光谱图
非负矩阵分解
特征提取
计算机科学
稳健性(进化)
矩阵分解
模式识别(心理学)
算法
约束(计算机辅助设计)
人工智能
正交性
数学
时频分析
基质(化学分析)
计算机视觉
物理
几何学
滤波器(信号处理)
生物化学
量子力学
基因
特征向量
复合材料
化学
材料科学
出处
期刊:IEEE Geoscience and Remote Sensing Letters
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:20: 1-5
被引量:1
标识
DOI:10.1109/lgrs.2023.3251723
摘要
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.
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