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Proceedings Paper

Real-time radar data fusion and registration systems for single integrated air picture
Author(s): Andrew L. Drozd; Ruixin Niu; Irina Kasperovich; Pramod K. Varshney; Clifford E. Carroll
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Paper Abstract

Real-time fusion of data collected from a variety of radars that acquire information from multiple perspectives and/or different frequencies, is being shown to provide a more accurate picture of the adversary threat cloud than any single radar or group of radars operating independently. This paper describes a cooperative multi-sensor approach in which multiple radars operate together in a non-interference limited manner, and where decision algorithms are applied to optimize the acquisition, tracking, and discrimination of moving targets with low false alarm rate. The approach is twofold: (i) measure and process radar returns in a shared manner for target feature extraction by exploiting frequency and spatial diversity; and (ii) employ feature-aided track/fusion algorithms to detect, discriminate, and track real targets from the adversary noise cloud. The results of computer simulations are provided that demonstrate the advantages of this approach.

Paper Details

Date Published: 17 May 2006
PDF: 9 pages
Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350U (17 May 2006); doi: 10.1117/12.665786
Show Author Affiliations
Andrew L. Drozd, ANDRO Computational Solutions, LLC (United States)
Ruixin Niu, Syracuse Univ. (United States)
Irina Kasperovich, ANDRO Computational Solutions, LLC (United States)
Pramod K. Varshney, Syracuse Univ. (United States)
Clifford E. Carroll, ANDRO Computational Solutions, LLC (United States)

Published in SPIE Proceedings Vol. 6235:
Signal Processing, Sensor Fusion, and Target Recognition XV
Ivan Kadar, Editor(s)

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