摘要
针对雷达系统的非线性目标跟踪存在精度低、滤波易发散等问题,提出一种新的非线性滤波算法——随机球面径向积分滤波算法(SSIF)。该滤波算法基于随机积分准则,利用随机球面积分准则和随机径向积分准则来近似函数积分。所提的滤波算法和传统的非线性滤波算法,例如扩展卡尔曼滤波、不敏卡尔曼滤波和容积卡尔曼滤波等相比在计算复杂度相当的情况下,不仅可以消除系统误差具有更高的跟踪精度,而且可以防止滤波发散提高滤波稳定度。通过蒙特卡洛仿真实验表明,所提出的非线性滤波算法整体性能明显优于传统的滤波算法。
To solve the problem of low filter accuracy and easy getting divergence during target tracking in nonlinear system,a new nonlinear filter algorithm—stochastic spherical radial integration filter（SSIF）is proposed.The method uses stochastic radial rules and stochastic spherical integration rules to approximate the integral.Comparing with the traditional nonlinear filter,such as EKF,UKF and CKF,the new nonlinear filter can not only eliminate the systematic error with higher tracking accuracy,but also improve the stability of the filter,with the similar computational complexity.The Mont Carlo simulation shows that the method outperforms the traditional algorithms.
出处
《雷达科学与技术》
北大核心
2015年第2期139-144,共6页
Radar Science and Technology
基金
国家自然科学基金(No.61301266
61178068
61201276)
中国中央大学基本研究基金(No.ZYGX2012Z001)
新世纪优秀人才支持计划(No.A1098524023901001063)
关键词
非线性滤波
状态估计
数值积分
目标跟踪
nonlinear filter
state estimation
numerical integration
target tracking
