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Proceedings Paper

Robust centralized predetection fusion for enhanced target detection
Author(s): Ivan Kadar; Bernard S. Abrams; Louis A. Lovas; Mark G. Alford; William P. Berry; Martin E. Liggins
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Paper Abstract

The evolutionary design, signal conditioning, performance prediction and validation with experimental data of robust centralized fusion algorithms (CFAs) that operate in clutter, with unspecified distribution, are presented. Two CFAs, called non-coherent integration and T-squared, followed by an adaptive constant false alarm post-processing along with several variants were evaluated. The fusion algorithms were designed to provide various degrees of robustness and inherent CFAR properties to Weibull and Lognormal clutter. Each algorithm's fusion performance, defined via receiver operating characteristics (ROCs), was compared and also compared to the ROCs of the individual sensors (both by Monte Carlo simulation and by the use of measured data with target in clutter). The test results with both target in the clear and target in clutter data are in concert with the theoretically predicted behavior.

Paper Details

Date Published: 10 June 1994
PDF: 19 pages
Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177766
Show Author Affiliations
Ivan Kadar, Grumman Aerospace and Electronics (United States)
Bernard S. Abrams, Grumman Aerospace and Electronics (United States)
Louis A. Lovas, Grumman Aerospace and Electronics (United States)
Mark G. Alford, Rome Lab. (United States)
William P. Berry, Rome Lab. (United States)
Martin E. Liggins, Rome Lab. (United States)

Published in SPIE Proceedings Vol. 2232:
Signal Processing, Sensor Fusion, and Target Recognition III
Ivan Kadar; Vibeke Libby, Editor(s)

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