EGU2020-8423, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-8423
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

The selection of adaptive region of geomagnetic map based on PCA and GA-BP neural network

Yang Chong1,2, Dongqing Zhao1, Guorui Xiao1, Minzhi Xiang1, Linyang Li1, and Zuoping Gong1
Yang Chong et al.
  • 1Institute of geospatial information, Information Engineering University, Zhengzhou, China (chongyang_geodesy@outlook.com)
  • 2State Key Laboratory of Geo-information Engineering, Xi'an, China (chongyang_geodesy@outlook.com)

The selection of adaptive region of geomagnetic map is an important factor that affects the positioning accuracy of geomagnetic navigation. An automatic recognition and classification method of adaptive region of geomagnetic background field based on Principal Component Analysis (PCA) and GA-BP neural network is proposed. Firstly, PCA is used to analyze the geomagnetic characteristic parameters, and the independent characteristic parameters containing principal components are selected. Then, the GA-BP neural network model is constructed, and the correspondence between the geomagnetic characteristic parameters and matching performance is established, so as to realize the recognition and classification of adaptive region. Finally, Simulation results show that the method is feasible and efficient, and the positioning accuracy of geomagnetic navigation is improved.

How to cite: Chong, Y., Zhao, D., Xiao, G., Xiang, M., Li, L., and Gong, Z.: The selection of adaptive region of geomagnetic map based on PCA and GA-BP neural network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8423, https://doi.org/10.5194/egusphere-egu2020-8423, 2020