Fusion of Data from Multiple Automotive Radars for High-Resolution DoA Estimation

Anusha Ravish  Suvarna; Arie  Koppelaar; Feike Jansen; Jianping Wang; Alexander Yarovoy

doi:10.1109/RadarConf2248738.2022.9764277

Fusion of Data from Multiple Automotive Radars for High-Resolution DoA Estimation

Anusha Ravish Suvarna, Arie Koppelaar, Feike Jansen, Jianping Wang, Alexander Yarovoy

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this problem, we propose a high-resolution Direction of Arrival (DoA) estimation by using multiple small radar sensors distributed on the fascia of the automobile. To exploit the diversity gain due to different target observation angles by different radars, a block Focal Under determined System Solver based approach is proposed to incoherently fuse the data from multiple small MIMO sensors. This method significantly improves the DoA estimation compared to single sensor, decreases probability of false alarm and increases probability of multiple target detection. Its performance is demonstrated through both numerical simulations and experimental results.

Original language	English
Title of host publication	2022 IEEE Radar Conference (RadarConf22) Proceedings
Place of Publication	Piscataway
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	978-1-7281-5368-1
ISBN (Print)	978-1-7281-5369-8
DOIs	https://doi.org/10.1109/RadarConf2248738.2022.9764277
Publication status	Published - 2022
Event	2022 IEEE Radar Conference - New York City, United States Duration: 21 Mar 2022 → 25 Mar 2022

Conference

Conference	2022 IEEE Radar Conference
Abbreviated title	RadarConf22
Country/Territory	United States
City	New York City
Period	21/03/22 → 25/03/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Compressive Sensing (CS)
FOCUSS
Block sparsity
distributed radar
MIMO
automotive radar
OMP
BOMP
incoherent processing
ambiguity function
single snap-shot
DoA estimation

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Fusion_of_Data_from_Multiple_Automotive_Radars_for_High-Resolution_DoA_EstimationFinal published version, 1.8 MB

Cite this

@inproceedings{a57ebb9511d04d778d4c279a6810d972,

title = "Fusion of Data from Multiple Automotive Radars for High-Resolution DoA Estimation",

abstract = "High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this problem, we propose a high-resolution Direction of Arrival (DoA) estimation by using multiple small radar sensors distributed on the fascia of the automobile. To exploit the diversity gain due to different target observation angles by different radars, a block Focal Under determined System Solver based approach is proposed to incoherently fuse the data from multiple small MIMO sensors. This method significantly improves the DoA estimation compared to single sensor, decreases probability of false alarm and increases probability of multiple target detection. Its performance is demonstrated through both numerical simulations and experimental results.",

keywords = "Compressive Sensing (CS), FOCUSS, Block sparsity, distributed radar, MIMO, automotive radar, OMP, BOMP, incoherent processing, ambiguity function, single snap-shot, DoA estimation",

author = "Suvarna, {Anusha Ravish} and Arie Koppelaar and Feike Jansen and Jianping Wang and Alexander Yarovoy",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2022 IEEE Radar Conference <br/>, RadarConf22 ; Conference date: 21-03-2022 Through 25-03-2022",

year = "2022",

doi = "10.1109/RadarConf2248738.2022.9764277",

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AU - Suvarna, Anusha Ravish

AU - Koppelaar, Arie

AU - Jansen, Feike

AU - Wang, Jianping

AU - Yarovoy, Alexander

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2022

Y1 - 2022

N2 - High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this problem, we propose a high-resolution Direction of Arrival (DoA) estimation by using multiple small radar sensors distributed on the fascia of the automobile. To exploit the diversity gain due to different target observation angles by different radars, a block Focal Under determined System Solver based approach is proposed to incoherently fuse the data from multiple small MIMO sensors. This method significantly improves the DoA estimation compared to single sensor, decreases probability of false alarm and increases probability of multiple target detection. Its performance is demonstrated through both numerical simulations and experimental results.

AB - High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this problem, we propose a high-resolution Direction of Arrival (DoA) estimation by using multiple small radar sensors distributed on the fascia of the automobile. To exploit the diversity gain due to different target observation angles by different radars, a block Focal Under determined System Solver based approach is proposed to incoherently fuse the data from multiple small MIMO sensors. This method significantly improves the DoA estimation compared to single sensor, decreases probability of false alarm and increases probability of multiple target detection. Its performance is demonstrated through both numerical simulations and experimental results.

KW - Compressive Sensing (CS)

KW - FOCUSS

KW - Block sparsity

KW - distributed radar

KW - MIMO

KW - automotive radar

KW - OMP

KW - BOMP

KW - incoherent processing

KW - ambiguity function

KW - single snap-shot

KW - DoA estimation

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U2 - 10.1109/RadarConf2248738.2022.9764277

DO - 10.1109/RadarConf2248738.2022.9764277

M3 - Conference contribution

SN - 978-1-7281-5369-8

BT - 2022 IEEE Radar Conference (RadarConf22) Proceedings

PB - IEEE

CY - Piscataway

T2 - 2022 IEEE Radar Conference <br/>

Y2 - 21 March 2022 through 25 March 2022

ER -

Fusion of Data from Multiple Automotive Radars for High-Resolution DoA Estimation

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Bibliographical note

Keywords

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