Multi-Sensor Single Target Bearing-Only Tracking in Clutter

Abstract

In this paper, we have addressed the single target multiple acoustic UGS tracking in clutter using the particle filter (PF) algorithm. We have used realistic values for the probability of detection and false alarm. We have demonstrated that the PF algorithm works in a robust manner when the probability of detection is low and the false alarm is high as is the case in realistic harsh scenarios. In our future work, we plan to compare the performance of the PF with the EKF using the PDA approach and analyze the estimation accuracy by varying the accuracy of the acoustic sensor measurement.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2001
Accession Number
ADA409363

Entities

People

  • Mahendra Mallick
  • T. Kirubarajan

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Acoustic Detectors
  • Acoustic Measurement
  • Algorithms
  • Bayesian Networks
  • Computational Science
  • Detection
  • Estimators
  • Gaussian Distributions
  • Gaussian Noise
  • Gaussian Processes
  • Kalman Filters
  • Measurement
  • Models
  • Nonlinear Dynamics
  • Optimal Estimators
  • Probability
  • Statistical Analysis

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.