多任务下分布式MIMO雷达有限阵元 快速选取

摘要

本文针对分布式MIMO雷达在目标检测和跟踪多任务下重点目标优先的阵元选取问题，提出了基于多任务下改进的贪婪多起点搜索的阵元选取模型及求解算法。将每个跟踪目标的位置估计误差界进行去量纲化、归一化处理，分别引入与目标重要程度和任务程度成正比的权重因子，以突出重点目标和调整系统资源在检测性能和跟踪性能两方面的配比，最后引入表征系统综合性能的参数。最小的阵元集合为代价函数，建立优化模型，通过遍历法寻找最优初始阵元集，逐次增加对系统贡献最大的阵元，完成阵元选择。仿真结果表明，所提算法能够在保证系统整体性能的同时降低系统计算量。 In this paper, the algorithm of model establishment of antenna selection and its solution based on modified greedy multi-start local search of multitask is proposed to solve the problem of antennas selection for distributed MIMO radar with priority for key targets under the multitask of target detection and tracking. The position estimation error bounds of each tracking target are non-dimensionalized and normalized. Weight factors that are proportional to the importance of the target and the task are introduced respectively to highlight the key targets and adjust the proportion of system resources in detection performance and tracking performance, and then the parameter that represents the comprehensive performance of the system is introduced. Taking the minimum set of antennas as the cost function, the optimization model is established. The optimal initial antennas set is found by exhaustive method, and the antenna that contributes the most to the system is added step by step to complete the antenna selection. The simulation results show that the proposed algorithm can guarantee the overall performance of the system and effectively reduce the system computation.