Abstract
For searching and detecting near-field unknown ferromagnetic targets, four automatic search algorithms are proposed based on magnetic anomaly information from any position on planes or in space. Firstly, gradient search algorithms and enhanced gradient search algorithms are deduced using magnetic modulus anomaly information and magnetic vector anomaly information. In each algorithm, there are plane search forms and space search forms considering different practical search situations. Then the magnetic anomaly space data of typical magnetic source of oblique magnetization are forwardly simulated by ANSYS MAXWELL software. The plane distributions of some variables are numerically computed and the search destinations of different algorithms are predicted. Four automatic search algorithms are applied to simulate search paths on three characteristic orthogonal planes and in whole solution space. The factor affecting the performance of algorithms is analyzed. Features of each algorithm in different conditions are analyzed and suitable applications are discussed and verified by the experiment. The results show that proposed search algorithms require few prior information and have real-time performance for searching and tracking magnetic anomaly target.
Highlights
With the development of magnetic signal processing technology [1,2,3,4,5,6,7], magnetic anomaly detection (MAD) has been widely applied for ferromagnetic object detection and location which plays important roles in many situations such as area surveillance and boundary security [8, 9], motion tracking [10, 11], and crack detection [12, 13].According to objects’ features, there are two types of technologies for MAD
We have proposed four automatic search algorithms based on searching and tracking near-field magnetic anomaly targets
400 600 800 1000 x (m) magnetic vector anomaly from any point, automatic search can be conducted on planes or in space
Summary
With the development of magnetic signal processing technology [1,2,3,4,5,6,7], magnetic anomaly detection (MAD) has been widely applied for ferromagnetic object detection and location which plays important roles in many situations such as area surveillance and boundary security [8, 9], motion tracking [10, 11], and crack detection [12, 13]. The other type technology of MAD concentrates on the detection of large-scale area with complex magnetic anomaly distribution which is mainly applied in mineral exploration and geologic mapping of prospective areas with buried igneous bodies This kind of studies relies on magnetic inversion and quantitative interpretation [29,30,31,32] in whole data space, which can apply in source localization, buried depth estimation, and edge detection of mineral resources. Comparing with the two types of technologies above, four different algorithms applied in automatic searching near-field unknown ferromagnetic targets we proposed require few prior information and have real-time performance for searching and tracking magnetic anomaly targets.
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