基于改进迭代扩展卡尔曼滤波的3星时频差测向融合动目标跟踪方法

针对传统3星时频差定位系统在未知高程情况下，对运动辐射源会产生由目标速度引发的定位误差的问题，该文提出一种利用主星的干涉仪测向信息的改进迭代扩展卡尔曼滤波(IEKF)，结合3星时差、频差信息的无源融合动目标跟踪新方法。首先，在坐标系转换的基础上建立了定位模型，并在此基础上利用改进的迭代扩展卡尔曼滤波算法对未知高程的运动目标进行跟踪。仿真结果表明，该方法无需获知目标的高程信息即可实现对运动辐射源的定位、跟踪和测速，且对目标的位置、速度估计性能有较大的提高。

Tracking Method of Moving Target for Three-satellite TDOA/FDOA/DOA System Based on Improved IEKF Algorithm

In case of the traditional three-satellite time-frequency difference positioning system with unknown elevation, it will produce positioning errors caused by the target speed to the moving state radiation source. A new method of fusion passive tracking is proposed, which uses the Direction Of Arrival (DOA) information of the main star and combines the Time Difference Of Arrival (TDOA) and Frequency Difference Of Arrival (FDOA) information of the three satellites. First, a positioning model is established on the basis of coordinate system transformation, and on this basis, an improved Iterative Extended Kalman Filter (IEKF) algorithm is used to track moving objects of unknown elevation. The simulation results of the algorithm show that this method can realize the positioning, tracking and speed measurement of the moving radiation source without knowing the height information of the target, and the position and speed estimation of the target are improved.