低轨卫星多目标无源定位到达时差分选方法

Arrival time difference sorting method for multi-target passive positioning oflow earth orbit

低地球轨道(Low Earth Orbit,LEO)卫星无源定位场景中不同目标辐射源之间相互干扰、时频混叠,不同目标的到达时差(Time Difference Of Arrival,TDOA)参数混杂难以区分,较难实现精准目标定位。基于网格密度聚类算法(Clustering Algorithm based on Grid Density,CAGD)的基本原理,并利用TDOA参数的多复杂特征,构建多目标TDOA参数分选模型,实现TDOA定位参数分选。模型通过定义网格密度波谷,解决了定位目标间数据被聚为一类的问题,同时引入位置相连原则实现最佳类簇合并,最终实现定位参数分选。仿真结果表明,相较于传统网格及密度聚类方法,本方法对LEO卫星无源定位场景下的多目标TDOA参数分选表现更好。

In passive positioning scenarios of Low Earth Orbit(LEO)satellites,different target radiation sources interfere with each other,and the Time Difference of Arrival(TDOA)parameters of different targets are mixed and difficult to distinguish,so it is difficult to achieve accurate target positioning.In this paper,based on the basic principle of Clustering Algorithm based on Grid Density(CAGD)and the multi-complex characteristics of TDOA parameters,a multi-objective TDOA parameter sorting model is constructed to achieve TDOA parameter sorting.By defining the grid density trough,the model solves the problem that the data among localization targets are clustered into one class,and introduces the principle of position connection to realize the best clustering,and finally realizes the sorting of localization parameters.The simulation results show that compared with the traditional grid and density clustering methods,the proposed method performs better in the multi-target TDOA parameter sorting in the scenario of LEO satellite passive positioning.