基于斜率加权的最小二乘RAIM算法研究

An RAIM Algorithm Based on Slope-Weighted Least Square Method

为解决某些卫星在故障检测算法中不敏感的问题,提出了卫星斜率加权的最小二乘算法。该方法从理论上推导出卫星特征斜率的表达式,根据特征斜率大小构建斜率加权矩阵,对特征斜率较小的卫星加以更大的权重。构造出斜率加权的检验统计量,通过比较新的检验统计量与检测门限,实现对卫星的故障检测。结合真实数据对该方法进行验证,结果表明:基于斜率加权的最小二乘RAIM算法的故障检测率优于最小二乘RAIM算法。

In order to solve the problem that some satellites are not sensitive in the fault detection algorithm a Slope-Weighted Least Square(SWLS)algorithm is proposed.This method theoretically derives the expression of the satellite feature slope constructs the slope-weighted matrix according to the size of the feature slope and gives greater weight to the satellite with smaller feature slope.The slope-weighted test statistics are constructed and the satellite fault detection is realized by comparing the new test statistics with the detection threshold.This method is verified by using real data and the results show that the fault detection rate of the slope-weighted least square RAIM algorithm is better than that of the least square RAIM algorithm.