相控阵雷达目标搜索的MAB模型策略

针对相控阵雷达波束指向的问题,研究相控阵雷达搜索状态下的波束指向控制策略,目的在于提升其目标发现概率以及发现效率。将相控阵雷达面临的搜索问题看作为一类多臂赌博机问题,进而在上限置信度指数方法的基础上对该问题进行求解,同时与贪婪算法等其他方法进行对比。仿真结果表明,所得到的雷达波束搜索策略使得雷达发现目标所用时间一般不超过扫描一次负责空域所用时间的两倍。在相同搜索时间内,雷达对弱小目标发现概率提升至少20%。并且该方法算法复杂度相对较低,具备实际应用能力。

A MAB Mode Strategy in AESA Radar Target Searching

The problem of phased array radar beam pointing is aimed at in this paper. The beam pointing control strategy of phased array radar search state is studied to improve its target discovery probability and discovery efficiency. The purpose is to improve its target discovery probability and discovery efficiency. The search problem faced by phased array radar is regarded as a type of multi-arm gaming machine (MAB) problem, and then the problem is solved based on the upper bound confidence (UCB) index method. At the same time, the algorithm is compared with other methods such as greedy algorithm. The simulation results show that the obtained radar beam search strategy makes the time taken by the radar to find the target generally less than twice the time taken to scan the responsible airspace. In the same search time, the radar increases the probability of finding weak targets by at least 50%.