基于扩展卡尔曼滤波的雷达无源定位方法

提出了基于扩展卡尔曼滤波的雷达无源定位技术。利用多无人机平台对雷达网进行航迹欺骗,需要对网内的雷达进行定位以达到精确欺骗干扰的目的。但飞行器在飞行过程量测噪声较高,传统的时差定位方法无法满足定位精度的要求。对于时差定位的非线性时变模型,提出了利用时变扩展卡尔曼滤波对雷达位置进行跟踪定位的方法。仿真结果显示,利用扩展卡尔滤波进行无源定位可以在高噪声背景下有较好的定位精度。

Passive Location of Radar Based on Extended Kalman Filter

In this paper,the method to locate the radar passively based on extended Kalman filter is proposed . When using cooperative autonomous vehicle teams to deceive radar network. we need to locate the position of radar in order to do deception jamming precisely. Due to the strong measurement noise as unmanned aerial vehicles flying,traditional TDOA technology cannot meet necessary precision. Because of the nonlinearized time-varying TDOA system. The time-varying extended Kalman filter model is presented to locate and follow the position of radar. The simulation result demonstrate that using extended Kalman filter model can improve the accuracy of location under the circumstances of strong measurement noise.