摘要
针对红外搜索跟踪(infrared search and track,IRST)系统单站情况下的弱可观测强非线性问题,提出了一种基于修正迭代扩展卡尔曼滤波(modified iterated extended Kalman filter,MIEKF)的多站融合跟踪算法。按照高斯-牛顿迭代方法对IEKF中的测量更新进行修正,并推导了最大似然迭代终止条件,减小了非线性滤波的线性化误差。结合集中式融合跟踪算法,应用于IRST系统多站目标跟踪。以三站为例进行仿真研究,结果表明所提算法的跟踪性能要优于EKF和UKF。
Aiming at the weakly observability and highly nonlinearity of a single observer of infrared search and track（IRST） systems,a multi-observer fusion tracking algorithm based on modified iterated extended Kalman filter（MIEKF） is proposed.The IEKF is modified by providing a new measurement update with Gauss-Newton iteration algorithm,then an iterative termination condition is deduced based on a maximum likelihood criterion,thus the linearity error is reduced.Finally the MIEKF combining with the central fusion tracking algorithm is applied to multi-observer target tracking of IRST.Simulation results show that the proposed algorithm is better than EKF and UKF for a three-observer target tracking system.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2010年第3期504-507,共4页
Systems Engineering and Electronics
基金
国家自然科学基金(60871074)资助课题
