Sparse arrays, MIMO, and compressive sensing for GMTI radar

Haley H. Kim; Alexander M. Haimovich; Mark A. Govoni

doi:10.1109/ACSSC.2014.7094571

Sparse arrays, MIMO, and compressive sensing for GMTI radar

Haley H. Kim, Alexander M. Haimovich, Mark A. Govoni

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

4 Scopus citations

Abstract

This work proposes a radar combining four synergistic elements: space-time adaptive processing (STAP), random arrays, multiple-input multiple-output (MIMO) radar, and compressive sensing. STAP supports joint space-time processing for detecting moving targets in ground clutter. Large, random arrays are undersampled arrays that support improved angle-Doppler resolution and lower minimum detectable velocity (MDV), at the cost of higher sidelobes. MIMO provides further improvements in angular resolution and MDV. Compressive sensing algorithms are designed to cope with ambiguities introduced by undersampling. We propose an algorithm for target detection and analyze its performance for detecting, slow ground targets.

Original language	English (US)
Title of host publication	Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	849-853
Number of pages	5
ISBN (Electronic)	9781479982974
DOIs	https://doi.org/10.1109/ACSSC.2014.7094571
State	Published - Apr 24 2015
Event	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: Nov 2 2014 → Nov 5 2014

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2015-April
ISSN (Print)	1058-6393

Other

Other	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/Territory	United States
City	Pacific Grove
Period	11/2/14 → 11/5/14

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2014.7094571

Cite this

Kim, H. H., Haimovich, A. M., & Govoni, M. A. (2015). Sparse arrays, MIMO, and compressive sensing for GMTI radar. In M. B. Matthews (Ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers (pp. 849-853). Article 7094571 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2014.7094571

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title = "Sparse arrays, MIMO, and compressive sensing for GMTI radar",

abstract = "This work proposes a radar combining four synergistic elements: space-time adaptive processing (STAP), random arrays, multiple-input multiple-output (MIMO) radar, and compressive sensing. STAP supports joint space-time processing for detecting moving targets in ground clutter. Large, random arrays are undersampled arrays that support improved angle-Doppler resolution and lower minimum detectable velocity (MDV), at the cost of higher sidelobes. MIMO provides further improvements in angular resolution and MDV. Compressive sensing algorithms are designed to cope with ambiguities introduced by undersampling. We propose an algorithm for target detection and analyze its performance for detecting, slow ground targets.",

author = "Kim, {Haley H.} and Haimovich, {Alexander M.} and Govoni, {Mark A.}",

year = "2015",

month = apr,

day = "24",

doi = "10.1109/ACSSC.2014.7094571",

language = "English (US)",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

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editor = "Matthews, {Michael B.}",

booktitle = "Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers",

address = "United States",

note = "48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 ; Conference date: 02-11-2014 Through 05-11-2014",

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Kim, HH, Haimovich, AM & Govoni, MA 2015, Sparse arrays, MIMO, and compressive sensing for GMTI radar. in MB Matthews (ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers., 7094571, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2015-April, IEEE Computer Society, pp. 849-853, 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, United States, 11/2/14. https://doi.org/10.1109/ACSSC.2014.7094571

Sparse arrays, MIMO, and compressive sensing for GMTI radar. / Kim, Haley H.; Haimovich, Alexander M.; Govoni, Mark A.
Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers. ed. / Michael B. Matthews. IEEE Computer Society, 2015. p. 849-853 7094571 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April).

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

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AB - This work proposes a radar combining four synergistic elements: space-time adaptive processing (STAP), random arrays, multiple-input multiple-output (MIMO) radar, and compressive sensing. STAP supports joint space-time processing for detecting moving targets in ground clutter. Large, random arrays are undersampled arrays that support improved angle-Doppler resolution and lower minimum detectable velocity (MDV), at the cost of higher sidelobes. MIMO provides further improvements in angular resolution and MDV. Compressive sensing algorithms are designed to cope with ambiguities introduced by undersampling. We propose an algorithm for target detection and analyze its performance for detecting, slow ground targets.

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Sparse arrays, MIMO, and compressive sensing for GMTI radar

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