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Ground moving target classification based on micro-Doppler signature using novel spectral information features
- Source :
- 2017 European Radar Conference (EURAD), 2017 European Radar Conference (EURAD), Oct 2017, Nuremberg, France. pp.255-258
- Publication Year :
- 2017
- Publisher :
- HAL CCSD, 2017.
-
Abstract
- A novel spectral-based feature set is proposed for ground moving target classification using a battlefield surveillance radar. Precise frequencies and coefficients are extracted from the backscattered radar signal which is used as an information in Automatic Target Recognition (ATR) system to solve the problem of ground moving target classification. The proposed ATR system is realized by combining Gaussian Mixture Model (GMM) with Maximum Likelihood (ML) rule. Experimental signals, realized with ground surveillance radar operating in centimetre range wavelengths, are used to test our ATR system. Numerical evaluation results are presented to assess the performance gain provided by the proposed method.
- Subjects :
- Computer science
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing
Feature extraction
02 engineering and technology
01 natural sciences
Signal
law.invention
symbols.namesake
Automatic target recognition
0203 mechanical engineering
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
law
Radar
Radar MASINT
ComputingMilieux_MISCELLANEOUS
020301 aerospace & aeronautics
business.industry
010401 analytical chemistry
Pattern recognition
Mixture model
0104 chemical sciences
symbols
Artificial intelligence
business
Doppler effect
Secondary surveillance radar
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- 2017 European Radar Conference (EURAD), 2017 European Radar Conference (EURAD), Oct 2017, Nuremberg, France. pp.255-258
- Accession number :
- edsair.doi.dedup.....31d5b45a5e29fd96155e8b05d8d4be25