基于迭代重加权的子阵级MIMO雷达角度超分辨算法OA北大核心CSTPCD

A subarray-level MIMO radar transceiver signal and multi-subarray angular measurement model is constructed in this pa-per to address the problem of high directional map sidelobes caused by the limited number of apertures of subarray-level multiple-input multiple-output(MIMO)radar arrays.Angular super-resolution algorithms based on adaptive iterative reweighted(AIR)and iterative reweighted least squares with p-norm constraint(p-IRLS)are proposed and the computational complexity of the two algo-rithms is analyzed.The performance of the two algorithms is verified in simulation experiments,and their effects in single and dual-target,and interference environment detection are comparatively analyzed.The simulation results show that the AIR and p-IRLS al-gorithms are able to effectively reduce the level of directional map sidelobes in subarray-level MIMO radars,while realizing angular super-resolution of targets.Compared with the AIR algorithm,the p-IRLS algorithm is more prominent in low signal-to-noise ratio and neighboring target resolution performance.