Inferrence evaluation in a finite evnidence domain

摘要

Modeling of a target starts with a subject matter expert (SME) analysis of the available sensor(s) data. The SME then forms relationships between the data and known target attributes, called evidence, to support modeling of different types of targets or target activity. Speeds in the interval 10 to 30 knots and ranges less than 30 nautical miles are two samples of target evidence derived from sensor data. Evidence is then organized into sets to define the activities of a target and/or to distinguish different types of targets. For example, near an airport, target activities of takeoff, landing, and holiding need to b e evaluated in addition to 5target classification of civilian or commerical aircraft. This paper discusses a method for evaluation of the inferred activities over the finite evidence domain formed from the collection of models under consideration. The methodology accounts for repeated use of evidence in different models. For example, "near an airport" is a required piece of evidence used prepeatedly in the takeoff, landing, and holding models of a wide area sensor. Properties of the activity model evaluator methodology are discussed in terms of model construction and informal results are presented in a Boolean evidence type of problem domain.