改进的强跟踪平方根分解UKF算法应用研究
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摘要
针对一类非线性系统滤波问题,提出了一种改进的强跟踪平方根分解UKF算法.该算法通过引入自适应渐消因子改善了滤波器的鲁棒性,利用改善的平方根分解方法提高了滤波器的计算效率.通过实验仿真验证,该算法相对于传统的强跟踪UKF算法具有相近的估计精度和更快的计算效率,相对于强跟踪滤波器具有更高的精度.
In this paper,for a class of nonlinear system filtering problem,a improved strong tracking square-rootunscented kalman filtering(ISTSRUKF)algorithm is proposed. The robustness of the filter is improved by introducingadaptive fading factor and the computation efficiency of the filter is better than traditional square-root unscentedkalman filter(UKF)by using modified decomposition method. The simulation results show that the algorithm has asimilar estimation accuracy and faster computational efficiency with respect to the traditional strong tracking UKFalgorithm and a higher accuracy relative to the strong tracking filter.
In this paper,for a class of nonlinear system filtering problem,a improved strong tracking square-rootunscented kalman filtering(ISTSRUKF)algorithm is proposed. The robustness of the filter is improved by introducingadaptive fading factor and the computation efficiency of the filter is better than traditional square-root unscentedkalman filter(UKF)by using modified decomposition method. The simulation results show that the algorithm has asimilar estimation accuracy and faster computational efficiency with respect to the traditional strong tracking UKFalgorithm and a higher accuracy relative to the strong tracking filter.
引文
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[7]周东华,席裕庚,张钟俊.非线性系统次优渐消因子的扩展卡尔曼滤波[J].控制与决策,2010,5(5):1-6.
[2]Joseph J,La Viola Jr.A comparison of unscented and extended kalman filtering for estimating quaternion motion[C]//Proceedings of the 2011 American Control Conference,San Francisco,CA,US:IEEE Press,2011.
[3]Julier S J,Uhlamnn J K,Durrant-Whyte H F.A new method for the nonlinear transformation of means and covariances in fiters and estimators[J].IEEE Transactions on Automatic Control,2010,45(3):477-482.
[4]Shou Honien,Lin Chentsung,Chang Chungliang,et al.Attitude angle rate estimation unscented kalman fiter approach[C]//Proceeding SCIE Annual conference 2010,Taipei,Taiwan:Information and Computer Press,2010.
[5]陈阳舟,孙章固,马海波.基于平方根UKF的车辆组合导航[J].系统工程与电子技术,2012,30(5):926-929.
[6]范利涛,郑伟,汤国建.基于平方根UKF滤波的轨道机动飞行器自主导航方法[J].中国惯性技术学报,2011,16(6):667-675.
[7]周东华,席裕庚,张钟俊.非线性系统次优渐消因子的扩展卡尔曼滤波[J].控制与决策,2010,5(5):1-6.