Open AccessAn Intelligent Geomagnetic Search Navigation Method Based on Evolutionary Gradient Strategy
Author(s) -
Xintian Ren,
Qi Zhang,
Mengchun Pan,
Dixiang Chen,
Zhongyan Liu,
Jiafei Hu,
Chen Zhuo,
Zhenxiong Wang,
Ze Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1885/4/042004
Subject(s) - earth's magnetic field , computer science , artificial intelligence , physics , magnetic field , quantum mechanics
Currently, most of the geomagnetic navigation methods are matching navigation algorithms, which require the geomagnetic maps retrieved in advance, and saved in a database. However, there are a great number of unknown environments exist worldwide that limit the extensive application of the geomagnetic matching method in practice. In this paper, an intelligent geomagnetic search navigation method based on the evolutionary gradient search (EGS) algorithm is proposed. The performance of the search and navigation method is analysed with both simulated and real geomagnetic data. And the conclusion is that compared with other intelligent search strategies, the proposed algorithm has better navigation performance with less average navigation error, 161m, which is equivalent to the most traditional geomagnetic matching algorithms. Thus, the EGS algorithm proposed in this paper can effectively improve the performance of geomagnetic navigation without prior geomagnetic information.