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Proceedings Paper

Wavelet detection of weak far-magnetic signal based on adaptive ARMA model threshold
Author(s): Ning Zhang; Chun-sheng Lin; Shi Fang
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Paper Abstract

Based on Mallat algorithm, a de-noising algorithm of adaptive wavelet threshold is applied for weak magnetic signal detection of far moving target in complex magnetic environment. The choice of threshold is the key problem. With the spectrum analysis of the magnetic field target, a threshold algorithm on the basis of adaptive ARMA model filter is brought forward to improve the wavelet filtering performance. The simulation of this algorithm on measured data is carried out. Compared to Donoho threshold algorithm, it shows that adaptive ARMA model threshold algorithm significantly improved the capability of weak magnetic signal detection in complex magnetic environment.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74951Z (30 October 2009); doi: 10.1117/12.833003
Show Author Affiliations
Ning Zhang, Naval Univ. of Engineering (China)
Chun-sheng Lin, Naval Univ. of Engineering (China)
Shi Fang, Naval Univ. of Engineering (China)

Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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