MAP-PF Detection and Tracking of Underwater Acoustic Targets

Abstract

The goal of this project was to develop an automated detection and tracking algorithm for broadband targets using complex hydrophone data from a passive acoustic array. The algorithm is an integral part of a larger Coherent Automated Multi-Target Tracker (CAMTT) system under development by Metron, Inc. for Detection, Classification, and Localization (DCL) for passive Anti-Submarine Warfare (ASW). The algorithm integrates the Maximum a Posteriori Penalty Function (MAP-PF) tracking algorithm with the Likelihood Ratio Detection and Tracking (LRDT) methodology. The detection and tracking problem is treated as a joint detection and estimation problem and the combined system automatically (1) detects and drops targets, (2) jointly estimates bearing vs. time tracks for all targets, and (3) jointly estimates the received spectrum of these targets. The spectral estimates improve the detection and tracking capability and are used to aid the classification component of the CAMTT system.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2009
Accession Number
ADA515401

Entities

People

  • Kristine L. Bell

Organizations

  • George Mason University

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Data Association
  • Detection
  • Detectors
  • Filters
  • Frequency
  • Frequency Bands
  • Kalman Filters
  • Measurement
  • Multitarget Tracking
  • Nonlinear Programming
  • Power Spectra
  • Radar
  • Spectra
  • Three Dimensional
  • White Noise

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.