Multi-Target Tracking with Unattended Ground Sensors (UGS) Data

Abstract

This paper studies the performance of an Extended Kalman Filter/Multi-Hypothesis Tracking (EKF/MHT) tracking with data from seismic and acoustic sensors. We study the impact of tracking performance of the number, placement, and detection threshold associated with these sensors. Our algorithm scales well as the number of sensors increases, indicating its suitability for processing data sets associated with large numbers of unattended ground sensors.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2001
Accession Number
ADA409361

Entities

People

  • Craig Carthel
  • Mahendra Mallick
  • Stefano Coraluppi

Tags

DTIC Thesaurus Topics

  • Acoustic Detectors
  • Acoustic Tracking
  • Algorithms
  • Computations
  • Coordinate Systems
  • Detection
  • Detectors
  • False Alarms
  • Filters
  • Geometry
  • Kalman Filters
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Probability
  • Simulations
  • Target Tracking
  • Two Dimensional

Readers

  • Computational Modeling and Simulation
  • Sensor Fusion and Tracking Systems.