空军工程大学;西安机电信息研究所;
针对目标跟踪中非线性滤波精度下降甚至发散的问题,提出了一种时变噪声统计估计的自适应无迹卡尔曼滤波(Unscented Kalman Filtering,UKF)算法。首先将系统模型和滤波算法修正为适于噪声非零均值时的情况,然后根据极大后验估计原理,推导出一种次优的时变噪声统计估计器,其系数通过指数加权的衰减因子计算得到,最后与传统UKF算法结合形成自适应的滤波算法。仿真结果表明,该算法保证了滤波收敛性,能够对目标进行有效跟踪,而且滤波精度显著提高。
253 | 6 | 6 |
下载次数 | 被引频次 | 阅读次数 |
[1]韩崇昭,朱洪艳,段战胜.多源信息融合[M].北京:清华大学出版社,2006:124-188.HAN Chong-zhao,ZHU Hong-yan,DUAN Zhan-sheng.Multi-source information fusion[M].Beijing:Tsinghua University Press,2006:124-188.(in Chi-nese)
[2]EINICKE G A,WHITE L B.Robust extended Kalmanfiltering[J].IEEE Transactions on Signal Processing,1999,47(9):2596-2599.
[3]秦永元,张洪钺,汪叔华.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,1998:182-188.QIN Yong-yuan,ZHANG Hong-yue,WANG Shu-hua.Kalman filtering and integrated navigation theory[M].Xi’an:Northwestern Polytechnical UniversityPress,1998:182-188.(in Chinese)
[4]JOSEPH J,LAVIOLA Jr.A comparison of unscentedand extended Kalman filtering for estimating quaternionmotion[C]//Proceedings of the American Control Con-ference.Denver:[s.n.],2003:2435-2440.
[5]JULIER S J.The scaled unscented transformation[C]//Proceedings of the American Control Confer-ence.Anchorage:[s.n.],2002:4555-4559.
[6]JULIER S J,UHLMANN J K.Unscented filtering andnonlinear estimation[J].Proceedings of the IEEE,2004,92(3):401-422.
[7]WAN E A,VAN DER MERVE R.The unscentedKalman filter for nonlinear estimation[C]//Proceed-ings of the IEEE Adaptive Systems for Signal Process-ing,Communication and Control Symposium.LakeLouise:[s.n.],2000:153-158.
[8]杨凯,倪龙强,张丽华,等.基于IMM-UKF的非线性机动目标跟踪仿真研究[J].火炮发射与控制学报,2010(3):12-16.YAN Kai,NI Long-qiang,ZHANG Li-hua,et al.Study on tracking simulation of nonlinear maneuveringtarget based on IMM-UKF[J].Journal of Gun Launch&Control,2010(3):12-16.(in Chinese)
[9]江宝安,万群.基于UKF-IMM的双红外机动目标跟踪算法[J].系统工程与电子技术,2008,30(8):1454-1459.JIANG Bao-an,WAN Qun.Maneuvering target pas-sive tracking with dual infrared observers using IMMalgorithm based on UKF[J].Systems Engineering andElectronics,2008,30(8):1454-1459.(in Chinese)
[10]张文玲,朱明清,陈宗海.基于强跟踪UKF的自适应SLAM算法[J].机器人,2010,32(2):190-195.ZHANG Wen-ling,ZHU Ming-qing,CHEN Zong-hai.An adaptive SLAM algorithm based on strongtracking UKF[J].Robot,2010,32(2):190-195.(inChinese)
[11]SAGE A P,HUSA G W.Adaptive filtering with un-known prior statistics[C].Tokyo:Proceedings of theJoint Automatic Control Conference,1969,760-769.
[12]石勇,韩崇昭.自适应UKF算法在目标跟踪中的应用[J].自动化学报,2011,37(6):755-759.SHI Yong,HAN Chong-zhao.Adaptive UKF methodwith applications to target tracking[J].Acta Auto-matica Sinica,2011,37(6):755-759.(in Chinese)
[13]孙尧,张强,万磊.基于自适应UKF算法的小型水下机器人导航系统[J].自动化学报,2011,37(3):342-353.SUN Yao,ZHANG Qiang,WAN Lei.Small autono-mous underwater vehicle navigation system based onadaptive UKF algorithm[J].Acta Automatica Sinica,2011,37(3):342-353.(in Chinese)
[14]赵琳,王小旭,薛红香,等.带噪声统计估计器的Unscented卡尔曼滤波器设计[J].控制与决策,2009,24(10):1483-1488.ZHAO Lin,WANG Xiao-xu,XUE Hong-xiang,etal.Design of unscented Kalman filter with noise sta-tistic estimator[J].Control and Decision,2009,24(10):1483-1488.(in Chinese)
基本信息:
DOI:10.19323/j.issn.1673-6524.2013.01.013
中图分类号:TJ011.1
引用信息:
[1]蔡佳,黄长强,李美亚等.时变噪声统计估计的自适应UKF目标跟踪算法[J].火炮发射与控制学报,2013,No.129(01):51-55.DOI:10.19323/j.issn.1673-6524.2013.01.013.
基金信息:
航空科学基金(20105196016)