Underground Target Localization Based on Improved Magnetic Gradient Tensor With Towed Transient Electromagnetic Sensor Array

• Published in: IEEE access Vol. 10; pp. 25025 - 25033
• Main Authors: Wang, Lijie, Zhang, Shuang, Chen, Shudong, Luo, Chaopeng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Coils; Error reduction; Localization; Location awareness; Magnetic domains; magnetic gradient tensor; Magnetic moments; Magnetic resonance; Mathematical analysis; Multiple target tracking; Receiving; Sensor arrays; Sensors; Signal to noise ratio; target localization; Tensors; Towed transient electromagnetic sensor array; unexploded ordnance (UXO)
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3156080

Errors of target localization with the traditional magnetic gradient tensor mainly comes from three aspects, namely, the large error of the magnetic gradient tensor for shallow targets, the low signal-to-noise ratio (SNR) of the response for deep targets, and the overlapping responses of multi-targets. In this study, a towed transient electromagnetic sensor with a <inline-formula> <tex-math notation="LaTeX">3\times3 </tex-math></inline-formula> receiving coils array is constructed. On the basis of the sensor array, an improved magnetic gradient tensor is proposed to accurately locate targets. For shallow targets, the magnetic gradient tensor is constructed using the responses of four adjacent receiving coils to reduce the error of the magnetic gradient tensor. For deep targets, all the responses of nine receiving coils are used to improve the SNR. Both the early and late time responses are used to roughly estimate the positions of multi-targets to improve the localization accuracy. Experimental results show that for underground targets within 2 m, the depth errors of the targets do not exceed 10 cm, and the horizontal errors of the targets are mostly within 10 cm, even if the responses of two adjacent targets overlap each other, indicating that the proposed method can effectively improve the localization accuracy of underground targets.