KMS Chongqing Institute of Green and Intelligent Technology, CAS
| Research on receiver autonomous integrity monitoring algorithm using genetic algorithm resampling particle filter | |
He, Pan ; Tan, Chun; Huang, Huawen
| |
| 2013 | |
| 摘要 | With the rapid development of global navigation satellite system, Receiver Autonomous Integrity Monitoring (RAIM) has attracted attention from many researchers and there still are a lot of unsolved problems in this field. Traditional RAIM algorithms are built upon Kalman filter under the assumption that satellite signal noise follows Gaussian distribution. However, with the impact of ionospheric delay error and other factors, the measurement noise usually doesn't follow Gaussian distribution. Under strong interference and harsh environmental conditions, particle filter is often employed to improve the efficiency of RAIM with non-Gaussian distribution errors. But those algorithms on particle filter are poor in convergence accuracy and stability because of particle degeneracy and this paper aims to provide a solution for particle degeneracy. Using the idea of approximate probability, this paper also takes use of particle filter in RAIM for fault detection and employs the idea of genetic operations to avoid particle degrading too early. Based on the classic particle filter procedure, simulation binary crossover operator, polynomial mutation operator and roulette wheeling selection method are used to produce new generation of particles from old generation in resampling process to increase particle diversity in state space as well as keeping good performance particles. The modified particle filter is then used in the fault detection and isolation process of RAIM with cumulative log likelihood ratio test. Finally, experiment are conducted using IGS tracking station observation data and the results showed that, our algorithm could be used to detect and isolate faults under non-Gaussian noise environment, which proved the efficiency of our algorithm in RAIM. Comparing with RAIM algorithms based on traditional particle filters, our algorithm could improve the fault detection accuracy and convergence rate under non-Gaussian noise conditions as well as avoiding particle degeneracy. © 2013 Springer-Verlag Berlin Heidelberg. |
| 语种 | 英语 |
| DOI | 10.1007/978-3-642-37404-3-20 |
| 会议(录)名称 | 4th China Satellite Navigation Conference, CSNC 2013
 |
| 页码 | 221-231 |
| 通讯作者 | He, P. (hepan@cigit.ac.cn) |
| 收录类别 | EI |
| 会议地点 | Wuhan, China |
| 会议日期 | May 13, 2013 - May 17, 2013 |
