Research On Optimization Method Of Radar Networking Resources Based On Positioning Performance

The main feature of radar networking is the collaborative work of radar nodes distributed in a wide area and the joint processing of data within the network.Radars in different positions can obtain different target information.By jointly processing this information,more information that cannot be obtained by a single radar can be obtained,so that the performance of the network in detection range,anti-stealth,and anti-jamming can be improved.The applicable scenarios are more extensive.The performance of radar networking is related to the way of resource allocation in the network.Reasonable and effective resource allocation can not only improve resource utilization,but also improve system performance,so it has become one of the important research directions in the radar field.This paper mainly studies the resource optimization configuration method of distributed radar network to improve the performance of the network in terms of positioning.The main work of the thesis is as follows:1.Research on the optimization of multi-station passive radar station deployment method based on positioning performance.First,through the positioning error covariance matrix in the passive time difference positioning method,the factors affecting the positioning accuracy when using this method are analyzed.Then,aiming at the radar node placement problem in the passive time difference positioning method,an improved Particle Swarm Optimization(PSO)algorithm combining linear inertial weights and disturbance terms is proposed.Finally,through simulation analysis,the improved PSO algorithm is explained.In the middle and late stages of the iteration,it has better local optimization capabilities than the standard PSO algorithm and the PSO algorithm using linear inertia weights,and can further improve the system positioning performance.2.Research on the optimization of the distributed multi-input multi-output(MIMO)radar target positioning problem.First,based on the distributed radar network,the Cramér-Rao Lower Bound(CRLB)of the target positioning error is derived,and it is used as the measurement standard of positioning performance,and then for the distributed MIMO in single target and multi-target scenarios For the optimization of radar nodes,a mathematical model is established with the objective function of minimizing the number of radar nodes and the positioning accuracy as the constraint.Finally,the problem is solved by using convex relaxation and weighting matrix.The results show that the optimized deployment of distributed MIMO radar based on positioning performance not only meets the positioning accuracy requirements of the target,but also minimizes the number of nodes in the radar network and reduces resource consumption.3.Research on the resource optimization allocation method of distributed MIMO radar target positioning.(1)Aiming at the problem of optimal allocation of distributed MIMO radar resources under a single target positioning task,two power allocation models of minimizing positioning error and minimizing the total power of the system are established and solved.The results show that compared with the average allocated power The obtained positioning error is optimized by using the power distribution algorithm to minimize the positioning error,which can effectively reduce the positioning error of the radar network and improve the positioning performance;when the positioning accuracy requirements of the system are known,the minimum total power is used The power allocation algorithm can effectively reduce the power usage of the network and save resources.(2)Aiming at the optimal allocation of distributed MIMO radar resources under multi-target positioning tasks,a joint power and bandwidth resource allocation model is established and solved.The results show that the joint power and bandwidth resource allocation method has better positioning performance than the single power resource allocation method and the average resource allocation method.