摘要
针对ESM传感器能够同时测量方位角与多普勒频率的特点,提出了基于MGEKF的ESM多普勒频率/方位角目标跟踪算法(DB-MGEKF)。与通常的纯方位角目标跟踪算法相比,DB-MGEKF算法增加了多普勒频率量测信息,并引入了能够较好处理系统非线性问题的修正增益扩展卡尔曼滤波器(MGEKF),从而提高了目标的估计精度及滤波的稳定性,同时避免了观测平台自身的机动。Monte-Carlo仿真及结果分析进一步说明了算法的有效性。
Aiming at the feature of Electronic Support Measures (ESM) detecting the bearings and Doppler frequencies simultaneously,a target tracking algorithms is proposed which uses ESM’s Doppler frequency and bearing measurements based on Modified Gain Extended Kalman Filter (DB-MGEKF). Compared with bearings-only target tracking algorithm,DB-MGEKF increases the Doppler frequencies measurement and introduces the MGEKF which can handle the nonlinear system preferably. The method improves the accuracy of target estimates as well as the stability of the filtering. Moreover, the observer’s maneuvering can be avoided. Monte-Carlo simulations with result analysis further illustrate the effectiveness of the algorithm.
出处
《光电工程》
CAS
CSCD
北大核心
2011年第3期9-13,共5页
Opto-Electronic Engineering
基金
国家自然科学基金项目资助(60434020
60602049)
关键词
ESM
目标运动分析
多普勒频率
目标跟踪
MGEKF
electronic support measures
target motion analysis
Doppler frequency
target tracking
modified gain extended Kalman filter