Sparse array optimization strategy for MIMO radar based on improved Harris Hanks Optimization
To address the sparse array optimization problem of MIMO radar,an improved Harris Eagle algo-rithm for MIMO radar array graph optimization strategy is proposed.Firstly,the local search ability of Har-ris Eagle algorithm is improved by integrating the barycentric neighborhood search and state transition opera-tor,and the horntail search strategy is added in the iteration process,so that the algorithm always maintains a high population diversity in the iteration process,and improves the convergence accuracy and convergence speed of the algorithm.Secondly,taking the minimum sidelobe peak value of equivalent virtual transmitting and receiving beam as the objective function,the improved eagle swarm algorithm can be optimized.Final-ly,the experimental results are compared with those of other optimization strategies.The proposed algorithm has a smaller sidelobe peak value,which improves the recognition ability and performance of MIMO radar.
MIMO radarSparse ArrayHarris HawkCenter of gravity neighborhoodState transition op-erator
NETL
NSTL
万方数据
