The capability to exploit multiple sources of information is of fundamental importance in a battlefield scenario. Information obtained from different sources, and separated in space and time, provide the opportunity to exploit diversities in order to mitigate uncertainty. For the specific challenge of Automatic Target Recognition (ATR) from radar platforms, both channel (e.g. polarization) and spatial diversity can provide useful information for such a specific and critical task. In this paper the use of pseudo-Zernike moments applied to multi-channel multi-pass data is presented exploiting diversities and invariant properties leading to high confidence ATR, small computational complexity and data transfer requirements. The effectiveness of the proposed approach, in different configurations and data source availability is demonstrated using real data.
@article{arxiv.1404.1682,
title = {Pseudo-Zernike Based Multi-Pass Automatic Target Recognition From Multi-Channel SAR},
author = {Carmine Clemente and Luca Pallotta and Ian Proudler and Antonio De Maio and John J. Soraghan and Alfonso Farina},
journal= {arXiv preprint arXiv:1404.1682},
year = {2014}
}
Comments
The paper has been withdrawn due to conceptual errors in the performance analysis and to the fact that a substantial restructuring of the paper is required