Label consistent K-SVD for sparse micro-doppler classification
Coutts, Fraser K. and Gaglione, Domenico and Clemente, Carmine and Li, Gang and Proudler, Ian K. and Soraghan, John J. Label consistent K-SVD for sparse micro-doppler classification. In: 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, GBR, pp. 90-94. ISBN 978-1-4799-8058-1
Full text not available in this repository.Request a copy from the Strathclyde authorAbstract
Secondary motions of targets observed by radar introduce non-stationary returns containing the so-called micro-Doppler information. This is characterizing information that can be exploited to enhance automatic target recognition systems. In this paper, the challenge of classifying the micro-Doppler return of helicopters is addressed. A robust dictionary learning algorithm, Label Consistent K-SVD (LC-KSVD), is applied to identify effectively and efficiently helicopters. The effectiveness of the proposed algorithm is demonstrated on both synthetic and real radar data.
| Author(s): | Coutts, Fraser K.  ORCID: https://orcid.org/0000-0003-2299-2648, Gaglione, Domenico ORCID: https://orcid.org/0000-0001-7401-1659, Clemente, Carmine ORCID: https://orcid.org/0000-0002-6665-693X, Li, Gang, Proudler, Ian K. and Soraghan, John J. ORCID: https://orcid.org/0000-0003-4418-7391 | Item type: | Book Section |
|---|---|
| ID code: | 55571 |
| Keywords: | doppler radar, airborne radar, helicopters, radar signal processing, radar target recognition, singular value decomposition, LC-KSVD, automatic target recognition systems, label consistent K-SVD, microdoppler information, microdoppler return, radar data, robust dictionary learning algorithm, secondary motions, sparse microDoppler classification, accuracy, blades, classification algorithms, dictionaries, radar, training, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering |
| Subjects: | Technology > Electrical engineering. Electronics Nuclear engineering |
| Department: | Faculty of Engineering > Electronic and Electrical Engineering Technology and Innovation Centre > Sensors and Asset Management |
| Depositing user: | Pure Administrator |
| Date deposited: | 18 Feb 2016 14:31 |
| Last modified: | 10 Jan 2020 08:21 |
| URI: | https://strathprints.strath.ac.uk/id/eprint/55571 |
| Export data: |
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)