Narrowband angle of arrival estimation exploiting graph topology and graph signals

Ian K. Proudler; Vladimir Stankovic; Stephan Weiss

doi:10.1109/SSPD47486.2020.9272170

Narrowband angle of arrival estimation exploiting graph topology and graph signals

Ian K. Proudler, Vladimir Stankovic, Stephan Weiss

Electronic And Electrical Engineering

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

13 Citations (Scopus)

45 Downloads (Pure)

Abstract

Based on recent results of applying graph signal processing (GSP) to narrowband angle of arrival estimation for uniform linear arrays, we generalise the analysis to the case of arrays with elements placed arbitrarily in three dimensional space. We comment on the selection of the adjacency matrix, analyse how this new approach compares to the multiple signal classification (MUSIC) algorithm, and provide an efficient implementation. We demonstrate that the GSP approach can perform as well as the MUSIC algorithm in terms of accuracy and computational cost. Simulations indicate that the proposed GSP approach avoids the severe performance degradation with which MUSIC is associated at low signal to noise ratios.

Original language	English
Title of host publication	2020 Sensor Signal Processing for Defence Conference (SSPD)
Place of Publication	Piscataway, NJ.
Publisher	IEEE
Number of pages	5
ISBN (Print)	9781728138114
DOIs	https://doi.org/10.1109/SSPD47486.2020.9272170
Publication status	Published - 30 Nov 2020
Event	International Conference on Sensor Signal Processing for Defence - Edinburgh, United Kingdom Duration: 15 Sept 2020 → 16 Sept 2020 https://sspd.eng.ed.ac.uk/

Conference

Conference	International Conference on Sensor Signal Processing for Defence
Abbreviated title	SSPD
Country/Territory	United Kingdom
City	Edinburgh
Period	15/09/20 → 16/09/20
Internet address	https://sspd.eng.ed.ac.uk/

Keywords

noise ratios
graph topology
arrival estimation techniques

Access to Document

10.1109/SSPD47486.2020.9272170

Proudler-etal-SSPD-2020-Narrowband-angle-of-arrival-estimation-exploiting-graphAccepted author manuscript, 555 KB

Signal Processing in the Information Age (UDRC III)
Weiss, S. (Principal Investigator) & Stankovic, V. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/07/18 → 31/03/24
Project: Research

Cite this

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title = "Narrowband angle of arrival estimation exploiting graph topology and graph signals",

abstract = "Based on recent results of applying graph signal processing (GSP) to narrowband angle of arrival estimation for uniform linear arrays, we generalise the analysis to the case of arrays with elements placed arbitrarily in three dimensional space. We comment on the selection of the adjacency matrix, analyse how this new approach compares to the multiple signal classification (MUSIC) algorithm, and provide an efficient implementation. We demonstrate that the GSP approach can perform as well as the MUSIC algorithm in terms of accuracy and computational cost. Simulations indicate that the proposed GSP approach avoids the severe performance degradation with which MUSIC is associated at low signal to noise ratios.",

keywords = "noise ratios, graph topology, arrival estimation techniques",

author = "Proudler, {Ian K.} and Vladimir Stankovic and Stephan Weiss",

note = "{\textcopyright} 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; International Conference on Sensor Signal Processing for Defence, SSPD ; Conference date: 15-09-2020 Through 16-09-2020",

year = "2020",

month = nov,

day = "30",

doi = "10.1109/SSPD47486.2020.9272170",

language = "English",

isbn = "9781728138114",

booktitle = "2020 Sensor Signal Processing for Defence Conference (SSPD)",

publisher = "IEEE",

url = "https://sspd.eng.ed.ac.uk/",

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Proudler, IK , Stankovic, V & Weiss, S 2020, Narrowband angle of arrival estimation exploiting graph topology and graph signals. in 2020 Sensor Signal Processing for Defence Conference (SSPD)., 9272170, IEEE, Piscataway, NJ., International Conference on Sensor Signal Processing for Defence, Edinburgh, United Kingdom, 15/09/20. https://doi.org/10.1109/SSPD47486.2020.9272170

TY - GEN

T1 - Narrowband angle of arrival estimation exploiting graph topology and graph signals

AU - Proudler, Ian K.

AU - Stankovic, Vladimir

AU - Weiss, Stephan

N1 - © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2020/11/30

Y1 - 2020/11/30

N2 - Based on recent results of applying graph signal processing (GSP) to narrowband angle of arrival estimation for uniform linear arrays, we generalise the analysis to the case of arrays with elements placed arbitrarily in three dimensional space. We comment on the selection of the adjacency matrix, analyse how this new approach compares to the multiple signal classification (MUSIC) algorithm, and provide an efficient implementation. We demonstrate that the GSP approach can perform as well as the MUSIC algorithm in terms of accuracy and computational cost. Simulations indicate that the proposed GSP approach avoids the severe performance degradation with which MUSIC is associated at low signal to noise ratios.

AB - Based on recent results of applying graph signal processing (GSP) to narrowband angle of arrival estimation for uniform linear arrays, we generalise the analysis to the case of arrays with elements placed arbitrarily in three dimensional space. We comment on the selection of the adjacency matrix, analyse how this new approach compares to the multiple signal classification (MUSIC) algorithm, and provide an efficient implementation. We demonstrate that the GSP approach can perform as well as the MUSIC algorithm in terms of accuracy and computational cost. Simulations indicate that the proposed GSP approach avoids the severe performance degradation with which MUSIC is associated at low signal to noise ratios.

KW - noise ratios

KW - graph topology

KW - arrival estimation techniques

U2 - 10.1109/SSPD47486.2020.9272170

DO - 10.1109/SSPD47486.2020.9272170

M3 - Conference contribution book

SN - 9781728138114

BT - 2020 Sensor Signal Processing for Defence Conference (SSPD)

PB - IEEE

CY - Piscataway, NJ.

T2 - International Conference on Sensor Signal Processing for Defence

Y2 - 15 September 2020 through 16 September 2020

ER -

Narrowband angle of arrival estimation exploiting graph topology and graph signals

Abstract

Conference

Keywords

Access to Document

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Projects

Signal Processing in the Information Age (UDRC III)

Cite this