Accession Number : ADA475342
Title : Fusion of Imperfect Information in the Unified Framework of Random Sets Theory: Application to Target Identification
Descriptive Note : Technical rept.
Corporate Author : DEFENCE RESEARCH AND DEVELOPMENT CANADA VALCARTIER (QUEBEC)
Personal Author(s) : Florea, Mihai C ; Jousselme, Anne-Laure ; Bosse, Eloi
Report Date : Nov 2007
Pagination or Media Count : 142
Abstract : This is a study of the applicability of random sets theory to target identification problems as a technique for fusion of imperfect information. For target identification, several sources of information (radar, ESM - Electronic Support Measures, SAR - Synthetic Aperture Radar, IR images) are available. Since the information provided is always imperfect and several kinds of imperfection may be encountered (imprecision, uncertainty, incompleteness, vagueness, etc.), several theories were developed to assist probability theory (long the only tool available to deal with uncertainty) in data fusion problems. In recent decades fuzzy sets theory was developed to deal with vague information, possibility theory was developed to deal with incomplete information, evidence theory was developed to deal with imprecise and uncertain information, and rough sets theory was developed to deal with vague and uncertain information. These theories have several points in common; here we study random sets theory, which is a unifying framework for all the aforementioned theories. In two simple test scenarios, we demonstrate the effectiveness of this unifying framework for representing and fusing imperfect information in the target identification application.
Descriptors : *DATA FUSION , *INFORMATION THEORY , *TARGET DETECTION , *SET THEORY , UNCERTAINTY , PROBABILITY , ELECTRONIC SUPPORT MEASURES , CANADA , SYNTHETIC APERTURE RADAR , INFRARED IMAGES , FUZZY SETS
Subject Categories : Information Science
Target Direction, Range and Position Finding
Distribution Statement : APPROVED FOR PUBLIC RELEASE