Decision Factors for Cooperative Multiple Warhead UAV Target Classification and Attack with Control Applications

Autonomous wide area search, classification and attack using Unmanned Combat Air Vehicles (UCAVs) is considered. The wide area search and attack scenario is modelled, capturing important problem parameters related to environment, seeker, and munitions. Probabilistic analysis is used to formulate and analytically solve for various probabilities, including the probability of mission success. Two methods are utilized. The first examines the sub-events required for various events to occur. The second utilizes a Markov chain approach. General expressions are first obtained that are applicable to any assumed a priori distributions of targets and false targets. These expressions are subsequently applied to a multiple warhead munition/UCAV operating in several multiple target/multiple false target scenarios. Examples of application of the analytically derived results are given for all facets of the system design and operation of Wide Area Search Munitions including the evaluation of cooperation schemes and rules of engagement. The problem is formulated as a control problem, and the possibility of adaptive control based on estimation of environmental parameters is examined.Air Force Inst of Tech Wright-Patterson AFB OH School of Engineering and Management is the author of 'Decision Factors for Cooperative Multiple Warhead UAV Target Classification and Attack with Control Applications', published 2004 under ISBN 9781423520634 and ISBN 1423520637.