Tracking multiple targets with self-organizing distributed ground sensors

Richard Brooks, David Friedlander, John Koch, Shashi Phoha

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

This paper describes a fully distributed approach to target tracking that we have implemented and tested in a military setting. The approach uses local sharing of robust statistics that summarize local events. Local collaboration extracts detection information such as time, velocity, position, heading and target type from the summary statistics. Groups of nodes used for local collaboration are determined dynamically at run time. Local collaboration information is compared with a list of tracks in the immediate vicinity. A variation on the nearest-neighbor algorithm associates detections to tracks. This paper extends our previous work by analyzing the ability of our distributed tracker to track multiple targets in a simulated environment. Results from simulations and field tests of the approach are provided.

Original languageEnglish (US)
Pages (from-to)874-884
Number of pages11
JournalJournal of Parallel and Distributed Computing
Volume64
Issue number7
DOIs
StatePublished - Jan 1 2004

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Tracking multiple targets with self-organizing distributed ground sensors'. Together they form a unique fingerprint.

  • Cite this