采用粒子群算法的空时二维参数估计  

Application of particle swarm optimization to space-time two-dimensional parameter estimation

作　　者：邱新建[1,2] 山拜.达拉拜 薛凤凤[3] 

机构地区：[1]新疆大学信息科学与工程学院 [2]中国人民解放军68203部队 [3]空军工程大学电讯工程学院

出　　处：《计算机应用》2012年第11期3054-3056,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目(60971130)

摘　　要：针对传统的空时二维参数估计计算复杂、鲁棒性及通用性差、收敛速度慢等缺点,根据空时具有等效性,以空域和时域处理算法可以相互转化为基础,推导出合适的适应度函数,运用改进的粒子群算法同时搜索信号的到达角和频率,用K-means聚类算法对搜索结果进行分类,利用粒子群算法计算简单、全局收敛、可并行性等特点提高算法的搜索能力。计算机仿真表明,与传统的方法相比该算法具有较好的统计和收敛性能。The traditional space-time two-dimensional parameter estimation has many shortcomings, such as high computational complexity, poor robustness and generalization, and slow convergence speed. According to the space-time equivalence and that the spatial and time domain processing algorithms can be transformed into each other, a suitable fitness function was derived, the improved particle swarm algorithm was used to search the arrival angle and frequency of signal, and the search results were classified with K-means clustering algorithm. Using particle swarm algorithm＇s feature, such as global convergence, parallelism, can improve the algorithm＇s searching capabilities. The computer simulation shows that the proposed method has better statistics and convergence performance than traditional methods.

关 键 词：空时二维参数估计 粒子群算法 谱估计 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]