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Approximate Formulas for the Blind Spot Prediction of Phased Arrays with Uniaxial Multilayer WAIM Sheet
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, provides the opportunity to exploit diversities to mitigate uncertainty. In this study, the authors address the problem of automatic target recognition (ATR) from synthetic aperture radar platforms. The author’s approach exploits both channel (e.g. polarisation) and spatial diversity to obtain suitable information for such a critical task. In particular they use the pseudo-Zernike moments (pZm) to extract features representing commercial vehicles to perform target identification. The proposed approach exploits diversities and invariant properties of pZm leading to high confidence ATR, with limited computational complexity and data transfer requirements. The effectiveness of the proposed method is demonstrated using real data from the Gotcha dataset, in different operational configurations and data source availability.
Paper for Seminar/Symposium/Conference
2016 IEEE International Symposium on Phased Array Systems and Technology (18-21 October 2016, Waltham, MA, USA)
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