Accession Number:

ADA445061

Title:

General Markov Modeling of Pop-Up Threats with Applications to Persistent Area Denial

Descriptive Note:

Technical rept.

Corporate Author:

OHIO STATE UNIV COLUMBUS DEPT OF COMPUTER SCIENCE AND ENGINEERING

Report Date:

2006-01-01

Pagination or Media Count:

32.0

Abstract:

Pop-up threats usually appear or disappear randomly in a battlefield. If the next pop-up threat locations could be predicted, it would assist a search or attack team in getting a team of unmanned air vehicles UAVs to the threats sooner, such as in the case of a Persistent Area Denial PAD mission. The authors present a Markov model for predicting pop-up ground threats in military operations. They first introduce a general Markov chain of order n to capture the dependence of the appearance of pop-up threats on previous locations of the pop-up threats over time. Then they present an adaptive approach to estimating the stationary transition probabilities of the nth order Markov models. To choose the order of the Markov chain model for a specific application, they also discuss hypothesis tests from statistical inference on historical data of pop-up threat locations. Anticipating intelligent responses from an adversary, which might change its pop-up threat deployment strategy upon observing UAV movements, the authors present adaptive Markov chain models using a moving horizon approach to estimate possibly abrupt changes in transition probabilities. They consider the problem of cooperative control among multiple networked UAVs for the PAD mission. The combined information of predicted and actual pop-up target locations is utilized to develop efficient cooperative strategies for networked UAVs. Both a theoretical analysis and simulation results are presented to evaluate the Markov model used for predicting pop-up threats. These results demonstrate the effectiveness of cooperative strategies using the combined information of threats and predicted threats in improving overall mission performance. Index terms Pop-up threats Markov chain model Model order test Cooperative strategies.

Subject Categories:

  • Pilotless Aircraft
  • Statistics and Probability
  • Defense Systems
  • Target Direction, Range and Position Finding
  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE