Target tracking for heterogeneous smart sensor networks
James E. Bevington, Timothy X. McDonnell · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
Distributed sensor networks will play a key role in the network centric warfighting environments of the future. We envision a ubiquitous sensing `fabric,' comprising sensors distributed over the terrain and carried on manned and unmanned, terrestrial and airborne vehicles. As a complex `system of systems,' this fabric will need to adapt and self-organize to perform a variety of higher-level tasks such as surveillance and target acquisition. The topology and availability of the sensors will be constantly changing, as will the needs of users as dictated by evolving missions and operational environments. In this work, focusing on the task of target tracking, we address approaches for locating and organizing sensing and processing resources and present algorithms for suitably fusing the observations obtained from a varied and changing set of sensors. Run-time discovery and access of new sensing resources are obtained through the use of Java Jini, treating sensing resources as `services' and viewing higher-level processes such as tracking as clients. Algorithms for fusing generic sensor observations for target tracking are based on the extended Kalman filter, while detection and track initiation are based on a new likelihood projection technique. We present results from an implementation of these concepts in a real- time sensor testbed and discuss lessons learned.