量子进化算法在水下目标DOA估计中的应用

Application of quantum-inspired evolutionary algorithm for DOA estimation of underwater target

高分辨DOA估计算法的空间谱搜索运算量大、耗时长,利用量子进化算法（QEA）的并行加速特性对其进行优化,是满足应用实时性的有效途径。利用模拟退火原则对传统QEA的旋转角取值策略进行了改进,并在比较DOA估计的信号相位匹配（SPM）算法、MUSIC算法和CBF算法的计算复杂度的基础上,提出了一种基于改进QEA（MQEA）的水下目标SPM定向算法。仿真实验和湖试数据实验结果表明,所提算法测向精度虽稍有下降,但大幅缩短了计算耗时,提高了DOA估计的实时性。

QEA is an effective approach,for the real-time applications,to reduce the computational load of the high-resolution DOA estimation algorithms. Improved the selection strategy of angle of rotation in QEA by the simulated annealing principle. Comparing the computational complexity among SPM,MUSIC and CBF and then,proposed a DOA estimation algorithm of underwater target based on the modified QEA （ MQEA） and SPM. The simulated experiments and lake test data experiments all show that the run-time is shorten by the proposed method significantly,while the precision of direction finding decrease in small,improving the real-time performance of DOA estimation.