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
相关论文
共 50 条
  • [41] Particle swarm optimization based on simulated annealing for solving constrained optimization problems
    Jiao W.
    Liu G.-B.
    Zhang Y.-H.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2010, 32 (07): : 1532 - 1536
  • [42] Chaotic simulated annealing particle swarm optimization algorithm research and its application
    Yang, Y. (yuyang@cqu.edu.cn), 1722, Zhejiang University (47):
  • [43] AN improved particle swarm optimization algorithm for high dimension image matching
    Hua, Sunni
    Yu, Qiuze
    Zhou, Yuhao
    MIPPR 2013: PARALLEL PROCESSING OF IMAGES AND OPTIMIZATION AND MEDICAL IMAGING PROCESSING, 2013, 8920
  • [44] Multi-agent simulated annealing algorithm based on particle swarm optimization algorithm for protein structure prediction
    Lin, Juan
    Ning, Jing
    Du, Qing-Liang
    Zhong, Yi-Wen
    Journal of Bionanoscience, 2013, 7 (01): : 84 - 91
  • [45] An Improved Simulated Annealing Particle Swarm Optimization Algorithm for Path Planning of Mobile Robots Using Mutation Particles
    Lu, Jianzhang
    Zhang, Zhihao
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021
  • [46] Combination optimization of green energy supply in data center based on simulated annealing particle swarm optimization algorithm
    Liu, Xuehui
    Hou, Guisheng
    Yang, Lei
    FRONTIERS IN EARTH SCIENCE, 2023, 11
  • [47] Improved Salp Swarm Algorithm with Simulated Annealing for Solving Engineering Optimization Problems
    Duan, Qing
    Wang, Lu
    Kang, Hongwei
    Shen, Yong
    Sun, Xingping
    Chen, Qingyi
    SYMMETRY-BASEL, 2021, 13 (06):
  • [48] Hybrid particle swarm-based-simulated annealing optimization techniques
    Sadati, Nasser
    Zamani, Majid
    Mahdavian, Hamid Reza Feyz
    IECON 2006 - 32ND ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS, VOLS 1-11, 2006, : 2295 - +
  • [49] A cooperative particle swarm optimization with constriction factor based on simulated annealing
    Wu, Zhuang
    Zhang, Shuo
    Wang, Ting
    COMPUTING, 2018, 100 (08) : 861 - 880
  • [50] A Hybrid Particle Swarm Optimization Based on Symmetric Distribution and Simulated Annealing
    Li, Xueyan
    PROCEEDINGS OF THE 2016 6TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS, ENVIRONMENT, BIOTECHNOLOGY AND COMPUTER (MMEBC), 2016, 88 : 1965 - 1969
12345