Classification systems and methods using convex hulls

摘要

A computerized classifier system that forms convex hulls containing all training experiences for each target class (e.g. threat/non-threat) is disclosed. The intersection of convex hulls for each pair of classes defines a region of ambiguity in feature space. Measurement of feature vector(s) outside an ambiguous region of feature space leads to a class decision while measurement of feature vector(s) within an ambiguous region of feature space defined by convex hulls causes a transition to a new feature space with new features. In particular embodiments, measured feature data includes estimated motion states and electrical lengths of a given object, and range, velocity and acceleration image data from second phase differences for debris mitigation.