Statistical Fusion of Unmanned Aerial Vehicle Observations for Aided Target Recognition

Abstract

The use of computers and sensors to detect and classify targets, often called aided target recognition (ATR), is an important component of military and civilian surveillance. Carrying it out from unmanned aerial vehicles is expensive in terms of both manpower and hardware. In this paper, we discuss the creation of a distributed ATR (DATR) method which replaces a single monolithic approach to ATR with a more robust multi-agent method. We present software and algorithms which have been developed for the purpose of testing and proving the validity of DATR, as well as some of the implementation possibilities and steps which we have taken to further prove the validity of the approach. Our examples and experiments with the normal light-weight ATR algorithms for our agents, combined with a fusion method based on belief calculus to demonstrate what DATR would perform like, show the validity of the approach