Stochastic Matched Filters for Signal Detection Applications

Abstract

The stochastic matched filter (SMF) is a variation of the matched filter that can detect stochastic signals in noisy environments. Some earlier studies suggest that the SMF can be extended to the detection of frequency time-variant (nonstationary) signals, namely wideband modulated sonar in shallow water. This thesis considers the SMF algorithm first proposed by J.-F. Cavasillas in signal detection and estimation scenarios, and investigates its application to narrowband and chirp signals imbedded in white noise. In medium to high signal-to-noise ratio (SNR) values, results indicate that the SMF is a viable technique for signal detection and estimation, and could be employed in passive, real-time signal detection and estimation scenarios.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2022
Accession Number
AD1184685

Entities

People

  • Michelle M. Welch

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Acoustic Signals
  • Algorithms
  • Bandwidth
  • Computer Programs
  • Detection
  • Dimensionality Reduction
  • Eigenvalues
  • Electrical Engineering
  • Filters
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Matched Filters
  • Pattern Recognition
  • Random Variables
  • Schools
  • Signal Detection
  • Signal Processing
  • Simulations
  • Synthetic Aperture Radar
  • Time Domain
  • Time Signals
  • United States
  • United States Naval Academy
  • White Noise

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Engineering.
  • Image Processing and Computer Vision.