一种简化的强跟踪容积卡尔曼滤波算法  

A Simplified Strong Tracking Cubature Kalman Filtering Algorithm

作　　者：蔡宗平 张雪影 牛创 卫浩 CAI Zong-ping ZHANG Xue-ying NIU Chuang WEI Hao(Department of Automation, Rocket Force University of Engineering. Xi＇an 710025, China)

机构地区：[1]火箭军工程大学自动化系,西安710025

出　　处：《电光与控制》2017年第1期6-8,32,共4页Electronics Optics & Control

基　　金：国家自然科学基金(61174207)

摘　　要：针对强跟踪容积卡尔曼滤波(STCKF)算法因引入渐消因子而导致计算量增加、实时性变差的问题,提出一种简化的STCKF算法。通过证明STCKF算法的时间更新环节与KF算法的一步预测过程相一致,推导出简化的STCKF算法,并进行了算法复杂度分析。仿真结果表明,简化后的STCKF算法在保证滤波精度不变的情况下,有效提高了算法实时性。To deal with the problems of the increased calculation complexity and decreased real-time performance due to the introduction of the fading factor in Strong Tracking Cubature Kalman Filter （STCKF） algorithm, a simplified STCKF algorithm is proposed. By proving that the time update of STCKF algorithm is consistent with one-step prediction process of Kalman Filter （KF） algorithm, the simplified STCKF algorithm is derived and the complexity of the algorithm is analyzed. The simulation results show that the simplified STCKF algorithm can effectively improve the real-time performance of the algorithm while keeping the filtering accuracy.

关 键 词：目标跟踪 强跟踪 容积卡尔曼滤波 实时性 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]