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Nowadays the identification of ballistic missile warheads in a cloud of decoys and debris is essential for defence systems in order to optimize the use of ammunition resources, avoiding to run out of all the available interceptors in vain. This paper introduces a novel solution for the classification of ballistic targets based on the computation of the inverse Radon transform of the target signatures, represented by a high resolution range profile frame acquired within an entire period of the main rotation of the target. Namely, the precession for warheads and the tumbling for decoys are taken into account. Following, the pseudo-Zernike moments of the resulting transformation are evaluated as the final feature vector for the classifier. The extracted features guarantee robustness against target's dimensions and rotation velocity, and the initial phase of the target's motion. The classification results on simulated data are shown for different polarizations of the electromagnetic radar waveform and for various operational conditions, confirming the validity of the algorithm.
|Number of pages||25|
|Journal||IEEE Transactions on Aerospace and Electronic Systems|
|Early online date||15 Mar 2019|
|Publication status||E-pub ahead of print - 15 Mar 2019|
- ballistic missile defence
- high resolution range profile
- inverse radon transform
- psedo-Zernike moments
- ballistic target classification
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