Statistical signal processing for detection of buried landmines using quadrupole resonance

Feng Liu; Stacy Tantum; Leslie Collins; Lawrence Carin

doi:10.1117/12.396285

Statistical signal processing for detection of buried landmines using quadrupole resonance

Feng Liu, Stacy Tantum, Leslie Collins, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Quadrupole resonance (QR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives. However, explosives detection via QR is complicated by several issues. This article discusses several signal processing tools developed to further enhance the utility of QR explosives (mine) detection. In particular, with regard to the uncertainties concerning the background environment and sensor height, statistical signal processing strategies are explored to rigorously account for the inherent variability in these parameters.

Original language	English (US)
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Publisher	Society of Photo-Optical Instrumentation EngineersBellingham
Pages	572-577
Number of pages	6
DOIs	https://doi.org/10.1117/12.396285
State	Published - Jan 1 2000
Externally published	Yes

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Generated from Scopus record by KAUST IRTS on 2021-02-09

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10.1117/12.396285

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@inproceedings{1d89db9539774622a57226af1076ad62,

title = "Statistical signal processing for detection of buried landmines using quadrupole resonance",

abstract = "Quadrupole resonance (QR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives. However, explosives detection via QR is complicated by several issues. This article discusses several signal processing tools developed to further enhance the utility of QR explosives (mine) detection. In particular, with regard to the uncertainties concerning the background environment and sensor height, statistical signal processing strategies are explored to rigorously account for the inherent variability in these parameters.",

author = "Feng Liu and Stacy Tantum and Leslie Collins and Lawrence Carin",

note = "Generated from Scopus record by KAUST IRTS on 2021-02-09",

year = "2000",

month = jan,

day = "1",

doi = "10.1117/12.396285",

language = "English (US)",

pages = "572--577",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

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Statistical signal processing for detection of buried landmines using quadrupole resonance. / Liu, Feng; Tantum, Stacy; Collins, Leslie et al.
Proceedings of SPIE - The International Society for Optical Engineering. Society of Photo-Optical Instrumentation EngineersBellingham, 2000. p. 572-577.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Statistical signal processing for detection of buried landmines using quadrupole resonance

AU - Liu, Feng

AU - Tantum, Stacy

AU - Collins, Leslie

AU - Carin, Lawrence

N1 - Generated from Scopus record by KAUST IRTS on 2021-02-09

PY - 2000/1/1

Y1 - 2000/1/1

N2 - Quadrupole resonance (QR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives. However, explosives detection via QR is complicated by several issues. This article discusses several signal processing tools developed to further enhance the utility of QR explosives (mine) detection. In particular, with regard to the uncertainties concerning the background environment and sensor height, statistical signal processing strategies are explored to rigorously account for the inherent variability in these parameters.

AB - Quadrupole resonance (QR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives. However, explosives detection via QR is complicated by several issues. This article discusses several signal processing tools developed to further enhance the utility of QR explosives (mine) detection. In particular, with regard to the uncertainties concerning the background environment and sensor height, statistical signal processing strategies are explored to rigorously account for the inherent variability in these parameters.

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UR - http://www.scopus.com/inward/record.url?scp=0033686270&partnerID=8YFLogxK

U2 - 10.1117/12.396285

DO - 10.1117/12.396285

M3 - Conference contribution

SP - 572

EP - 577

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Society of Photo-Optical Instrumentation EngineersBellingham

ER -

Statistical signal processing for detection of buried landmines using quadrupole resonance

Abstract

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