A novel W-MUSIC algorithm for GPR target detection in noisy and distorted signals

J Wei, Stephen R Pennock, Peter R Shepherd

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

When applied to ground penetrating radar (GPR), the multiple signal classification (MUSIC) algorithm is an important frequency estimation method as it can detect very closely spaced targets, particularly when one of the target responses is substantially less than another. The MUSIC algorithm however must be seeded with the number of targets to find and will indicate that number of targets regardless of the number of targets actually present. In addition, there is no reliable indication of the magnitude of the responses of the targets. In the presence of relatively low levels of noise the MUSIC algorithm is prone to reporting the position of false target positions in preference to weaker genuine target responses. In this paper a superimposed MUSIC technique is proposed to suppress false targets. A novel windowed FFT MUSIC (W-MUSIC) algorithm is examined using a linear sweep frequency in noise, and it is seen to give a clear indication of targets. In the presence of distortion, FFT is seen to be a more robust approach than the MUSIC algorithm, the latter method becoming very prone to inaccuracy in the presence of distortion.
Original languageEnglish
Title of host publication2009 IEEE Radar Conference
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781424428717
ISBN (Print)9781424428700
DOIs
Publication statusPublished - 2009
Event2009 IEEE Radar Conference - Pasadena, California, USA United States
Duration: 4 May 20098 May 2009

Conference

Conference2009 IEEE Radar Conference
CountryUSA United States
CityPasadena, California
Period4/05/098/05/09

Keywords

  • windowed FFT MUSIC
  • suppress false targets
  • GPR target detection
  • W-MUSIC algorithm
  • object detection
  • frequency estimation
  • linear sweep frequency
  • ground penetrating radar
  • multiple signal classification
  • distorted signals
  • signal classification
  • noisy signals

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