building was vacated at the time and was well suited for the experiment. The exterior wall of the building is made of brick on concrete with an overall thickness of approximately 11 inches. One-way loss of such wall material is expected to be more than 10 dB. Fig. 67 shows the layout of the experiment.

Figure 67. Layout diagram of standoff test at building 14

Initially the standoff distance was set to approximately 7m, i.e., the receiver array was located at about 7m away from the exterior of the wall. Measurements were made for both vertical and horizontal polarization. Fig. 68 to 69 show the measured range profiles for the two polarizations. These results show that the first target is visible in the vertical polarization and is barely above the noise in the H-pol case. The second target is completely buried in the noise for both cases. Fig. 70 shows the computer radar image for the vertical case. The image is formed using intra-pulse cross-correlated BP to take advantage of the 6dB integration gain.


Figure 68. Range profile of building 14 @7m (H-pol)

Figure 69. Range profile of building 14 @7m (V-pol)


Figure 70. Radar image of building 14 @7m (V-pol)

The experiment was repeated for the vertical polarization with the receiver located at a distance of 27m away from the wall. Fig. 71 shows the measured range profile. In this case, signal levels of both targets are barely visible. Fig. 72 shows the image computed using the intra-pulse cross-correlated BP. As shown in the Fig. 72, even with this technique, only the first target is visible.

Cylinder


Figure 71. Range profile of building 14 @27m (V-pol)

Figure 72. Radar Image of building 14 @27m (V-pol)


3.5 Mine detection Other researchers have conducted similar work on the subject in the past [7]. The purpose of this effort is to gain understanding of mine detection using the UWB algorithm developed at DRDC. The main interest is to investigate the possibility of detection of medium to large size land mine from a standoff location at a slant angle. The experiment starts with mines placed on the surface of the sand. The idea was to repeat the same with the targets buried under the sand, if the targets are detectable. Unfortunately, the buried object cases were not completed due to the time and weather conditions. This work has yet to be further pursued in the future. This section summarizes the works completed on the subject thus far. The mine detection work starts off with two targets scattered on the surface of a typical sand surface. Fig. 73 and 74 show the layout diagram and the equipment setup.

Figure 73. Layout diagram of mine detection


Figure 74. Test set-up of mine detection

Fig. 75 to 77 show the types of land mine used for the test. Note that type 1 and type 3 mines are made of plastics. Fig. 78 and 79 show the measured range profile and computed radar image. The range profile shows the detection of signature from all three targets. However, the signal strength of the first and the second and targets are relatively weak, more than 14 dB below that of the third target. This is because only the third target is made of metal. Target #1 and #2 are made of plastic. Unfortunately, this test setup is not accurate enough to allow the use of cross correlation for the image reconstruction. The radar images are formed using the standard BP and only the third target is visible on the radar image.


Figure 75. Type #1 mine



Type: Circular disk Material: plastic (except firing pin) Thickness: 74 to 83 mm Diameter: 310 mm

Type: Cone Material: Metallic Thickness: 118 mm Diameter: 255mm

Type: Square disk Material: Plastic (except firing pin) Thickness: 112 mm Width: 270 mm Length: 295 mm


Figure 78. Range profile of mine detection

Figure 79. Back projection image of mine detection


The previous experiment was repeated in a more controlled environment. This time, targets were placed on a sand pile with a flat surface. Fig. 80 and 81 show the test set-up. Only two targets are used. The first target is of type 2 (metallic) and the second target is of type 1 (plastic).

Figure 80. Test set-up for mine detection (case #2)

Figure 81. Layout of mine detection (case #2)


Fig. 82 and 83 show the measured range profile and the back-projected image. Again, only the metallic mine is visible (target #1). The second target (plastic) is buried in the noise.

Figure 82. Range profile of mine detection (case #2)

Figure 83. Back projected image of mine detection (case #2)


The experiment was repeated with the locations of the two targets interchanged. This step is to verify that the detection of the target is not a result of the location. Fig. 84 shows the layout of the set-up.

Figure 84. Layout of mine detection (case #3)

Fig. 85 shows the measured range profile. The metallic mine (target #2) is clearly visible; however, target# 1 (plastic) is barely above the noise level. Fig. 86 shows computed radar image. In this case, target#1 (plastic) disappears from the map and only the target #2 is visible. This confirms that a plastic land mine of this size is much more difficult to detect. More work is needed in this area.


Figure 85. Range profile of mine detection (case #3)

Figure 86. Back projected image of mine detection (case #3)


4. High Resolution UWB radar imaging

4.1 Concept study Up to this point, the azimuth resolution of radar images is dictated by the overall array size. Although the cross correlation algorithm can provide superior image quality, the cross-range resolution remains limited for long-range remote sensing. This section explores the cross correlation algorithm for further improvement of the image resolution. Conventionally, only increasing the overall size of the array can reduce the beamwidth. For an impulse-like signal, the cross correlation formulation offers a possibility of achieving the same goal by cross correlating the element outputs to the output of a reference element that is located further away from the array center. Conceptually, the azimuth beam shape of a UWB array can be dramatically narrowed, if the location of the reference element is chosen such that its point response intercepts the point responses of other array elements at a large subtend angle. This can be achieved by locating the reference element away from the array center. The concept is simulated using the array layout shown in Fig. 87. The receiver array consists of 33 elements with a total length of 4.88m. The transmitter is located at 1.2192m in front of the receiver array center. A single target is assumed at 10m away from the array center along the Y-axis. The reference element is placed at a remote position as shown in Fig. 87. The radar image is calculated for two cases: (1) cross-correlation with the center element of the receive array as the reference correlation channel (2) cross-correlation with a remote element as the reference channel. Fig. 88 to 91 show the calculated azimuth beam patterns and the range profiles at the target position.

Figure 87. High resolution array configuration

4.88m Rx array

X

Y

Target (0.0,10m)

Reference element(-10m, 2.0m) Transmitter

(0.0,1.2192m)


Figure 88. Range profile with array center as reference channel

Figure 89. Azimuth beam pattern with array center as reference channel


Figure 90. Range profile with Reference Element as reference channel

Figure 91. Azimuth beam pattern with Reference Element as reference channel


Table 2 shows the results. Evidently, cross correlating the array elements with the remote reference improves the azimuth beam pattern dramatically. The beam shape rolls off at a very rapid rate and the SLL drops to below –50 dB. This shows a very significant improvement in the cross-range resolution. Of course, the performance will vary depending on the location of the reference element.

Table 2. Comparisons of beam patterns (HIGH RESOLUTION UWB)

PARAMETER CASE I (Center element as

reference)

CASE II (Remote element as

reference)

10dB Beamwidth 1.5 deg < 0.5 deg

1st Null 4 deg N/A

Max SLL -17 dB < -50 dB

4.2 High resolution imaging case study The high resolution UWB concept was tested at building 39. Fig. 92 shows the layout diagram of the test. A sphere and a cylinder were placed in front of a small hill as shown in the layout diagram (Fig. 92). The receiver array consists of 33 elements and is approximately 4.88m long. The transmit antenna is positioned at 1.292m in front of the receiver array center. Fig. 93 shows the measured range profile. Both targets and the hill are clearly detected. Note that the signal strength of the hill is approximately 8.5 dB above that of the targets. Fig. 94 shows the cross-correlated BP radar image with the center element of the array as the reference channel. Fig. 95 shows the cross-correlated BP image with the remote element as the reference channel. By contrast, it is evident that cross correlation with the remote reference gives a better resolution in the azimuth direction. The cross-correlation BP image using the remote channel as the reference not only shows the shape of the hill it also gives a sharper image of the two targets. This can be achieved only with a much better resolution in the cross range. Fig. 96 and 97 give the intra-pulse cross-correlated BP images. These results verify that cross correlation with the remote element as the reference gives a much better resolution in the cross range.


Figure 92. Layout of high resolution UWB Test

Figure 93. Range Profile of high resolution test


Figure 94. Cross correlated BP image (array center as reference)

Figure 95. Cross correlated BP image (Remote element as reference)

Sphere

Cylinder

Hill

Sphere

Cylinder

Hill


Figure 96. Intra-pulse cross correlated BP image (array center as reference)

Figure 97. Intra-pulse Cross correlated BP image (Remote element as reference)

Sphere Hill

Cylinder

Sphere

Cylinder

Hill


5. Discussion

Results of this report confirm the feasibility of UWB as an imaging radar for location of hidden objects behind common materials such as drywall, concrete, brick wall and snow. At this point, UWB work at DRDC remains at an early stage. Many aspects of the technology have yet to be explored. DRDC Ottawa continues to explore the UWB imaging in the areas of through-wall radar for urban operations, mine detection at standoff location, and search and rescue in snow covered environment. Further work in high resolution imaging techniques and target identification is essential in enhancing capabilities in these areas.

This report has demonstrated that a cross-correlation time reversal formulation can indeed be used to gain significant improvement in the cross-range resolution. Further improvement may be possible by applying this algorithm in conjunction with other types of UWB pulse, such as a linear phase modulated UWB, which gives higher integration gain, and a UWB pulse with a higher center frequency.

Identification of a human subject buried in the snow among other objects can be difficult since Doppler discrimination is not possible. Detection of mine composed primarily of plastic material is also a challenge. Further work on the high-resolution UWB radar and study of time and frequency signatures of various objects can help in these areas.


6. Conclusions This report summarizes the UWB work conducted at DRDC Ottawa, between Nov 2002 and Nov 2003. Results show that, even operating at a relatively low power, UWB radar can indeed penetrate various common materials with moderate losses and allows location of hidden targets behind walls or buried in snow. It is demonstrated that one can locate a human subject behind a drywall or concrete wall at a distance up to 30m with just 1 watt of average transmitter power. Furthermore, with an average transmit power of less than one milliwatt, UWB radar can be used to detect a human subject buried a few meter under snow at a standoff position of more than 5m away. The UWB has a fine resolution in the down range which is inherent to its short time duration. The cross-range resolution is, however, dictated by the size of the receiver array. This report presented a cross correlation time-reversal formulation that can be used to improve the cross-range resolution of the UWB radars. It is demonstrated that by cross correlating the receiver array with a remote element located farther away from the array center, the azimuth resolution is improved by many folds. This algorithm can potentially form a very high resolution UWB beam in both directions by using a more complex UWB pulse, which also provides a higher compression gain.


References

Ultra-wideband

[1] Taylor, D.J. (1995). Introduction to ultra-wideband radar systems. CRC Press. [2] Aiello, G.R., Rogerson, G.D. Ultra-wideband wireless systems. IEEE Microwave

magazine, June 2003, 36-47. [3] Browne, J. UWB proponents seek standardization. Microwave & RF, August 2003,

33-37. [4] Immoreev, I.J., Taylor, D.J. Future of radars. IEEE conference on Ultra Wideband

Systems and Technology, 2002, 197-199. [5] Keignart, J., Daniele, N. Subnanosecond UWB channel sounding in frequency and

temporal domain. IEEE conference on Ultra Wideband Systems and Technology, 2002, 25-30.

[6] Immoreev, I.J., Dmitry, P., Fedotov, V.Ultra wideband radar systems: advantages

and disadvantages. IEEE conference on Ultra Wideband Systems and Technology, 2002, 201-205.

[7] Digest of papers, 2002 IEEE Conference on Ultra wideband systems and

technologies. May 21-23, 2002, IEEE Catalog No. 02EX580. [8] Foo, S., Kashyap, S. Time-domain array factor for UWB antenna array. Electronics

Letters, Vol. 39, no.18, 4th September, 2003, 1304-1305. [9] Foo, S. EM modeling of UWB through-wall radar imaging using the high-frequency

geometrical optics (GO). Technical memorandum TM 2002-166, Defence R&D Canada, December 2002.

Image Reconstruction

[10] Herman, G.T. (1979). Image reconstruction from projections. Spriner-Verlag, Berlin, Heidelberg, New York.

[11] Kak, A.C., Slaney, M. (1987). Principles of computerized tomographic imaging.

IEEE Press, New York. [12] Lee, H., Wade, G. (1985). Imaging technology. IEEE Press, New York. [13] Haykin, S.S. (1985). Array signal processing. Prentice-Hall, Inc., Englewood Cliffs,

New Jersey.


[14] Carraea , W.G., Goodman, R.S., Majewski, R.M. (1995). Spotlight synthetic aperture radar signal processing algorithms. Artech House, Boston.

[15] Larsen, L.E., Jacobi, J.H. (1985). Medical applications of microwave imaging. IEEE

Press, New York. [16] Mersereau, R.M., Oppenheim, A.V. Digital reconstruction of multidimensional

signals from their projections. Proceedings of the IEEE, vol. 62, no. 10, 1319-1338, October 1974.

[17] Munson, D.C., O’Brien, J.D., Jenkins, W.K. A tomographic formulation of

spotlight-mode synthetic aperture radar. Proceedings of the IEEE, vol. 71, no.8, 917-925, August 1983.

[18] Desai, M.D., Jenkins, K.W. Convolution backprojection image reconstruction for

spotlight mode synthetic aperture radar. IEEE Transactions on image processing, vol. 1, no. 4 , 505-517, October 1992.

[19] Scudder, H.J. Introduction to computer aided tomography. Proceedings of the IEEE,

vol. 66, no. 6, 628-637, June 1978. [20] Lewitt, R.M. Reconstruction algorithms: Transform methods. Proceedings of the

IEEE, vol. 71, no. 3, 390-408, March 1983. [21] Macovski, A.M. Physical problems of computerized tomography. Proceedings of

the IEEE, vol. 71, no. 3, 373-378, March 1983.


List of acronyms BP Back Projection

dB Decibel

dBi Decibel in reference to an isotropic source

dBm Decibel in reference to one milliwatt

DFT Discrete Fourier Transform

DND Department of National Defence

DRDC Defence Research and Development Canada

EM Electromagnetic

FCC Federal Communications Commission

GHz Gigahertz (109 Hz)

GO Geometrical Optics

H-pol Horizontal polarization

LNA Low Noise Amplifier

MHz Megahertz (106 Hz)

PO Physical Optics

RF Radio Frequency

SBR Shooting and Bouncing Ray

SLL Side Lobe Level

SNR Signal to Noise Ratio

UWB Ultra-Wideband

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Defence R&D Canada - Ottawa, 3701 Carling Avenue, Ottawa, Ontario, K1A 0Z4

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Ultra-wdieband (UWB) remote sensing and radar imaging (U)

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Foo, Senglee; Walsh Alan; Kashyap, Satish

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DRDC Ottawa TR 2004-081

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The ultra-wideband (UWB) technology has an inherent fine resolution in time measurement and good penetration into many common materials. Used in conjunction with a time-reversal algorithm such as the back projection method, UWB radars are versatile RF imaging tools for remote sensing of objects hidden behind obstacle such as wall, sand and snow. DRDC Ottawa has conducted theoretical and experimental aspects of the UWB radar imaging in various areas using the stepped-frequency method. The method has been successfully applied in detecting and imaging targets hidden behind wall of various types, including detection of human subjects buried in the snow. A cross-correlated time-reversal algorithm was developed for the UWB image reconstruction. This algorithm enables UWB imaging radars to locate and resolve objects behind wall at a standoff position. In comparison to the standard back projection scheme, this algorithm produces images of superior quality with better cross-range resolution. It is also demonstrated that by cross-correlating the array elements with a reference element located further away from the array center, this algorithm is capable of improving the cross-range resolution of the radar images to the pulse-width of the UWB signal.

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UWB, ultra-wideband, through-wall, snow penetration, radar imaging, remote sensing

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