Wavelet detection of weak far-magnetic signal based on adaptive ARMA model threshold

Ning Zhang; Chun-sheng Lin; Shi Fang

doi:10.1117/12.833003

30 October 2009 Wavelet detection of weak far-magnetic signal based on adaptive ARMA model threshold

Ning Zhang, Chun-sheng Lin, Shi Fang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74951Z (2009) https://doi.org/10.1117/12.833003
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

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.

Citation Download Citation

Ning Zhang, Chun-sheng Lin, and Shi Fang "Wavelet detection of weak far-magnetic signal based on adaptive ARMA model threshold", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74951Z (30 October 2009); https://doi.org/10.1117/12.833003

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