The capability to recognize ballistic threats, is a critical topic due to the increasing effectiveness of resultant objects and to economical constraints. In particular the ability to distinguish between warheads and decoys is crucial in order to mitigate the number of shots per hit and to maximize the ammunition capabilities. For this reason a reliable technique to classify warheads and decoys is required. In this paper the use of micro-Doppler signatures in conjunction with the 2-Dimensional Gabor filter is presented for this problem. The effectiveness of the proposed approach is demonstrated through the use of real data.
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