控制理论与应用2011，Vol.28Issue(12)：1723-1728,6.
基于改进“当前”统计模型的非线性机动目标跟踪算法
A nonlinear maneuver-tracking algorithm based on modified current statistical model
摘要
Abstract
The ‘current’statistical model depends on both the marginal value of the target acceleration and the fre-quency of the maneuver;this leads to a poor performance in tracking targets of low maneuverability or higher maneuver-ability.To obtain an improved model,we introduce to the existing ‘current’statistical（CS） model an activate function with the trace of the residual error variance as parameter for modifying the error covariance between the acceleration and the frequency.This modified model is then combined with an unscented Kalman filter（UKF） to form the modified current statistic model for the nonlinear maneuver tracking algorithm.Simulation results indicate that the proposed algorithms not only keep equal performance level as the CS model in tracking general maneuvers,but provide excellent performance in tracking targets with low maneuverability;thus,extending the range of maneuverability in tracking targets.关键词
机动目标跟踪/当前统计模型/活化函数/UKFKey words
maneuvering target tracking/＂current＂statistical model/activate function/unscented Kalman filter分类
信息技术与安全科学引用本文复制引用
黄伟平,徐毓,王杰..基于改进“当前”统计模型的非线性机动目标跟踪算法[J].控制理论与应用,2011,28(12):1723-1728,6.基金项目
国家地、县级海防管理监控中心资助项目 （）
