摘要
针对基于粒子滤波的接收机自主完好性监测(receiver autonomous integrity monitoring,RAIM)算法中普遍存在粒子退化和采样枯竭问题,提出基于鲁棒扩展卡尔曼粒子滤波(robust extended Kalman particle filter,REKPF)的RAIM算法。该算法利用扩展卡尔曼滤波计算粒子的建议密度函数,引导重采样做出更加准确的采样分布;同时,为了减小伪距偏差对滤波估计的影响,利用抗差估计对卡尔曼增益矩阵进行修正。通过实测数据构建卫星故障检测的检验统计量,对各状态的累加对数似然比进行一致性检测。仿真结果表明,当存在伪距偏差时,基于REKPF的RAIM算法能够有效诊断故障星,缩短告警延迟时间,提高定位精度,算法性能更好。
Since the problems of particle degeneracy and sample impoverishment exist commonly in the particle filter used in the receiver autonomous integrity monitoring（RAIM）algorithm,a RAIM algorithm based on robust extended Kalman particle filter（REKPF）is proposed.In this method,the extended Kalman filter is used to calculate the proposed density function,so that the sampling distribution of re-sampling is more accurate.Meanwhile,in order to reduce the influence of pseudo-range bias on the filter estimation,the Kalman gain matrix is corrected by robust estimation.Based on the real global position system data,the statistic of consistency test of satellite fault detection is established,and then the cumulative logarithmic likelihood ratio of each state is compared to detect the faulty satellite.Simulation results demonstrate that,when there is a pseudorange bias on a satellite,the RAIM algorithm based on REKPF can diagnose the faulty satellite effectively,shorten the alarm delay time,and improve the position accuracy,thus the performance is better.
作者
彭雅奇
许承东
牛飞
李臻
范国超
PENG Yaqi;XU Chengdong;NIU Fei;LI Zhen;FAN Guochao(School of Aerospace Engineering,Beijing Institute of Technology,Beijing 100081,China;Beijing Satellite Navigation Center,Beijing 100094,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2018年第12期2790-2796,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61502257)资助课题
关键词
接收机自主完好性监测
鲁棒扩展卡尔曼粒子滤波
故障检测
对数似然比
receiver autonomous integrity monitoring （RAIM）
robust extended Kalman particle filter （REKPF）
fault detection
log-likelihood ratio （LLR）
