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Open Access research with a European policy impact...

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EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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Model-based sparse recovery method for automatic classification of helicopters

Clemente, Carmine and Gaglione, Domenico and Coutts, Fraser Kenneth and Li, Gang and Soraghan, John (2015) Model-based sparse recovery method for automatic classification of helicopters. In: 2015 IEEE Radar Conference (RadarCon). IEEE, pp. 1161-1165. ISBN 978-1-4799-8231-8

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Abstract

The rotation of rotor blades of a helicopter induces a Doppler modulation around the main Doppler shift. Such a non-stationary modulation, commonly called micro-Doppler signature, can be used to perform classification of the target. In this paper a model-based automatic helicopter classification algorithm is presented. A sparse signal model for radar return from a helicopter is developed and by means of the theory of sparse signal recovery, the characteristic parameters of the target are extracted and used for the classification. This approach does not require any learning process of a training set or adaptive processing of the received signal. Moreover, it is robust with respect to the initial position of the blades and the angle that the LOS forms with the perpendicular to the plane on which the blades lie. The proposed approach is tested on simulated and real data.