Improved Particle Swarm Optimization Geomagnetic Matching Algorithm Based on Simulated Annealing

被引：13
|
作者：
Ji, Caijuan [1 ]
Chen, Qingwei [1 ]
Song, Chengying [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Dept Control Sci & Engn, Nanjing 210094, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Navigation; Real-time systems; Particle swarm optimization; Particle measurements; Atmospheric measurements; Satellite navigation systems; Magnetic domains; Geomagnetic matching; particle swarm optimization; simulated annealing; NAVIGATION; ICCP;
D O I：
10.1109/ACCESS.2020.3043794
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
As a new assistant navigation technology using geophysical field for navigation, geomagnetic matching navigation can effectively alleviate the problems such as the unavailability of satellite and the easy divergence of position data of inertial navigation system in the process of navigation. It can also carry out real-time assistant navigation with high concealment, all-around area and all-weather. According to the principle of geomagnetic matching and the geomagnetic affine model, considering that the basic particle swarm optimization algorithm is easy to fall into local extremum, this paper introduces particle swarm optimization geomagnetic matching algorithm based on simulated annealing(SAPSO) for limitations of traditional matching algorithm. What's more, the SAPSO is improved from three parts: constraints, parameters and function of fitness. Finally, the simulation analysis is carried out from five aspects to verify the effectiveness and accuracy of the improved SAPSO.
引用
收藏
页码：226064 / 226073
页数：10
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