MATEC Web of Conferences
Volume 44, 20162016 International Conference on Electronic, Information and Computer Engineering
|Number of page(s)||4|
|Section||Computer, Algorithm, Control and Application Engineering|
|Published online||08 March 2016|
Research on GPS Receiver Autonomous Integrity Monitoring Algorithm In the Occurrence of Two-satellite Faults
Shenyang Aerospace University, Shenyang 110136, China
2 Liaoning General Aviation Key Laboratory, Shenyang 110136, China
a Ershen Wang: firstname.lastname@example.org
Reliability is an essential factor for GPS navigation system. Therefore, an integrity monitoring is considered as one of the most important parts for a navigation system. GPS receiver autonomous integrity monitoring (RAIM) technique can detect and isolate fault satellite. Based on particle filter, a novel RAIM method was proposed to detect two-satellite faults of the GPS signal by using hierarchical particle filter. It can deal with any system nonlinear and any noise distributions. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the particle filter can estimate the posterior distribution more accurately. In order to detect fault, the consistency test statistics is established through cumulative log-likelihood ratio (LLR) between the main and auxiliary particle filters (PFs).Specifically, an approach combining PF with the hierarchical filter is used in the process of two-satellite faults. Through GPS real measurement, the performance of the proposed GPS two-satellite faults detection algorithm was illustrated. Some simulation results are given to evaluate integrity monitoring performance of the algorithm. Validated by the real measurement data, the results show that the proposed algorithm can successfully detect and isolate the faulty satellite in the case of non-Gaussian measurement noise.
Key words: Global positioning system (GPS) / Receiver autonomous integrity monitoring (RAIM) / Hierarchical Particle filter / Fault detection / Fault isolation
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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