Precise relative positioning using real tracking data from COMPASS GEO and IGSO satellites

China completed a basic COMPASS navigation network with three Geostationary and three Inclined Geosynchronous satellites in orbit in April 2011. The network has been able to provide preliminary positioning and navigation functions. We first present a quality analysis using 1-week COMPASS measurements collected in Wuhan. Satellite visibility and validity of measurements, carrier-to-noise density ratio and code noise are analyzed. The analysis of multipath combinations shows that the noise level of COMPASS code measurements is higher than that of GPS collected using the same receiver. Second, the results of positioning are presented and analyzed. For the standalone COMPASS solutions, an accuracy of 20 m can be achieved. An accuracy of 3.0 m for the vertical, 1.5 m for the North and about 0.6–0.8 m for the East component is obtained using dual-frequency code only measurements for a short baseline. More importantly, code and phase measurements of the short baseline are processed together to obtain precise relative positioning. Kinematic solutions are then compared with the ground truth. The precision of COMPASS only solutions is better than 2 cm for the North component and 4 cm for the vertical. The standard deviation of the East component is smaller than 1 cm, which is even better than that of the East component of GPS solutions. The accuracy of GPS/COMPASS combination solutions is at least 20 % better than that of GPS alone. Furthermore, the geometry-based residuals of double differenced phase and code measurements are analyzed. The analysis shows that the noise level of un-differenced phase measurements is about 2–4 mm on both B1 and B2 frequencies. For the code measurements, the noise level is less than 0.45 m for B1 CA and about 0.35 m for B2 P code. Many of the COMPASS results presented are very promising and have been obtained for the first time.

[1]  P. Teunissen Least-squares estimation of the integer GPS ambiguities , 1993 .

[2]  C. Tiberius,et al.  ESTIMATION OF THE STOCHASTIC MODEL FOR GPS CODE AND PHASE OBSERVABLES , 2000 .

[3]  Christian Tiberius,et al.  VARIANCE COMPONENT ESTIMATION AND PRECISE GPS POSITIONING: CASE STUDY , 2003 .

[4]  AA Verhagen,et al.  Algorithms for design computations for integrated GPS-Galileo , 2003 .

[5]  X. Chang,et al.  MLAMBDA: a modified LAMBDA method for integer least-squares estimation , 2005 .

[6]  A. Amiri-Simkooei,et al.  Assessing receiver noise using GPS short baseline time series , 2006 .

[7]  Jean-Luc Issler,et al.  Compass Signal Structure and First Measurements , 2007 .

[8]  Liu Jing-nan,et al.  PANDA software and its preliminary result of positioning and orbit determination , 2003, Wuhan University Journal of Natural Sciences.

[9]  Jingnan Liu,et al.  Recent development of PANDA software in GNSS data processing , 2008, International Conference on Earth Observation for Global Changes.

[10]  M. Cannon,et al.  Evaluation of Compass Ambiguity Resolution Performance Using Geometric-Based Techniques with Comparison to GPS and Galileo , 2008 .

[11]  Todd Walter,et al.  Compass-M1 Broadcast Codes in E2, E5b, and E6 Frequency Bands , 2009, IEEE Journal of Selected Topics in Signal Processing.

[12]  Zhang Shao-cheng,et al.  An Analysis of Satellite Visibility and Relative Positioning Precision of COMPASS , 2010 .

[13]  Zhizhao Liu,et al.  A new automated cycle slip detection and repair method for a single dual-frequency GPS receiver , 2011 .

[14]  O. Montenbruck,et al.  Characterization of Compass M-1 signals , 2011, GPS Solutions.

[15]  Initial Observations and analysis of Compass meO Satellite Signals , .