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

Persico, Adriano Rosario and Clemente, Carmine and Gaglione, Domenico and Ilioudis, Christos V. and Cao, Jianlin and Pallotta, Luca and De Maio, Antonio and Proudler, Ian and Soraghan, John J. (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. ISSN 0018-9251 (https://doi.org/10.1109/TAES.2017.2665258)

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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