12
航測及遙測學刊 第十三卷 第三期 183-194 民國 97 9 183 Journal of Photogrammetry and Remote Sensing Volume 13, No.3, Sepetmber 2008, pp. 183-194 多參考站 GPS 動態定位演算法之研究 朱康文 1 吳 究 2 謝吉修 3 中長距離 GPS 定位存在與距離相關的各種誤差,如大氣折射,這些誤差使單時刻相位模稜解算成功 率降低,進而影響定位精度。使用多參考站可以模式化參考站與使用者間與距離相關的各種誤差,期望 可以增加使用者的移動距離或提升定位精度。本研究目的在利用已知坐標,找出參考站間的相對對流層 天頂向延遲(Relative Tropospheric Zenith Delay, RTZD),並提供移動站內插改正數,以得到更精確的定位 結果。主要工作分為三個階段:(1)使用虛擬 RTZD 觀測方程式,計算參考站間的 RTZD(2)根據參考站 數目,選擇適當的改正面函數;(3)動態定位。本研究方法僅需使用一至三時刻觀測量即可成功獲得定位 整數解,可降低周波脫落或資料中斷影響。實驗結果指出,若能正確求得參考站間 RTZD,並使用適當 的內插模式,則可改善定位精度。 關鍵詞:多參考站、GPS 動態定位、對流層天頂向延遲 1. 前言 GPS(Global positioning system)已廣泛應用於 測量及導航定位,近年來,使用者對於 GPS 即時 動態(Peal-Time Kinematic, RTK)定位的需求漸增, 常見的單基線 RTK 已發展相當成功,但是在動態 定位時,由於觀測量驟減,一旦移動距離增加,即 受大氣折射的影響,造成相位模稜解算失敗,無法 得到精確的定位解,移動站始終被限制在參考站附 近數公里內。 大氣效應影響的主要因素為電離層與對流層 路徑延遲,將電離層視為附加參數的方式,與其他 未知參數一併求解的方法經過實驗證實,對於長距 離基線有顯著的幫助(Goad and Yang, 1997)。對流 層影響一般採用模式估計,利用溫度、溼度、氣壓, 配合適當的氣象模式,但是往往沒辦法完全估計, 當基線距離增加,這些殘餘的對流層影響仍會在求 解相位模稜時造成錯誤,降低定位精度。 以多參考站取代傳統單參考站的 RTK 定位, 希望可以增加使用者的移動距離及獲得較高精度 的坐標成果。使用多參考站的好處之一,即提高 RTK 服務的可靠度及可行性,因為當有參考站失 去作用時,尚有其他參考站可供使用(Hu et al., 2003)。另一最重要的關鍵,參考站擁有精確的坐 標,可產生與距離相關的各種偏差改正,如大氣延 遲誤差及軌道誤差,經由模式化後可提供使用者適 當的改正值,以支持中長距離的相位定位(Dai et al., 2003)改正值的正確與否會影響使用者端的定位精 度,為了提供正確的改正值給使用者,多參考站各 基線間的整數相位模稜(Phase ambiguity)必須正確 的決定,但是隨著參考站間距離的增加,大氣折射 效應造成即時相位模稜不易求定。本文針對中長距 離的多參考站定位提出即時相位模稜解算的方法, 估計該時刻大氣延遲量,本方法使用少觀測量,所 以較不受周波脫落(Cycle slips)及資料中斷的影響。 相位模稜固定後利用線性內插求得使用者端的改 正值,以改善定位精度。 1 國立中央大學土木工程學系空間資訊組碩士 2 國立中央大學太空及遙測研究中心暨土木工程學系教授 3 國立中央大學土木工程學系空間資訊組博士生候選人 收到日期:民國 97 年 10 月 22 日 修改日期:民國 97 年 12 月 08 日 接受日期:民國 97 年 12 月 21 日

多參考站GPS動態定位演算法之研究 - CSPRS

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<4D6963726F736F667420576F7264202D2039374F323230315FA668B0D1A6D2AFB8475053B0CABA41A977A6ECBA74BAE2AA6BA4A7ACE3A8735FB2C433BD675F> 183-194 979 183 Journal of Photogrammetry and Remote Sensing Volume 13, No.3, Sepetmber 2008, pp. 183-194
GPS

(1) RTZD RTZD(2)
(3)

1.
(Peal-Time Kinematic, RTK)

184 97 9
2.
2.1
(Double difference)

( ) gh ij
gh g g h h gh gh gh gh ij i j i j ij ij ij ijR T I N vλ λ
Φ Φ = − − + = + − − +
gh ij
gh g g h h gh gh gh ij i j i j ij ij ijR T I v
ρ ρ ρ ρ ρ ρ= − − + = + + +
ij
gh λ
gh ijN gh
ijΦ
GPS
ij m n
gh gh gh gh gh gh ij m n m n ij m n ij m n ij m n ij m n ijR N I T vλ λ
Φ Φ = = + + + +

+ (4)
, 1 2 gh gh gh ij m n ij ijN mN nN= + ,
gh ij m nI
(m)
+ =
+
(1)(2)(3)

gh wijN L1
1 gh ijN


m (m) 0
2 2 2 /1( )(1 e ) 2
d D mσ σ −
wijN
L1
1, 2, 2 1/ /I I f f =

GPS L1, L2 1 2/ 77 / 60f f = −
77m = ,
60n = − (3)
77, 60 1 77, 60
(77 60 )
gh gh gh ij ij ij
gh gh gh gh ij ij wij ijR N N T
λ
λ λ ε −
gh ijT (2001)
1 1 1 1 1[( ) ( )] 2 cos cos cos cosh g h g
j j i i
= − + − (8)
(8)(7) gh ijT
gh ijT MF z= × (9)
(9)z
'z 0 (m)


l
m
2 iσ
(Accompanying) n × n Ci (n
)

2
1
m
2 iσ Ci
Q
2 1, {1,..., }i i mσ ≅ ∈

Yeh, 2005)
BC B Q (12)

(m=4)



/ ( , , / 2) ( , ,1 / 2)
χ α α
1 2d d


1
RTZD
1
1 1
EΔ , NΔ TWD97(Taiwan
Datum 97, 1997 )
RTZD
1 1 1u u uz a E b N c= Δ + Δ + (15)
1uz RTZD 1uEΔ
iuNΔ 1uNΔ

RTZD

error) ( Mean, Sigma,

2006 3 13 21:03 21:13
CSRF()SPP0
3 1
2
RTZD
RTZD



L1
RTZD)

2 RTZD
1

2
3
0 200 400 600 Time (epochs)
-0.10
-0.05
0.00
0.05
0.10
-0.10
-0.05
0.00
0.05
0.10
8 NTPU
RTZD


3 5
(Mean)(Sigma)(RMSE,
(MRS)
(cm) RMSE Sigma Mean
SBL 1.53 0.44 -1.46
MRS 1.51 0.44 -1.45
(cm) RMSE Sigma Mean
SBL 2.97 2.29 -1.89
MRS 1.81 0.34 -1.77
(cm) RMSE Sigma Mean
SBL 4.88 4.03 2.76
MRS 2.87 1.99 2.86
2007 4 19 17:00 17:10
CSRF()SPP0SINPNTPU
XINU 9
6 7~8 GDOP
3.0 ~ 3.3 CSRF XINU 2 Hz
1 Hz 15.0°
7
CSRF_SINP

RTZD

-0.05
0
0.05
0.1
-0.20
-0.10
0.00
0.10
0.20
0.30

7
10 RTZD (CSRF_NTPU)
11 RTZD (CSRF_SINP)
12 RTZD (CSRF_SPP0)
(cm) RMSE Sigma Mean
SBL 4.02 0.49 -4.00
MRS 3.98 0.32 -3.97
0 200 400 600 Time (epochs)
-0.10
-0.05
0.00
0.05
0.10
-0.10
-0.05
0.00
0.05
0.10
-0.10
-0.05
0.00
0.05
0.10
-0.1
-0.05
0
0.05
0.1
(cm) RMSE Sigma Mean
SBL 5.10 0.94 -5.01
MRS 4.16 0.46 -4.14
(cm) RMSE Sigma Mean
SBL 9.38 2.32 -9.10
MRS 1.37 1.29 -0.46
YMSM TPSODYSSEY_E TPSCR3_GGD
12
(km) 8.8 20.8 37.2 12.3 12.3
3.3 NTPU_XINU
NTPU_XINU
2007 4 15 23:35 23:40
NTPU()CSRFSPP0SINP
YMSM 15
3.0 ~ 3.3 CSRF XINU 2 Hz
1 Hz 15.0°
12
NTPU_SPP0 NTPU_YMSM
NTPU SPP0
(37.2 km) NTPU YMSM
NTPU 60.9 m
YMSM 784.0 m RTZD
RTZD 20
21 XINU
22
23

-0.16
-0.12
-0.08
-0.04
0.00
0.04
80% 23


13 15

-0.1
-0.05
0
0.05
0.1
-0.1
-0.05
0
0.05
0.1
-0.1
-0.05
0
0.05
0.1
-0.1
-0.05
0
0.05
0.1
-0.1
-0.05
0
0.05
0.1
22 XINU
23 XINU
13 XINU (N)
(cm) RMSE Sigma Mean
SBL 3.44 0.73 -3.37
MRS 3.38 0.26 -3.37
14 XINU (E)
(cm) RMSE Sigma Mean
SBL 0.98 0.74 -0.65
MRS 0.82 0.37 -0.73
15 XINU (H)
(cm) RMSE Sigma Mean
SBL 2.93 2.34 1.74
MRS 2.76 2.04 -1.87

“Simplified formulae for the BIQUE estimation
of variance components in disjunctive
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No. 6, pp. 447-457.
Dai, L., Han, S., Wang, J., and Rizos, C. (2003),
“Comparison of interpolation algorithms in
network-based GPS techniques.” Navigation, Vol.
50, No. 4, pp. 277-293.
Goad, C. C. and Yang, M. (1997), “A new approach
to precision airborne GPS positioning for
photogrammetry.” Photogrammetric Engineering
1067-1077.
Hu, G. R., Khoo, H. S., Goh, P. C., and Law, C. L.
(2003), “Development and assessment of GPS
virtual reference stations for RTK positioning.”
Journal of Geodesy, Vol. 77, No. 5-6, pp.
292-302.
John Wiley & Sons, Inc., Hoboken.
Wu, J. and Yeh, T. F. (2005), “Single-epoch
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Navigation, Vol. 52, No. 1, pp. 39-47.
194 Journal of Photogrammetry and Remote Sensing Volume 13, No. 3, Sepetmber 2008
Research on GPS Kinematic Positioning with Multiple
Reference Stations
ABSTRACT The distance-dependent GPS errors, notably atmospheric refraction, reduce the success rate of
epoch-by-epoch ambiguity resolution, and limit the GPS positioning accuracy, especially for medium- to long-range baselines. Using multiple reference stations to model (or interpolate) the distance-dependent biases between the reference station and a rover can extend the distance or improve the positioning accuracy. The objective of this research is to find out the relative tropospheric zenith delays (RTZD) between different reference stations by using known coordinates and to provide rovers with interpolated corrections for more precise positioning. The project consists of three major steps: (1) finding out the RTZDs between reference stations, (2) modeling the RTZDs; (3) kinematic positioning. In the first step, a pseudo observation equation of RTZD is added in order to reduce the impact of RTZD on ambiguity resolution. In the second step, different model is used according to the numbers of reference stations. These two steps are the emphases of this investigation. The proposed method needs only one to three epochs to resolve ambiguities, so the effects of cycle slip or data gap are not very serious. A multiple reference stations network located in north Taiwan is used in this research. There are six permanent GPS stations in this network. Test result indicates that if the RTZDs between different reference stations can be resolved successfully, and a proper interpolation model is used, it is possible to improve the positioning accuracy.
Keywords: Multiple reference stations, GPS kinematic positioning, Tropospheric zenith delay
1 Graduate Student, Department of Civil Engeneering, National Central University 2 Professor, Centor for Space and Remote Sensing Research, National Central
University 3 Ph. D. Candidate, Department of Civil Engeneering, National Central University