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21 June 2024 Normalized magnetic source intensity localization method based on Gaussian convolutional kernel
Yabo Zhang, Yong Yang, Jiaqiang Wang, Qiangfeng Xu, Weiwei Zhu
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Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131670T (2024) https://doi.org/10.1117/12.3029634
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China
Abstract
To reduce the impact of magnetization direction and stripe noise on the positioning accuracy of magnetic target and improve the positioning accuracy of underground shallow unexploded ordnance with different attitudes, this paper studies a normalized magnetic source intensity localization method based on Gaussian convolutional kernel. The traditional normalized magnetic source intensity method is not affected by the magnetization direction, but the stripe noise generated by the method itself can affect the positioning result. The use of Gaussian convolutional kernel can eliminate the influence of stripe noise. The actual flight test shows that the proposed method can eliminate stripe noise and is not affected by magnetization direction, and the maximum positioning error for five different attitudes of simulated unexploded ordnance on the ground is less than 15cm. Therefore, this method can be used for high-precision positioning of underground shallow unexploded ordnance with different attitudes.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Yabo Zhang, Yong Yang, Jiaqiang Wang, Qiangfeng Xu, and Weiwei Zhu "Normalized magnetic source intensity localization method based on Gaussian convolutional kernel", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131670T (21 June 2024); https://doi.org/10.1117/12.3029634
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KEYWORDS
Magnetism
Unmanned aerial vehicles
Convolution
Magnetometers
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