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接收机自主完好性监测(RAIM)是航空卫星导航接收机必不可少的功能,为保持全球卫星导航系统(GNSS)在卫星发生故障时系统性能不降级,需要对卫星故障进行检测和隔离。针对接收机观测噪声非高斯分布的特点,提出一种基于粒子群优化粒子滤波(PSOPF)的故障检测和隔离算法。通过粒子群优化粒子滤波对状态估计进行一致性检验实现故障检测。采集实测数据验证算法的检测性能,并与基于基本粒子滤波的完好性监测算法进行比较,结果表明:本文所提算法在非高斯测量噪声下可检测并隔离全球定位系统(GPS)故障卫星,其性能优于基于基本粒子滤波的完好性监测算法性能,对研究北斗卫星导航系统(BDS)接收机自主完好性监测具有一定的意义。
Receiver Autonomous Integrity Monitoring (RAIM) is an indispensable function of the satellite navigation receiver. To keep the global satellite navigation system (GNSS) from degrading its performance in the event of a satellite failure, it is necessary to detect and isolate satellite faults. Aiming at the non-Gaussian distribution of the observed noise of the receiver, a fault detection and isolation algorithm based on Particle Swarm Optimization Particle Filter (PSOPF) is proposed. Particle swarm optimization particle filter consistency checking state estimation to achieve fault detection. The measured data were collected to verify the performance of the algorithm and compared with the algorithm based on the basic particle filter. The results show that the algorithm proposed in this paper can detect and isolate global positioning system (GPS) faulty satellites under non-Gaussian noise measurement, Performance is better than the performance of the integrity monitoring algorithm based on the basic particle filter, which is of great significance for studying the self-integrity monitoring of Beidou satellite navigation system (BDS) receiver.