Direction estimation using compressive sampling array processing

Ying Wang; Geert Leus; Ashish Pandharipande

doi:10.1109/SSP.2009.5278497

Direction estimation using compressive sampling array processing

Ying Wang, Geert Leus, Ashish Pandharipande

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

136 Citations (Scopus)

Abstract

We propose a new architecture, the compressive sampling (CS) array, for array based applications, by exploiting compressive sampling in the spatial domain. With random projections (or selections) of the array elements, we can transform a large size array into a small size array. We also propose two approaches of direction-of-arrival (DoA) estimation using our CS array, I. (joint) CS recovery, and II. CS beamformers. As a result we can greatly reduce the hardware complexity and software complexity while still maintaining the high resolution achieved as if a large size array were used.

Original language	English
Title of host publication	2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09
Publisher	Institute of Electrical and Electronics Engineers
Pages	626-629
Number of pages	4
ISBN (Electronic)	978-1-4244-2711-6
ISBN (Print)	978-1-4244-2709-3
DOIs	https://doi.org/10.1109/SSP.2009.5278497
Publication status	Published - 2009
Externally published	Yes
Event	2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP 2009) - Cardiff, United Kingdom Duration: 31 Aug 2009 → 3 Sept 2009

Conference

Conference	2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP 2009)
Country/Territory	United Kingdom
City	Cardiff
Period	31/08/09 → 3/09/09

Keywords

Beamforming
Compressive sampling
Direction-of-arrival estimation

Access to Document

10.1109/SSP.2009.5278497

Cite this

@inproceedings{f9cb5a6a21e749f581222d7d4cf00eaf,

title = "Direction estimation using compressive sampling array processing",

abstract = "We propose a new architecture, the compressive sampling (CS) array, for array based applications, by exploiting compressive sampling in the spatial domain. With random projections (or selections) of the array elements, we can transform a large size array into a small size array. We also propose two approaches of direction-of-arrival (DoA) estimation using our CS array, I. (joint) CS recovery, and II. CS beamformers. As a result we can greatly reduce the hardware complexity and software complexity while still maintaining the high resolution achieved as if a large size array were used.",

keywords = "Beamforming, Compressive sampling, Direction-of-arrival estimation",

author = "Ying Wang and Geert Leus and Ashish Pandharipande",

year = "2009",

doi = "10.1109/SSP.2009.5278497",

language = "English",

isbn = "978-1-4244-2709-3",

pages = "626--629",

booktitle = "2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP 2009) ; Conference date: 31-08-2009 Through 03-09-2009",

}

Wang, Y, Leus, G & Pandharipande, A 2009, Direction estimation using compressive sampling array processing. in 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09., 5278497, Institute of Electrical and Electronics Engineers, pp. 626-629, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP 2009), Cardiff, United Kingdom, 31/08/09. https://doi.org/10.1109/SSP.2009.5278497

Direction estimation using compressive sampling array processing. / Wang, Ying; Leus, Geert; Pandharipande, Ashish.

2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09. Institute of Electrical and Electronics Engineers, 2009. p. 626-629 5278497.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Direction estimation using compressive sampling array processing

AU - Wang, Ying

AU - Leus, Geert

AU - Pandharipande, Ashish

PY - 2009

Y1 - 2009

N2 - We propose a new architecture, the compressive sampling (CS) array, for array based applications, by exploiting compressive sampling in the spatial domain. With random projections (or selections) of the array elements, we can transform a large size array into a small size array. We also propose two approaches of direction-of-arrival (DoA) estimation using our CS array, I. (joint) CS recovery, and II. CS beamformers. As a result we can greatly reduce the hardware complexity and software complexity while still maintaining the high resolution achieved as if a large size array were used.

AB - We propose a new architecture, the compressive sampling (CS) array, for array based applications, by exploiting compressive sampling in the spatial domain. With random projections (or selections) of the array elements, we can transform a large size array into a small size array. We also propose two approaches of direction-of-arrival (DoA) estimation using our CS array, I. (joint) CS recovery, and II. CS beamformers. As a result we can greatly reduce the hardware complexity and software complexity while still maintaining the high resolution achieved as if a large size array were used.

KW - Beamforming

KW - Compressive sampling

KW - Direction-of-arrival estimation

UR - http://www.scopus.com/inward/record.url?scp=72349097493&partnerID=8YFLogxK

U2 - 10.1109/SSP.2009.5278497

DO - 10.1109/SSP.2009.5278497

M3 - Conference contribution

AN - SCOPUS:72349097493

SN - 978-1-4244-2709-3

SP - 626

EP - 629

BT - 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09

PB - Institute of Electrical and Electronics Engineers

T2 - 2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP 2009)

Y2 - 31 August 2009 through 3 September 2009

ER -

Direction estimation using compressive sampling array processing

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this