Micro-Doppler Feature Extraction of Group Targets Using Signal Decomposition Based on Bessel Function Basis

ZHANG Qun; HE Qifang; LUO Ying

doi:10.11999/JEIT161036

Volume 38 Issue 12

Jan. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(12): 3056-3062

ZHANG Qun, HE Qifang, LUO Ying. Micro-Doppler Feature Extraction of Group Targets Using Signal Decomposition Based on Bessel Function Basis[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3056-3062. doi: 10.11999/JEIT161036

Citation:

ZHANG Qun, HE Qifang, LUO Ying. Micro-Doppler Feature Extraction of Group Targets Using Signal Decomposition Based on Bessel Function Basis[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3056-3062. doi: 10.11999/JEIT161036

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Micro-Doppler Feature Extraction of Group Targets Using Signal Decomposition Based on Bessel Function Basis

doi: 10.11999/JEIT161036

ZHANG Qun¹,
HE Qifang^{1
,
,},
LUO Ying¹

Funds:

The National Natural Science Foundation of China (61471386, 61571457)

Received Date: 2016-10-08
Rev Recd Date: 2016-11-08
Publish Date: 2016-12-19

Abstract

Abstract

Micro-Doppler (m-D) feature extraction is significant for group target discrimination, while the methods for single target are invalid. An m-D feature extraction method of group targets is proposed based on signal orthogonal decomposition. First, the Sinusoidal Frequency-Modulated (SFM) form of m-D signals and the decomposition result of the phase term on k-resolution Bessel basis is deduced. The m-D frequency is coarsely estimated by the one-to-one relationship between frequencies and basis functions. Then an algorithm is introduced to reduce the error and thus a finer estimation is obtained. Finally, the m-D frequency of each target is extracted by discrete echoes without phase shift ambiguity. Simulation experiments validate the effectiveness, and show that the proposed method outperforms the Sinusoidal Frequency Modulation Fourier Transform (SFMFT)-based method and Average Magnitude Difference Function (AMDF)-based method in estimation precision.
- Micro-Doppler (m-D),
- Group targets,
- Bessel function basis,
- Feature extraction,
- Parameter estimation

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References(30)

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