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Distributed Detection Theory and Data Fusion
Final rept. 15 Jan 1993-14 Jan 1994
SYRACUSE UNIV NY DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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Design of distributed order statistic constant false alarm rate OS-CFAR detection systems with data fusion was investigated. Its performance for different fusion rules and for a variety of nonhomogeneous backgrounds such as clutter edges and interfering targets was analyzed. Issues related to sampling and quantization in distributed detection systems were addressed. Sampling schemes for signal detection based on Ali-Silvey distance measures were derive. Performance enhancement over uniform sampling was shown. A number of collaborative research projects with Rome Laboratory engineers were carried out. The most notable one was the development of a prototype of an expert system CFAR ES-CFAR processor. This processor intelligently selects the CFAR algorithm based upon the observed characteristics of the environment. Substantial performance improvement over a conventional CFAR processor was demonstrated. Distributed detection, Data fusion, Detection theory.
APPROVED FOR PUBLIC RELEASE