基于粒子滤波的机载单站无源跟踪算法

摘要

针对空中观测平台对远距离海面慢速运动目标定位跟踪这一非线性估计问题,介绍了专门处理非线性估计问题的粒子滤波算法,将粒子滤波算法（Particle Filter,PF）应用于机载单站无源定位跟踪问题,有效提高了对慢速运动目标的单站无源定位跟踪性能,解决了传统的扩展卡尔曼滤波算法在非线性估计时存在收敛速度慢的问题。通过与扩展卡尔曼滤波算法的仿真比较表明,粒子滤波算法可实现对慢速运动目标的高精度定位跟踪,且性能优于扩展卡尔曼滤波算法。%Locating remote slow sea-surface targets with airborne observation pla tform is a non-linear problem.Particle filter（PF） is a special method that de a ls with non-linear problem.Applying PF to airborne single-station passive tra ck ing can efficiently improve the tracking performance for slow sea-surface targe t s,and resolve the low speed problem based on the conventional extended Kalman f ilter（EKF） algorithm.Through the comparison with EKF,the PF can quickly reali ze slow target tracking,and has the performance advantage over EKF.