Enhanced Multistatic Active Sonar via Innovative Signal Processing

Abstract

Our goal is to address fundamental signal processing research issues for enhanced multistatic active sonar systems. To effectively mitigate the reverberation problems encountered in shallow water, both probing waveform synthesis and receive filter design need to be optimized. In this report, CAN (cyclic algorithm-new) is employed to synthesize probing sequences with good aperiodic auto-correlation properties. The performance of the CAN sequences will be compared with those of pseudo random noise and random phase sequences. Two adaptive receiver designs, namely the iterative adaptive approach (IAA) and the sparse learning via iterative minimization (SLIM) method, will also be considered. IAA and SLIM will be compared with the conventional matched filter method. In addition, a fast implementation of the SLIM algorithm is presented by taking advantage of the conjugate gradient method and the fast Fourier transform.

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Document Details

Document Type
Technical Report
Publication Date
Dec 31, 2010
Accession Number
ADA535674

Entities

People

  • Jiantao Li

Organizations

  • University of Florida

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Active Sonar
  • Algorithms
  • Data Sets
  • Detection
  • Fast Fourier Transforms
  • Filters
  • Learning
  • Matched Filters
  • Multiple Input Multiple Output
  • Radial Velocity
  • Reverberation
  • Sequences
  • Shallow Water
  • Signal Processing
  • Sonar
  • Target Recognition
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Computer Programming and Software Development.
  • Military History / Militaries and War Studies