CAJ | 학술논문

为提高声纳浮标阵的目标搜索效率，文章首先建立目标运动模型和累积搜索概率的计算方法，然后提出了基于多点随机搜索、分区分支界定和遗传算法的浮标阵优化布放方法。仿真结果表明：这3种优化方法均优于传统布放方法，多点随机搜索算法性能最差但适合短时间制定布放策略；分区分支界定算法适合优化较少参数的浮标阵形，保证能找到最优点；对于较多的浮标阵形参数，利用遗传算法优化最好但运算时间较长。
위제고성납부표진적목표수색효솔，문장수선건립목표운동모형화루적수색개솔적계산방법，연후제출료기우다점수궤수색、분구분지계정화유전산법적부표진우화포방방법。방진결과표명：저3충우화방법균우우전통포방방법，다점수궤수색산법성능최차단괄합단시간제정포방책략；분구분지계정산법괄합우화교소삼수적부표진형，보증능조도최우점；대우교다적부표진형삼수，이용유전산법우화최호단운산시간교장。
It is important to optimize sonobuoys deployment for enhancing cumulative detection probability in aviation ASW. Firstly, the target motion model was established and method of calculation cumulative detection probability was interpreted. Then three kinds of global optimization algorithms were designed validly for sonobuoys deployment, based on multi-start random search, branch-and-bound based partition and a genetic algorithm. The simulation results showed that the multi-start random search algorithm was comparatively weak but fit for give deployment scheme in short time, branch-and-bound based partition algorithm could reach optimization but only fit few sonobouys array parameters, and GA was fit for sonobouys array with many parameters but need long time to calculate