基于强跟踪滤波的车载行进间对准

In-motion alignment based on strong tracking filter

针对车载行进间对准过程中存在复杂路面和未知干扰的情况,提出基于强跟踪滤波的里程计辅助车载捷联惯导行进间对准方法。采用多重渐消因子的强跟踪滤波器进行车载行进间精对准。多重渐消因子的强跟踪滤波器利用卡尔曼滤波取得最佳增益时残差序列互不相关的性质,在线自适应地调整渐消因子,对未知干扰有较强的鲁棒性。建立行进间对准的状态方程与观测方程,针对三种不同路况进行了8次跑车行进间对准试验。试验结果表明:强跟踪滤波能适应恶劣复杂路况;精对准后航向误差(1?)≤3.6′,满足指标要求。

A new odometer-aided in-motion alignment algorithm based on strong tracking filter（STF） is proposed for vehicles driving in complicated environment. The STF with multiple fading factors is used in the fine alignment stage based on the property that the sequences of residuals are mutually uncorrelated when Kalman filter gain is optimal. The algorithm can adjust multiple fading factors adaptively, so it is robust to unknown external disturbances. The state equations and observation equations of in-motion alignment algorithm is established, and eight groups of ground-based navigation experiments are carried out in three different road conditions. The results show that this method is effective in complicated environment, and the estimated accuracy of heading error angle is less than 3.6′（1？）, which satisfy the requirements of the in-motion alignment.