Open AccessPerformance improvement of magnetic anomaly detector using Karhunen–Loeve expansion
Author(s) -
Wan Chengbiao,
Pan Mengchun,
Zhang Qi,
Chen Dixiang,
Pang Hongfeng,
Zhu Xuejun
Publication year - 2017
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2016.0392
Subject(s) - detector , noise (video) , gaussian noise , earth's magnetic field , anomaly (physics) , autocorrelation , physics , mathematics , signal to noise ratio (imaging) , algorithm , computer science , optics , artificial intelligence , statistics , magnetic field , condensed matter physics , quantum mechanics , image (mathematics)
In this work, the authors improve the magnetic anomaly detector by using Karhunen–Loeve expansion, for expanding the detection distance of visually obscured ferromagnetic object when the target signal is contaminated by coloured noise. In the detector, the orthonormal basis functions are modified by the autocorrelation function of geomagnetic noise, and the anomaly is detected by matched filtering. Compared with the traditional detector, simulation results show that the modified detector has better performance with coloured Gaussian noise; especially, the improvement is more evident when the noise exponent is bigger. The real geomagnetic noise is proved to be coloured and obey approximate Gaussian distribution by the measurements in experiment. Tests with this noise indicate that the proposed detector achieves an incremental detection probability of 0.1 – 0.2 in the case of low signal‐to‐noise ratio, which makes it more attractive in practice.