Research On Control Method Of Airborne Distributed MIMO Radar Node Resource And Path

The airborne distributed multiple input multiple output(MIMO)radar system is based on a distributed platform.It uses multiple radar nodes to simultaneously transmit and receive signals,and collaboratively process multiple radar echoes to improve the signal-to-noise ratio,thereby improving the monitoring performance of the radar system for the observation area.System resource management and control can significantly improve the utilization of resources such as node locations and flight paths,and enhance target detection capabilities.It is one of the key technologies of airborne distributed MIMO radar systems and has become a research hotspot in the field of radar at home and abroad.This thesis conducts research on control method of airborne distributed MIMO radar node resource and path.The main work is as follows:1.Aiming at the regional surveillance mission,the airborne distributed MIMO radar cooperative detection power model is introduced,the definition and numerical calculation method of the effective surveillance rate are given,and the performance index of flight path optimization and flight motion constraints are expounded.The distributed MIMO radar node resource optimization model and path planning model are established,which lays the foundation for the research on control method of airborne distributed MIMO radar node resource and path.2.A step-by-step optimization control method for node resource and path of airborne distributed MIMO radar is studied.First,the particle swarm optimization(PSO)is used to optimize the location resources of the airborne distributed MIMO radar nodes to obtain the optimal location of each radar node.Then,according to the different requirements of path planning,three different node matching criteria are designed,namely,the shortest track sum,the shortest longest track,and the smallest track residual.Finally,the path planning optimization model is established with the next frame track position of the fleet as a parameter,and the genetic algorithm(GA)is used to solve frame by frame to obtain the final optimal path.3.A joint optimization control method of node resource and path of airborne distributed MIMO radar is studied.Firstly,in order to jointly optimize the radar area monitoring performance and flight path performance,the multi-objective optimization problem is introduced,and the related concepts of multi-objective optimization are introduced.Secondly,aiming at joint optimization of node position and path in straightline flight,an optimization control algorithm based on multi-objective particle swarm optimization using relative crowding distance(MOPSO-RCD)was used to optimize the solution.Finally,a multi-aircraft cooperative path optimization algorithm based on the third-generation non-dominated sorting genetic algorithm(NSGA-III)was studied in non-linear flight to improve flight path complexity and regional monitoring performance of intermediate track points.The above algorithms are verified by simulation experiment,which proves the feasibility and effectiveness of the algorithm.