在一定海空战场背景下,通过调整多机无源定位系统中各机位置布局可以有效地提高该系统对特定区域目标的定位精度。文中通过推导多机时差定位算法误差的GDOP公式,提出了利用粒子群算法寻找多机无源定位系统最优布站的方法。与传统典型布站相比较显著降低了对区域目标定位误差,明显提升了多机无源定位动态快速布站能力。同时利用粒子群算法对定位站数不同情况下进行仿真,得出了对应的最优布站形式。Under certain sea and air battlefield background,the positioning accuracy of the multi-machine passive position⁃ing system can be effectively improved by adjusting the position layout of each machine in the system.In this paper,the GDOP for⁃mula of the error of multi-machine time difference positioning algorithm is derived,and a method to find the optimal station of multi-machine passive positioning system using particle swarm optimization is proposed.Compared with the traditional typical posi⁃tioning station,the positioning error of regional target is significantly reduced,and the capability of multi-machine passive position⁃ing dynamic fast positioning station is significantly improved.At the same time,particle swarm optimization(pso)algorithm is used to simulate the situation that the number of stations is different,and the corresponding optimal layout of stations is obtained.
机构地区海军航空大学
出处《计算机与数字工程》 2021年第3期487-492,共6页Computer & Digital Engineering
基金国家自然科学基金项目“基于AdHoc无人飞行器组网测控通信链路研究”(编号:9140A24040714JB14387)资助。
关键词无源定位 粒子群算法 优化布站passive location particle swarm optimization optimization station
分类号TN958.97 [电子电信—信号与信息处理]
