雷达学报Issue(2)：257-264,8.DOI:10.3724/SP.J.1300.2013.13003
机动目标跟踪中一种机动频率和方差自适应滤波算法
One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking
摘要
Abstract
The approach of tracking maneuvering targets based on the“Current”Statistical (CS) model is widely used. The method needs to preset the maneuvering frequency and the maximum acceleration based on experience. In practice, the preset values are often not consistent with the actual moving state of targets and result in larger tracking errors. To tackle the problem, we initially deduce a self-adapting maneuvering frequency algorithm from the discrete-state equation of the CS model. Then, an improved self-adapting acceleration covariance algorithm is presented. Simulation results show that, by using the self-adapting maneuvering frequency algorithm and the improved self-adapting acceleration covariance algorithm to track targets simultaneously, we can improve the ability to self-adapt to the fluctuation of the moving state. The tracking accuracy is also improved, and the convergence speed of the algorithm is relatively quick.关键词
机动目标跟踪/“当前”统计模型/机动频率自适应/方差自适应Key words
Maneuvering target tracking/“Current” Statistical (CS) model/Maneuvering frequency adaptive/Acceleration variance adaptive分类
信息技术与安全科学引用本文复制引用
钱广华,李颖,骆荣剑..机动目标跟踪中一种机动频率和方差自适应滤波算法[J].雷达学报,2013,(2):257-264,8.基金项目
国家自然科学基金(61272043)和重庆市自然科学基金重点项目(CSTC2011BA2016)资助课题 （61272043）
