13 April 2018 Adaptive filtering method for magnetic anomaly detection
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Abstract
Magnetic anomaly detection (MAD) is a technique applied in searching, localizing, and even tracking (if the target is moving) a ferromagnetic target of interest. Due to the complexity of the ambient magnetic field, almost all of the detection methods need a filter to be a preprocessing procedure. A typical way is passing the measured signal through a fixed frequency band that contains the frequency of the target signal. However, the target signal’s frequency is mostly determined by the movement velocity of the magnetometer and the distance from magnetometer to target. Namely, in different cases, the targets’ frequencies are different. We analyze the target model and represent the target signal with a single scalar variable. Through projecting the three-dimensional space into a two-dimensional plane, we lastly transform the target signal into a superposition of three sinusoids. Based on it, we propose a method to estimate the frequency band adaptively. Furthermore, we present an adaptive filtering method based on wavelet transform and take some simulation tests to prove that the proposed method has better performance compared with traditional filters.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Guanyi Zhao, Qi Han, Xiaojun Tong, Hong Guo, "Adaptive filtering method for magnetic anomaly detection," Journal of Applied Remote Sensing 12(2), 025003 (13 April 2018). https://doi.org/10.1117/1.JRS.12.025003 Submission: Received 14 September 2017; Accepted 28 March 2018
Submission: Received 14 September 2017; Accepted 28 March 2018
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