华中科技大学学报：自然科学版2012，Vol.40Issue(9)：52-56,5.
基于AR模型的非线性目标跟踪自适应算法
Adaptive algorithm of nonlinear target tracking based on AR model
摘要
Abstract
Due to the influence of setting up the unreasonable parameters about Jerk model,an improved adaptive algorithm of parameters based on auto regressive(AR) model was proposed in this paper.The model parameters were estimated online and then the target tracking system was amended.The accuracy and stability could be enhanced effectively.Meanwhile,in order to deal with the problems of extended Kalman filter(EKF) that it was complexly computed with low accuracy in state estimation,an improved filter square-root cubature Kalman filter(SRCKF) was present,which enhanced the algorithm numerical stability,guaranteed positive semi-definiteness of the state covariance,and also increased the filtering accuracy,providing a fitness advantage for Jerk parameters adaptation.At last,simulation results verified the effective of this algorithm.关键词
机动目标跟踪/非线性滤波/自回归（AR）模型/Jerk模型/平方根容积卡尔曼滤波器（SRCKF）/自适应算法Key words
maneuvering target tracking/nonlinear filter/auto regressive(AR) model/Jerk model/square-root cubature Kalman filter(SRCKF)/adaptive algorithm分类
信息技术与安全科学引用本文复制引用
钱华明,陈亮,杨峻巍..基于AR模型的非线性目标跟踪自适应算法[J].华中科技大学学报：自然科学版,2012,40(9):52-56,5.基金项目
国家自然科学基金资助项目 （）
