A Joint Feature Extraction and Data Compression Method for Low Bit Rate Transmission in Distributed Acoustic Sensor Environments

Abstract

Unattended distributed passive acoustic sensors are widely used for remote battlefield surveillance, situation awareness and monitoring applications. To improve the spatial resolution for separating multiple closely spaced targets while reducing the on-board computational requirements, a modest quantity of single microphones could be deployed in a surveillance area of interest. These distributed microphones are considerably less expensive and small sized and contain generic DSP boards capable of performing detection, feature extraction and data compression tasks. They are equipped with basic communication systems to transmit essential compressed target information to a master station, which has more computational power to carry out high-level operations for sensor array processing and target classification. In this Phase I research, a subband-based joint detection, feature extraction, data compression/encoding system for low bit rate transmission of essential target information will be developed. The extracted features allow for detection and classification of the targets as well as data compression/encoding without incurring degradation in the overall performance. New methods for formation of the optimal sparse sensor arrays based upon multi-channel coherence information would also be developed. The effectiveness of the developed methods will be demonstrated on real and synthesized data sets.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2004
Accession Number
ADA430254

Entities

People

  • A. Pezeshki
  • M. R. Azimi-sadjadi

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Detectors
  • Angle Of Arrival
  • Coding
  • Communication Systems
  • Data Compression
  • Data Sets
  • Detection
  • Detectors
  • Digital Signal Processing
  • Feature Extraction
  • Frequency Bands
  • Hidden Markov Models
  • Identification
  • Probability
  • Recognition
  • Signal Processing
  • Target Classification

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • Space
  • Space - Space Objects