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Proceedings Paper

On a nascent mathematical-physical latency-information theory, part I: the revelation of powerful and fast knowledge-unaided power-centroid radar
Author(s): Erlan H. Feria
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Paper Abstract

In this first part of the latest latency-information theory (LIT) and applications paper series powerful and fast 'knowledge-unaided' power-centroid (F-KUPC) radar is revealed. More specifically, it is found that for real-world airborne moving target indicator radar subjected to severely taxing environmental conditions F-KUPC radar approximates the signal to interference plus noise ratio (SINR) radar performance derived with more complex knowledge-aided power-centroid (KAPC) radar. KAPC radar was discovered earlier as part of DARPA's 2001-2005 knowledge-aided sensor signal processing expert reasoning (KASSPER) Program and outperforms standard priorknowledge radar schemes by several orders of magnitude in both the compression of sourced intelligence-space of priorknowledge, in the form of SAR imagery, and the compression of processing intelligence-time of the associated clutter covariance processor, while also yielding an average SINR radar performance that is approximately 1dB away from the optimum. In this paper, it is shown that the average SINR performance of significantly simpler F-KUPC radar emulates that of KAPC radar and, like KAPC radar, outperforms a conventional knowledge-unaided sample covariance matrix inverse radar algorithm by several dBs. The matlab simulation programs that were used to derive these results will become available in the author's Web site.

Paper Details

Date Published: 4 May 2009
PDF: 18 pages
Proc. SPIE 7351, Mobile Multimedia/Image Processing, Security, and Applications 2009, 73510U (4 May 2009); doi: 10.1117/12.819040
Show Author Affiliations
Erlan H. Feria, College of Staten Island, CUNY (United States)

Published in SPIE Proceedings Vol. 7351:
Mobile Multimedia/Image Processing, Security, and Applications 2009
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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