Earticle

초록

영어

Reliability is an essential factor for GPS navigation system. Therefore, an integrity monitoring is considered 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 based probability test. The particle filter is popular filtering methods to estimate states of a general dynamic system. 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 and the application of the RAIM method, the performance of the proposed GPS two-satellite faults detection algorithm was illustrated. Some simulation and experiment results are given to evaluate integrity monitoring performance of the algorithm. Validated by the real experimental data, the results show that the proposed algorithm can successfully detect and isolate the faulty satellite in the case of non-Gaussian measurement noise.

목차

Abstract
 1. Introduction
 2. Particle Filter Algorithm
 3. Hierarchical Particle Filter for Two-Satellite Faults Detection
  3.1. Test Statistics Establishment
  3.2. Hierarchical Particle Filter for Fault Detection
  3.3. Hierarchical Particle Filter Algorithm Flow for GPS RAIM
 4. Experiment Testing and Results Analysis
  4.1. Experiment Results under Normal Condition
  4.2. Fault Testing Results under Two-Satellite Faults Condition
 5. Conclusions
 References

키워드

저자

• Ershen Wang [ Shenyang Aerospace University, Shenyang, China ]
• Tao Pang [ Shenyang Aerospace University, Shenyang, China ]
• Yongming Yang [ Shenyang Aerospace University, Shenyang, China ]
• Shujie Zhangand Pingping Qu [ Shenyang Aerospace University, Shenyang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605