The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

The paper describes airborne sensor networks for target tracking and identification in military applications. The raw information about targets from airborne sensors is uncertain and often noisy. One challenge in airborne sensor networks is how to effectively fuse enormous amounts of uncertain and noisy information for better battlefield situation assessment. In this paper we present a novel approach to military force aggregation and classification using Dempster-Shafer theory and doctrinal templates. Our approach helps commanders understand operational pictures of the battlefield, e.g., enemy force levels and deployment, and make better decisions than adversaries in the battlefield. A sample application of our approach is illustrated in the simulated testbed OTBSAF and RETSINA system.

Keywords

military force aggregation, Dempster-Shafer theory

Notes

Sponsor: Air Force Office of Scientific Research

Associated Center(s) / Consortia: Center for Integrated Manfacturing Decision Systems

Associated Lab(s) / Group(s): Advanced Agent - Robotics Technology Lab

Associated Project(s): Reusable Environment for Task Structured Intelligent Network Agents and AFOSR PRET: Information Fusion for Command and Control: The Translation of Raw Data To Actionable Knowledge and Decision

Number of pages: 8

Text Reference

Bin Yu, Katia Sycara, Joseph Andrew Giampapa, and Sean R. Owens, "Uncertain Information Fusion for Force Aggregation and Classification in Airborne Sensor Networks," AAAI-04 Workshop on Sensor Networks, July, 2004.

BibTeX Reference

@inproceedings{Yu_2004_4677,
   author = "Bin Yu and Katia Sycara and Joseph Andrew Giampapa and Sean R Owens",
   editor = "Gaurav S. Sukhatme and Adnan Darwiche and Deborah Estrin",
   title = "Uncertain Information Fusion for Force Aggregation and Classification in Airborne Sensor Networks",
   booktitle = "AAAI-04 Workshop on Sensor Networks",
   publisher = "AAAI Press",
   month = "July",
   year = "2004",
}

The Robotics Institute

Menu