Improved Particle Swarm Optimization Geomagnetic Matching Algorithm Based on Simulated Annealing

被引：14
|
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
  • [1] An Improved Particle Swarm Optimization Algorithm Based on Simulated Annealing
    Yang, Huafen
    Yang, Zuyuan
    Yang, You
    Zhang, Lihui
    2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014, : 529 - 533
  • [2] Particle Swarm Optimization Algorithm Based on the Idea of Simulated Annealing
    Dong Chaojun
    Qiu Zulian
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2006, 6 (10): : 152 - 157
  • [3] Improvement of Original Particle Swarm Optimization Algorithm Based on Simulated Annealing Algorithm
    Cong Liang
    Hu Chengquan
    Guo Zongpeng
    Jiang Yu
    Sha Lihua
    PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 6, 2008, : 671 - 676
  • [4] A cooperative evolutionary algorithm based on simulated annealing algorithm and particle swarm optimization
    Wang, LF
    Zeng, JC
    PROGRESS IN INTELLIGENCE COMPUTATION & APPLICATIONS, 2005, : 19 - 25
  • [5] Adaptive simulated annealing particle swarm optimization algorithm
    Yan Q.
    Ma R.
    Ma Y.
    Wang J.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2021, 48 (04): : 120 - 127
  • [6] Application of Particle Swarm Optimization Algorithm in Geomagnetic Matching Navigation
    Li, Shi-xin
    Cai, Ru-yi
    Fan, Chao-nan
    Huo, Xiang-zuo
    2018 2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELING AND SIMULATION (AMMS 2018), 2018, 305 : 123 - 127
  • [7] An Improved Self-Adaptive Particle Swarm Optimization Algorithm with Simulated Annealing
    Jun, Shu
    Jian, Li
    2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 3, PROCEEDINGS, 2009, : 396 - +
  • [8] Based on Particle Swarm Optimization and Simulated Annealing Combined Algorithm for Reactive Power Optimization
    Wang, Zhenshu
    Li, Linchuan
    Li, Bo
    2009 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), VOLS 1-7, 2009, : 1909 - +
  • [9] Hybrid particle swarm optimization with simulated annealing
    Pan, Xiuqin
    Xue, Limiao
    Lu, Yong
    Sun, Na
    MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (21) : 29921 - 29936
  • [10] Hybrid particle swarm optimization with simulated annealing
    Wang, XH
    Li, JJ
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 2402 - 2405
12345