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Alternative TitleBearings Only Target Motion Analysis Based on Strong Tracking Square-Root Cubature Kalman Filter
王艳艳; 刘开周; 封锡盛
Source Publication计算机测量与控制
Contribution Rank1
Funding Organization国家自然科学基金面上项目(61273334) ; 中国科学院科研装备研制项目(YZ201441) ; 中国大洋矿产资源研究开发协会前沿课题(DY125-22-QY-24)
KeywordAuv 纯方位目标跟踪 非线性系统 平方根容积卡尔曼滤波 强跟踪滤波
Abstract针对纯方位目标跟踪系统中模型状态简化、系统噪声统计特性未知、目标初始距离信息不准确导致的滤波收敛时间长和滤波精度不高的问题,以自主水下机器人(autonomous underwater vehicle,AUV)跟踪水下动态目标为例,提出了一种基于强跟踪平方根容积卡尔曼滤波器(strong tracking square root cubature kalman filter,STFSRCKF)的纯方位目标运动分析算法;该算法在滤波过程中,利用平方根容积卡尔曼滤波器(square root cubature kalman filter,SRCKF)完成预测更新,对于SRCKF中的每个容积点采用强...
Other AbstractIn order to solve the problems of target motion analysis convergence time too long and low accuracy for AUV bearings-only target tracking by model simplification, unknown noise statistical properties and target initial distance information inaccurate, an improved Strong Tracking Square Root Cubature Kalman Filter bearings only target motion analysis method is proposed. With the STFSRCKF algorithm, the equation of state is predicted and updated with SRCKF, each cubature point of SRCKF is updated by strong tracking filter(STF), the effects of noises on system state estimation are suppressed by optimizing filter gains, and the system state estimation converges to real values quickly. At last, several algorithms such as EKF,UKF,SRCKF and STFSRCKF under different initial condition and noise environment were compared in numerical simulation experiments. The experimental results show that the proposed strong tracking SRCKF filter has better performance on robustness and convergence.
Document Type期刊论文
Corresponding Author王艳艳
Recommended Citation
GB/T 7714
王艳艳,刘开周,封锡盛. 基于强跟踪平方根容积卡尔曼滤波的纯方位目标运动分析方法[J]. 计算机测量与控制,2016,24(11):136-140.
APA 王艳艳,刘开周,&封锡盛.(2016).基于强跟踪平方根容积卡尔曼滤波的纯方位目标运动分析方法.计算机测量与控制,24(11),136-140.
MLA 王艳艳,et al."基于强跟踪平方根容积卡尔曼滤波的纯方位目标运动分析方法".计算机测量与控制 24.11(2016):136-140.
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