Micro-motion Estimation for Ballistic Targets with Multi-frequency Chirp Decomposition

ZHOU Yejian; ZHANG Lei; JIAN Mao; WANG Hongxian; XING Mengdao

doi:10.11999/JEIT170163

Volume 39 Issue 10

Oct. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(10): 2360-2365

ZHOU Yejian, ZHANG Lei, JIAN Mao, WANG Hongxian, XING Mengdao. Micro-motion Estimation for Ballistic Targets with Multi-frequency Chirp Decomposition[J]. Journal of Electronics & Information Technology, 2017, 39(10): 2360-2365. doi: 10.11999/JEIT170163

Citation:

ZHOU Yejian, ZHANG Lei, JIAN Mao, WANG Hongxian, XING Mengdao. Micro-motion Estimation for Ballistic Targets with Multi-frequency Chirp Decomposition[J]. Journal of Electronics & Information Technology, 2017, 39(10): 2360-2365. doi: 10.11999/JEIT170163

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Micro-motion Estimation for Ballistic Targets with Multi-frequency Chirp Decomposition

doi: 10.11999/JEIT170163

Funds:

The National Natural Science Foundation of China (61301280, 61301293)

Received Date: 2017-02-27
Rev Recd Date: 2017-06-22
Publish Date: 2017-10-19

Abstract

Abstract

Accurate micro-motion characteristics analysis is an important technique to extract the geometrical characteristics of ballistic targets. In this paper, a multi-frequency Chirp sparse decomposition method for time- frequency analysis of micro-motion targets is proposed. First, the echo micro-Doppler expression of the equivalent scattering center model with the procession motion is deduced. After the translation compensation process, the multi-frequency echo are segmented and used to estimate the micro-motion characteristics with the Chirp sparse decomposition algorithm. While the sparseness of multi-frequency echo are effectively utilized, and the joint multi-frequency estimation improves the robustness of the algorithm. Finally, target,s micro-motion curve are obtained by stitching the segments estimation results. The validity and robustness of the algorithm are verified by electromagnetic simulation data and can be applied to time-frequency analysis and recognition of ballistic target.
- Micro-motions characteristics,
- Chirp Fourier,
- Time-frequency analysis,
- Multi-frequency,
- Sparse decomposition

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References(24)

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