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Abstract
The ability to discriminate between Ballistic Missile warheads and confusing objects is an important topic from different points of view. In particular, the high cost of the interceptors with respect to tactical missiles may lead to an ammunition problem. Moreover, since the time interval in which the defence system can intercept the missile is very short with respect to target velocities, it is fundamental to minimise the number of shoots per kill. For this reason a reliable technique to classify warheads and confusing objects is required. In the efficient warhead classification system presented in this paper a model and a robust framework is developed, which incorporates different microDoppler based classification techniques. The reliability of the proposed framework is tested on both simulated and real data
Original language | English |
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Pages (from-to) | 1088-1108 |
Number of pages | 21 |
Journal | IEEE Transactions on Aerospace and Electronic Systems |
Volume | 53 |
Issue number | 3 |
Early online date | 7 Feb 2017 |
DOIs | |
Publication status | Published - 30 Jun 2017 |
Keywords
- ballistic missiles classification
- micro-doppler based classification
- cadence velocity diagram
- pseudo-Zernike moments
- Gabor filters
- ACVD based feature vector approach
- pseudo-Zernike based feature vector approach
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Dive into the research topics of 'On model, algorithms and experiment for micro-doppler based recognition of ballistic targets'. Together they form a unique fingerprint.Profiles
Projects
- 1 Finished
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Signal Processing Solutions For the Networked Battlespace
Clemente, C. (Academic) & Soraghan, J. (Academic)
1/04/13 → 31/03/18
Project: Research
Datasets
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micro-Doppler ballistic targets
Persico, A. R. (Creator), Clemente, C. (Creator), Gaglione, D. (Creator), Ilioudis, C. (Creator) & Soraghan, J. (Creator), University of Strathclyde, 30 Sept 2016
DOI: 10.15129/c693ee6a-487f-47ec-bb39-fdc3ff8f273a
Dataset