摘要
针对深水机器人导航定位算法的鲁棒性问题,提出基于M估计的扩展卡尔曼滤波算法。该方法通过采用M估计评价函数引入加权矩阵,从而对观测异常值进行修正。不仅将M估计应用到非线性系统,同时也很好地抑制了观测异常值对导航算法的影响。通过仿真实验验证了该方法的有效性。
To improve the robustness of navigation and positioning algorithm for deep water robot,we propose an M-estimate-basedextended Kalman filter （EKF）algorithm.By the use of M-estimate evaluation function,the method introduces weighting matrix so as tocorrect the observed outlier.This applies the M-estimate in nonlinear system,and well retrains the impact of the observed outlier onnavigation algorithm too.The effectiveness of the algorithm is verified through simulation test.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第9期249-252,共4页
Computer Applications and Software
基金
辽宁省自然科学基金项目(2236)
关键词
导航定位
异常值
鲁棒性
M-估计
Navigation and positioning
Outlier
Robustness
M-estimate
