GNSS/INS组合导航系统中异常观测的探测与抑制  

Detection and Resistance of the Outlying Observation in GNSS/INS Integrated Navigation System

作　　者：李科[1] 金际航[1] 常国宾[1] 

机构地区：[1]海军海洋测绘研究所,天津300061

出　　处：《海洋测绘》2015年第1期25-29,共5页Hydrographic Surveying and Charting

基　　金：国家自然科学基金(41414001)

摘　　要：在隧道、城市峡谷、多径效应明显等恶劣环境中,GNSS定位结果易受异常值影响。GNSS异常值的存在使得观测噪声服从Gauss分布的假设不再成立,从而将严重影响GNSS/INS组合系统中Kalman滤波的性能。本文将抗差Kalman滤波用于GNSS/INS组合导航系统中异常观测的探测与抑制。根据设定的显著性水平对Kalman滤波的新息向量进行c2检验,原假设被拒绝时认为异常观测存在;然后引入尺度化因子对新息向量的协方差矩阵进行膨胀,以抑制异常观测对滤波结果的影响,并通过解析方法求解该因子。数值仿真的结果验证了算法的有效性。Outliers exist almost inevitably in GNSS positioning results under adverse conditions,such as tunnels,canyons,and those with multipath effect. These outliers will violate the assumption about the Gaussianity of the observation noise,and hence will severely degrade the performance of the Kalman filter for GNSS/INS integration. Robust Kalman filter is employed in this paper to detect and resist observation outliers. The χ2test is performed for the innovation vector. If the null hypothesis is to be rejected,outliers are deemed to be present.Then a scaling factor,which can be calculated in closed form,is introduced to inflate the covariance matrix of the innovation vector,and hence the impact of the outliers is effectively restrained. Simulation results validate the efficacy of the algorithm.

关 键 词：组合导航 异常观测 KALMAN滤波 抗差 χ2检验 

分 类 号：P228.1[天文地球—大地测量学与测量工程]