基于“当前”统计模型的容积卡尔曼滤波算法  

Cubature Kalman Filter Method Based on Current Statistical Model

作　　者：张彪 薛俊杰 杨自豪 王涛 徐光辉 ZHANG Biao;XUE Junjie;YANG Zihao;WANG Tao;XU Guanghui(Shanghai Aerospace Electronics Technology Research Institute,Shanghai 201109,China)

机构地区：[1]上海航天电子技术研究所,上海201109

出　　处：《现代雷达》2022年第2期9-15,共7页Modern Radar

摘　　要：由于雷达探测目标是在极坐标系下进行的,因此在直角坐标系下建立雷达跟踪系统的状态方程和观测方程时,观测方程是非线性的,基于"当前"统计模型的机动目标跟踪不能直接通过标准卡尔曼滤波实现。文中在"当前"统计模型基础上,提出用容积卡尔曼滤波来实现非线性滤波,并将其与扩展卡尔曼滤波进行比较。通过对一个三维空间中机动目标跟踪的仿真,表明该算法能稳定跟踪目标,且跟踪精度高。For the radar detects the target in polar coordinate system,the observation equation is nonlinear when the state equation and observation equation of radar tracking system are established in Cartesian coordinate system.The maneuvering target tracking based on the current statistical model cannot be realized directly by standard Kalman filter.In this paper the cubature Kalman filter based on current statistical model is proposed to realize nonlinear filtering,and compared with extended Kalman filter.The simulation of the tracking of a maneuvering target in a three-dimensional space shows that the algorithm can track the target stably with high tracking accuracy.

关 键 词：“当前”统计模型 容积卡尔曼滤波 扩展卡尔曼滤波 机动目标跟踪 

分 类 号：TN958[电子电信—信号与信息处理]