粒子群优化算法在多基站时差定位中的应用  

Application of PSO in TDOA Based Multi-Station Location

作　　者：成伟明[1] 王寿峰[1] 赵春光[1] 

机构地区：[1]中国电子科技集团公司第二十八研究所,南京210007

出　　处：《指挥信息系统与技术》2010年第3期66-69,共4页Command Information System and Technology

摘　　要：提出利用粒子群算法求解时差定位系统解算方程的非线性最优化问题。设计一种动态群体的粒子群优化算法,使得种群的多样性得到保证,减少局部收敛的可能,同时又不会对已有种群的模式造成巨大破坏。对比实验表明该方法性能稳定,能找到逼近全局最优点的解。A particle swarm optimization （PSO） algorithm is proposed for the nonlinear optimization in time differences of arrival （TDOA） based location. A dynamic PSO algorithm is designed instead of traditional PSO to ensure the diversity of the particle swam, decrease the possibility of local convergence and not to destroy the pattern of the particle swarm. Comparison with the existing methods shows the algorithm is stable and can find the coordinates approaching the global optimal point.

关 键 词：粒子群 时差定位 局部收敛 

分 类 号：TN929.53[电子电信—通信与信息系统]