Self-similarity matrix based slow-time feature extraction for human target in high-resolution radar
| Autor: | Alexander Yarovoy, Pascal Aubry, Yuan He, F. Le Chevalier |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
slow-time feature
business.industry Computer science Property (programming) Feature extraction Pattern recognition high-resolution radar Mutual information Measure (mathematics) self-similarity matrix Matrix (mathematics) Similarity (network science) Feature (computer vision) Computer vision Artificial intelligence Self-similarity matrix Electrical and Electronic Engineering human target analysis business |
| Zdroj: | International Journal of Microwave and Wireless Technologies, FirstView Article pp 1-12 |
| ISSN: | 1759-0795 1759-0787 1474-0028 |
| Popis: | A new approach is proposed to extract the slow-time feature of human motion in high-resolution radars. The approach is based on the self-similarity matrix (SSM) of the radar signals. The Mutual Information is used as a measure of similarity. The SSMs of different radar signals (high-resolution range profile, micro-Doppler, and range-Doppler video sequence) are compared, and the angel-invariant property of the SSMs is demonstrated. The SSM for different activities (i.e. walking and running) is extracted from range-Doppler video sequence and analyzed. Finally, simulation result is validated by experimental data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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