强跟踪抗差自适应滤波算法及其在无人机导航定位中的应用

针对Sage-Husa自适应滤波算法在无人机导航定位应用中存在滤波发散和定位精度低的问题，本文提出一种强跟踪抗差自适应滤波算法。该算法在Sage-Husa自适应滤波算法基础上，引入强跟踪技术，通过自适应渐消因子降低历史数据对当前滤波的影响，从而抑制滤波发散，增强算法的稳健性；结合量测噪声和系统噪声进行实时估计，并且在估计中加入抗差因子抑制粗差对滤波的干扰，提高定位精度。仿真结果表明，该算法在发生滤波发散和粗差干扰的情况下能够表现出良好的滤波性能，较Sage-Husa算法有更强的稳健性。

Strong tracking robust adaptive filtering algorithm and its application on UAV navigation and positioning

Aiming at the problems that filtering divergence and low positioning accuracy in the application of Sage-Husa adaptive filtering algorithm in UAV navigation and positioning, a strong tracking robust adaptive filtering algorithm is proposed in this paper.The algorithm is based on Sage-Husa adaptive filtering, introduces the strong tracking technology in it, and reduces the influence of historical data on current filtering through adaptive fading factor, so as to suppress the divergence of filtering and enhance the robustness of the algorithm.The measurement noise and system noise are combined for real-time estimation, and the robust factor is added to the estimation to suppress the interference of outliers to the filtering and improve the positioning accuracy.Simulation results show that this algorithm can perform well in the case of filtering divergence and outliers, and has stronger robustness than Sage-Husa algorithm.