一种改进的强跟踪UKF算法及其在SINS大方位失准角初始对准中的应用
收稿日期: 2013-03-26
修回日期: 2013-06-04
网络出版日期: 2013-06-17
基金资助
国家自然科学基金（61153002）
An Improved Strong Tracking UKF Algorithm and Its Application in SINS Initial Alignment Under Large Azimuth Misalignment Angles
Received date: 2013-03-26
Revised date: 2013-06-04
Online published: 2013-06-17
Supported by
National Natural Science Foundation of China (61153002)
郭泽 , 缪玲娟 , 赵洪松 . 一种改进的强跟踪UKF算法及其在SINS大方位失准角初始对准中的应用[J]. 航空学报, 2014 , 35(1) : 203 -214 . DOI: 10.7527/S1000-6893.2013.0296
Against the lack of theoretical basis and poor filtering performance of the existing strong tracking unscented Kalman filter (UKF) algorithms, the sufficient condition of a strong tracking UKF is rigorously derived in this paper from the orthogonality principle, based on which an improved strong tracking UKF algorithm is proposed. This new algorithm requires less computation than the existing strong tracking UKF since it does not have to calculate the Jacobian matrix, and it is different from the original strong tracking filter in both the position and solution of the fading factor. This study presents the algorithm flow and the solution to the fading factor, and proves that the improved algorithm satisfies the sufficient condition of strong tracking UKF. Furthermore, the action mechanism of the fading factor is analyzed. The results of the strapdown inertial navigation system (SINS) initial alignment simulation under large azimuth misalignment angles verify the validity and effectiveness of the improved strong tracking UKF algorithm.
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