Title
Equivalence Proof And Performance Analysis Of Weighted Least Squares Residual Method And Weighted Parity Vector Method In Raim
Abstract
Besides accuracy, integrity is another important performance measure of GNSS. The classical least-squares-residual (LSR) method and parity vector (PV) method are often used in the receiver autonomous integrity monitoring (RAIM). The two fault detection methods assume that the observation errors of different satellites are the same, ignoring possible variations of accuracy between observations. In this study, the mathematical models of the weighted least-squares-residual (WLSR) method and the weighted parity vector (WPV) method are derived in detail. The equivalence of the two methods is established with statistical tests. The WPV method is applied to detect those faults based on both GPS and BDS observations collected at Wuhan JiuFeng Station (JFNG). The theoretical results show that this method has lower computational complexity than the WLSR method, hence more suited for cases requiring fast fault detection. The fault detection rate increases as the deviation of the pseudorange observation increases. Thus, using the threshold value T-d of the posterior unit weight error (sigma) over cap (0), the WPV achieves a higher fault detection rate than using a priori unit weight error sigma(0). The experiments show that these two methods can detect relatively large faults, it is possible to detect them in GPS observations if sigma(0) is more than 12xbias (1xbias=8 m) and (sigma) over cap (0) superior to 4xbias, whereas the faults detection in BDS observations requires a deviation bigger than 8xbias and 6xbias, respectively. But these two methods are insensitive when the deviation is smaller.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2929073
IEEE ACCESS
Keywords
DocType
Volume
Weighted least-squares-residual, weighted parity vectors, receiver autonomous integrity monitoring (RAIM), fault detection
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Xiaping Ma100.34
Kegen Yu255657.05
Jean-Philippe Montillet3577.63
Xiaoxing He400.34