Distributed Hypothesis Formation in Distributed Sensor Networks

Abstract

This report presents research results on distributed situation assessment in a distributed sensor network (DSN). The area of multitarget tracking and classification has been chosen to investigate issues associated with distributed hypothesis formation and evaluation. A general theory for Bayesian multitarget tracking has been developed. This is used as the basis for specifying the processing architecture at each node in the DSN. Each node contains the Generalized Tracker/Classifier for processing of local sensor data, an information fusion module to integrate processed information from various nodes, and an information distribution module. The problem of removing redundant information in a general distributed estimation system has also been investigated. Simulation results to study various issues associated with distributed situation assessment are presented.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA133849

Entities

People

  • C. Y. Chong
  • E. Tse
  • R. P. Wishner
  • S. Mori

Tags

Communities of Interest

  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Computational Science
  • Databases
  • Detection
  • Detectors
  • Information Processing
  • Information Science
  • Machine Learning
  • Markov Processes
  • Multitarget Tracking
  • Probability Distributions
  • Random Variables
  • Sensor Networks
  • Target Tracking
  • Warning Systems
  • Wireless Sensor Networks

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.

Technology Areas

  • AI & ML