Harbor Threat Detection, Classification, and Identification

Abstract

There is a critical need for reliably and rapidly detecting, identifying, and tracking submerged low observable targets in port environments, which would allow for rapid and effective neutralization of such threats. Without this capability, personnel, naval platforms and targets of opportunity are exposed to a cheap kill by an opportunistic threat. The goal of this effort is to exploit for the first time detailed active and passive acoustic signature information associated with harbor threats together with advanced Bayesian classifier techniques. In this effort the intent is to leverage the highly successful science and technology carried out in the broadband mine identification program [Ref. 1 and EOY reports for Award Numbers: N0001406WX20052 and N0001406WX20679].

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2007
Accession Number
ADA541163

Entities

People

  • Brian H. Houston
  • Larry Carin

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Acoustic Scattering
  • Algorithms
  • Autonomous Underwater Vehicles
  • Broadband
  • Classification
  • Databases
  • Detection
  • Divers
  • Frequency
  • Gaussian Distributions
  • Hidden Markov Models
  • Identification
  • Machine Learning
  • Measurement
  • Sequential Monte Carlo Methods
  • Signal Processing
  • Statistical Algorithms

Readers

  • Maritime Security/Maritime Homeland Security
  • Naval Mine Countermeasure Systems Development.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy