野值会严重影响滤波器的稳定性和滤波精度。以自主水下航行器(Autonomous UnderwaterVehicle,AUV)为应用背景,通过分析AUV中低精度组合导航系统的特点和误差模型,针对野值可能产生的影响,提出了一种由Sage_Husa自适应滤波和抗野值修正算法结合而成的自适应抗野值Kalman滤波算法。仿真结果表明,自适应抗野值Kalman滤波算法提高了滤波器的滤波精度和稳定性,具有较好的工程实用价值。 Outliers will seriously affect the filter stability and filtering accuracy. Based on the application of Autonomous Underwater Vehicle (AUV), this paper analyzes the characteristics and error model of low-precision integrated navigation system in AUV. Based on the possible influence of outliers, this paper proposes an adaptive underwater vehicle (SUV) An Adaptive Inverse Kalman Filtering Algorithm Combining Outliers Correction Algorithm. Simulation results show that the adaptive anti-outliers Kalman filter improves the filtering accuracy and stability, and has good engineering practical value.