摘要
通过对滤波状态协方差估计的修改,将水下纯方位被动目标运动分析中的扩展卡尔曼滤波(EKF)算法改进为修正增益扩展卡尔曼滤波(MGEKF)算法,并指出了两者的联系与区别。对比仿真分析表明,MGEKF较之EKF滤波效果有所改善,增强了稳定性,提高了精度,为水下纯方位被动目标运动分析的实现提供新的途径。
The algorithm of underwater bearings-only passive target motion analysis （TMA） is improved from extended Kalman filter （EKF） to modified gain EKF （MGEKF） by modifying the covarianee estimation of filter state. The differences and relationship of these two algorithms are also denoted. Simulation results demonstrate that the MGEKF has better performance than the EKF both in stability and precision. Thus it supplies a new method for the realization of underwater bearings-only passive TMA.
出处
《电光与控制》
北大核心
2006年第1期5-7,共3页
Electronics Optics & Control
基金
预研项目413040201
