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On model, algorithms, and experiment for micro-doppler-based recognition of ballistic targets

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posted on 06.09.2017, 13:39 by Adriano Rosario Persico, Carmine Clemente, Domenico Gaglione, Christos V. Ilioudis, Jianlin Cao, Luca Pallotta, Antonio De Maio, Ian Proudler, John J. Soraghan
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 defense system can intercept the missile is very short with respect to target velocities, it is fundamental to minimize 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 micro-Doppler-based classification techniques. The reliability of the proposed framework is tested on both simulated and real data.

Funding

This work was supported by the Engineering and Physical Sciences Research Council under Grant EP/K014307/1.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Aerospace and Electronic Systems

Volume

53

Issue

3

Pages

1088 - 1108

Citation

PERSICO, A.R. ... et al., 2017. On model, algorithms, and experiment for micro-doppler-based recognition of ballistic targets. IEEE Transactions on Aerospace and Electronic Systems, 53 (3), pp. 1088 - 1108.

Publisher

IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

04/07/2016

Publication date

2017

Notes

Published open access with a CC BY licence by IEEE.

ISSN

0018-9251

Language

en

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