摘要
针对多重信号分类(MUSIC)算法中二维常规网格化的搜索存在精度和时间不能兼顾的矛盾,而优化算法难以同时搜索多个谱峰。基于此,提出基于粒子群的网格化搜索算法,构建大网格进行谱峰粗位置搜索,然后基于粒子群算法在粗位置小邻域精细搜索的方法。仿真结果表明该算法能够在保证较高估计精度的前提下实现谱峰的快速搜索,在实时应用中具有一定的价值。
The two-dimensional conventional gridded search in the MUltiple SIgnal Classification(MUSIC)is hardly to balance the contradiction between precision and the time.And it is also difficult for the optimization algorithm to search multiple peaks at the same time.Based on this,the Grid searching based on Particle Swarm Optimization(GPSO)was proposed in this paper.Namely,a large grid was constructed to search for the coarse position of the spectrum peak,and then the small neighborhood in the coarse position was searched subtly by using the Particle Swarm Optimization.It can not only estimate the DOA quickly,but also achieve high accuracy of the estimations.The simulations results also show the valuable for the real-time applications.
作者
朱鹏
谢颖
谢聪
廖俭武
彭鑫
谢文武
欧先锋
ZHU Peng;XIE Ying;XIE Cong;LIAO Jianwu;PENG Xin;XIE Wenwu;OU Xianfeng(College of Information Science and Engineering,Hunan Institute of Science and Technology,Yueyang 414006,China;College of Physics and Electronic Engineering,Leshan Normal University, Leshan 614000,China)
出处
《成都工业学院学报》
2018年第4期14-18,共5页
Journal of Chengdu Technological University
基金
国家自然科学基金(61772195)
湖南省自然科学基金(2018JJ3210
2018JJ2154)
湖南省教育厅项目(17C0716)
湖南省科技计划项目(2016TP1021)
