Research Of Elastic Baseline Locating Algorithm Based On TDOA/FDOA Hybrid Measurement

With the development of UAV technology,the research on passive location and tracking of non cooperative targets using UAV cluster becomes more and more active.However,if the node distribution in passive location is not ideal,the optimal location accuracy can not be achieved.Aiming at the task requirement of UAV cluster using TDOA / FDOA hybrid measurement method to locate and track non cooperative targets,based on the evaluation standard of positioning accuracy based on the determinant of Fisher information matrix,this paper proposes the optimal configuration of node distribution in different scenarios.Then,the node selection strategy,UAV trajectory planning and node handover strategy of UAV cluster are designed,and these ideas are summarized,so as to put forward the concept of elastic baseline,and the elastic baseline positioning method which can use the flexible change of baseline to improve the positioning accuracy,and the process design based on the elastic baseline positioning algorithm is completed.This paper is divided into three parts1.Research on the optimal node configuration based on TDOA / FDOA hybrid measurement means positioning algorithm.In this paper,three kinds of UAV positioning scenes are proposed,which are unconstrained scene,near ground target scene and ground target scene.Based on the location model of TDOA / FDOA measurement means,the corresponding Fisher information matrix is derived.The optimal configuration of nodes in three scenarios,including location and speed,is studied by determinant mathematical properties and simulation.Then,it is pointed out that some of the optimal configurations are unsustainable and alternative schemes are given.2.UAV cluster node selection,mobile and handover strategy design.Aiming at the basic requirement of efficiently moving the own node to the optimal configuration,this paper designs the initial node selection method based on relative distance and speed for stationary target and moving target respectively,so that the initial node considering distance and dispersion can be selected;and then the specific target location calculation method which can be reached as soon as possible is designed.Next,the time first trajectory is designed for the longest node,and the energy first trajectory is designed for the other three nodes,so that the four nodes can arrive together as soon as possible,and the trajectory feasibility problem under the speed constraint is solved.Finally,in view of the power shortage of a node in the tracking process,a greedy handover node selection and handover trajectory are designed.3.The definition and design of UAV cluster 3D positioning and tracking algorithm based on the concept of elastic baseline.This paper summarizes the above ideas,puts forward the concept of elastic baseline and explains it,and completes the process design and Simulation of UAV positioning and tracking method based on elastic baseline.It shows that the elastic baseline positioning algorithm can use the flexible change of baseline to improve its positioning accuracy when dealing with static and dynamic targets.The simulation results show that the positioning accuracy of the elastic baseline positioning algorithm based on TDOA / FDOA hybrid measurement can be improved by moving the node to the optimal configuration.The root mean square error RMSE of the static and dynamic target scene before and after moving with the elastic baseline positioning algorithm is reduced from 2.77 M to 1.15 m on average,and the positioning accuracy is improved by 58.38%.