针对航空导航定位高可靠性的要求和GPS接收机观测噪声分布的特点, 研究将粒子滤波算法应用于接收机自主完好性监测(RAIM)中。通过粒子滤波算法对状态进行精确估计, 利用对数似然比建立一致性检验统计量进行故障检测与隔离。对算法进行了数学建模, 描述了完整的RAIM算法详细流程。通过实测数据对提出的RAIM算法进行验证, 结果表明:粒子滤波算法在非高斯测量噪声情况下可以对GPS接收机状态进行精确的估计, 利用对数似然比建立的一致性检验统计量能有效地检测并隔离故障卫星, 验证了该算法应用于GPS接收机自主完好性监测的可行性和有效性。
Aimed at high reliability of the aeronautical positioning and the measurement noise feature of GPS receiver, the particle filter algorithm is applied to GPS receiver autonomous integrity monitoring(RAIM).Estimating the state precisely with particle filter algorithm and using the log-likelihood ratio as a consistency test statistics to achieve the fault detection and isolation, satellite fault detection is undertaken by checking the cumulative log-likelihood ratio(LLR)of system state with detection threshold.Meanwhile, a detailed description of the algorithm flow is given.Based on real GPS data, the proposed RAIM algorithm is tested.Experimental results demonstrate that the particle filter algorithm under conditions of non-Gaussian measurement noise can estimate the state of GPS system accurately, and the log-likelihood ratio as the statistic of consistency test can effectively detect and isolate false satellites.Therefore, experimental results validate the feasibility and validity of particle filtering and likelihood of ratio methods for RAIM.
[1]Yun Y, Kim D.Integrity monitoring algorithms using filtering approaches for higher navigation performance:consideration of the non-gaussian gnss measurements[C].Proceedings of ION GNSS 20th International Technical Meeting of the Satellite Division, USA:ION, 2007:3070-3081.
[2]徐肖豪, 杨传森, 刘瑞华.GNSS用户端自主完好性监测研究综述[J].航空学报, 2013, 34(3):451-463.
[3]杨静, 张洪钺.卫星故障诊断的最优奇偶向量法[J].航空学报, 2002, 23(2):183-186.
[4]孙国良, 孙明菡, 陈金平.时一集综合的接收机自主完好性监测方法研究[J].航空学报, 2006, 27(6):1171-1175.
[5]Leppakoski H.Kuusniemi H, Takala J.RAIM and complementary kalman filtering for GNSS reliability enhancement[C].Proceedings of IEEE/ION Position Location and Navigation Symposium, 2006:948-956.
[6]Mathieu J, Boris P.Integrity risk of kalman filter-based RAIM[C].Proceedings of the 24th International Technical Meeting of The Satellite Division of the Institute of Navigation ION, SA:ION, 2011:3856-3867.
[7]Arulampalam M S, Maskell S, Gordon N, et al.A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking[J].IEEE Transactions on Signal Processing, 2002, 50(2):174-188.
[8]Fredrik Gustafsson, Fredrik Gunnarsson, et al.Particle filters for positioning, navigation, and tracking[J].IEEE Trans.on Signal Processing, 2002, 50(2):425-437.
[9]聂建亮, 杨元喜, 吴富梅.一种基于改进粒子滤波的动态精密单点定位算法[J].测绘学报, 2010, 39(4):338-343.
[10]LI P, Kadirkamanathan V.Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems[J].IEEE Transaction on Systems, Man, and Cybernetics, 2001, 31(3):337-343.
[11]Kaplan E, Hegarty C.Understanding GPS:principles and applications[M].Second Edition.MA, US:Artech House, Inc, 2006:239-264.
