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Micro-Doppler Extraction for Cone-Shaped Target Using Constrained Nonnegative Matrix Factorization
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DOI：10.1109/LGRS.2023.3251723.png)
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摘要
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Micro-Doppler (MD) extraction is the precondition for target classification based on micro-motion. This letter proposes a method for MD extraction based on constrained nonnegative matrix factorization (NMF). The proposed algorithm is applied to the time-frequency spectrogram of the cone-shaped precession target. Taking the sparsity constraint, temporal continuity constraint, and approximate orthogonality constraint into consideration, the basic NMF is improved to match the MD separation problem, and thus the time-frequency spectrogram of each scattering center is reconstructed by deriving the basis matrix and coefficient matrix. Morphological processing, valid frequency extraction, and MD curve fitting are conducted on the reconstructed spectrograms to extract the MD accurately. Experiment results show that the proposed approach outperforms other algorithms with better accuracy and robustness.
Keyword:
Spectrogram
Time-frequency analysis
Manganese
Scattering
Image reconstruction
Data mining
Geoscience and remote sensing
Cone-shaped target
micro-Doppler (MD)
non-negative matrix factorization (NMF)
signal separation
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
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