基于改进麻雀搜索算法的组网雷达功率控制

Power Control of Netted Radar Based on Improved Sparrow Search Algorithm

为了进一步优化目标跟踪模式下组网雷达系统的功率控制问题,提出一种使用改进麻雀搜索算法(improved sparrow search algorithm,ISSA)优化组网雷达辐射功率分配的方法。ISSA算法是基于鸟群算法迁徙行为中较强的搜索能力来增强麻雀算法觅食行为中较弱的搜索能力。并以施里海尔(Schleher)截获因子为目标,以反向散射信号和估计的目标响应之间互信息(mutual information,MI)的最小值和组网雷达系统总接收信噪比(signal-to-noise ration,SNR)为约束,建立组网雷达功率优化模型并使用ISSA求解。最后将ISSA算法、麻雀搜索算法(sparrow search algorithm,SSA)和非线性规划遗传算法(nonlinear programming based on genetic algorithm,NPGA)等应用于组网雷达功率分配模型中。仿真结果表明,使用ISSA算法的最大辐射功率比NPGA降低了7.05%,平均截获因子降低了8.19%,平均单次运行时间降低了53.75%,ISSA算法能更好地优化组网雷达功率控制问题。

In order to further optimize the power control problem of the networked radar system in the target tracking mode,a method of using the improved sparrow search algorithm(ISSA)to solve the radiated power distribution of the networked radar is proposed.ISSA is based on the stronger search ability in the migratory behavior of the bird swarm algorithm to enhance the weak search ability in the foraging behavior of the sparrow algorithm.With Schleher interception factor as the target,and the minimum value of mutual information(MI)between the backscatter signal and the estimated target response and the total received signal-to-noise ratio(SNR)as the constraint,the power optimization model of the networked radar is established and solved by ISSA.Finally,ISSA,sparrow search algorithm(SSA)and nonlinear programming based on genetic algorithm(NPGA)are applied to the networked radar power allocation model.The simulation shows that the maximum radiated power of ISSA is reduced by 7.05%compared with NPGA,the average intercept factor is reduced by 8.19%,and the average single run time is reduced by 53.75%.ISSA can better optimize the networked radar power control problem.