摘要
针对用传统解算方法求解非线性测距定位方程时,其解算结果不稳定及可靠性低的问题,利用粒子群算法对测距定位方程进行求解。模拟和实测算例的结果表明,粒子群算法相较于传统解算方法能够准确、高效地搜索到多个全局最优候选解,对进一步结合实际或引入约束条件,最终获取唯一解具有一定的应用价值。
In view of the instability and low reliability of the traditional method to solve the nonlinear distance equation,the particle swarm optimization(PSO)algorithm is used to solve the distcace equation.The performance of particle swarm optimization is verified by simulation and practical examples.The results show that PSO can search multiple candidate solutions accurately and efficiently compared with the traditional method.It has a certain practical value for further combining the actual situation or introducing constraints to obtain the final solution of the problem.
作者
杨文龙
薛树强
曲国庆
王薪普
王冠宇
YANG Wenlong;XUE Shuqiang;QU Guoqing;WANG Xinpu;WANG Guanyu(Shandong University of Technology,Zibo,Shandong 255000,China;Chinese Academy of Surveying and Mapping,Beijing 100036)
出处
《导航定位学报》
CSCD
2020年第3期121-126,共6页
Journal of Navigation and Positioning
基金
国家自然科学基金资助项目(41674014,41931076)
国家重点研发计划项目(2016YFB0501700)。
关键词
测距方程
非线性
病态方程
多解性
粒子群算法
distance observation
non-linear models
ill-conditioned equation
multiple solutions
particle swarm optimization
