MIMO Radar Hardware Acceleration with Enhanced Resolution

This paper proposes a method for accelerating an enhanced resolution 3D (range, velocity, and azimuth) Multiple Input Multiple Output (MIMO) radar on a Graphics Processing Unit (GPU). Implementation of MIMO radars and the investigation of their performance are of interest to the research community....

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Main Authors: Pitre Eric, Roberge Vincent, Bray Joey, Hefnawi Mostafa
Format: Article
Language:English
Published: EDP Sciences 2022-01-01
Series:ITM Web of Conferences
Online Access:https://www.itm-conferences.org/articles/itmconf/pdf/2022/08/itmconf_iccwcs2022_01013.pdf
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author Pitre Eric
Roberge Vincent
Bray Joey
Hefnawi Mostafa
author_facet Pitre Eric
Roberge Vincent
Bray Joey
Hefnawi Mostafa
author_sort Pitre Eric
collection DOAJ
description This paper proposes a method for accelerating an enhanced resolution 3D (range, velocity, and azimuth) Multiple Input Multiple Output (MIMO) radar on a Graphics Processing Unit (GPU). Implementation of MIMO radars and the investigation of their performance are of interest to the research community. However, the MIMO mode of operation increases the computational requirements of the radar system and seldom permits real-time operation without performance compromises. Current methods for achieving reasonable frame rates include reducing the scope of the radar (i.e., limiting the number of dimensions, the field of view, or the ranges of interest), choosing efficient but coarse algorithms (i.e., the FFT for range, velocity, and bearing estimation), or offloading the computation on task specific hardware, DSP, or FPGA. The proposed framework enables real-time operation of the MIMO radar by performing the signal processing on a GPU without compromising the radar coverage, while replacing the widely used 3D FFT with an enhanced resolution alternative. The proposed framework is tested on a Frequency Modulated Continuous Wave (FMCW) MIMO radar using 8 transmitters, 8 receivers, and having a Coherent Processing Interval (CPI) of 256 chirps. The parallel implementation of the enhanced resolution signal processing yields an acceleration of 453.6x when compared to sequential execution on CPU.
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spelling doaj.art-b35933cbefc8446e83f652f447df8ddd2022-12-22T03:49:58ZengEDP SciencesITM Web of Conferences2271-20972022-01-01480101310.1051/itmconf/20224801013itmconf_iccwcs2022_01013MIMO Radar Hardware Acceleration with Enhanced ResolutionPitre Eric0Roberge Vincent1Bray Joey2Hefnawi Mostafa3Royal Military College of Canada, Department of Electrical and Computer EngineeringRoyal Military College of Canada, Department of Electrical and Computer EngineeringRoyal Military College of Canada, Department of Electrical and Computer EngineeringRoyal Military College of Canada, Department of Electrical and Computer EngineeringThis paper proposes a method for accelerating an enhanced resolution 3D (range, velocity, and azimuth) Multiple Input Multiple Output (MIMO) radar on a Graphics Processing Unit (GPU). Implementation of MIMO radars and the investigation of their performance are of interest to the research community. However, the MIMO mode of operation increases the computational requirements of the radar system and seldom permits real-time operation without performance compromises. Current methods for achieving reasonable frame rates include reducing the scope of the radar (i.e., limiting the number of dimensions, the field of view, or the ranges of interest), choosing efficient but coarse algorithms (i.e., the FFT for range, velocity, and bearing estimation), or offloading the computation on task specific hardware, DSP, or FPGA. The proposed framework enables real-time operation of the MIMO radar by performing the signal processing on a GPU without compromising the radar coverage, while replacing the widely used 3D FFT with an enhanced resolution alternative. The proposed framework is tested on a Frequency Modulated Continuous Wave (FMCW) MIMO radar using 8 transmitters, 8 receivers, and having a Coherent Processing Interval (CPI) of 256 chirps. The parallel implementation of the enhanced resolution signal processing yields an acceleration of 453.6x when compared to sequential execution on CPU.https://www.itm-conferences.org/articles/itmconf/pdf/2022/08/itmconf_iccwcs2022_01013.pdf
spellingShingle Pitre Eric
Roberge Vincent
Bray Joey
Hefnawi Mostafa
MIMO Radar Hardware Acceleration with Enhanced Resolution
ITM Web of Conferences
title MIMO Radar Hardware Acceleration with Enhanced Resolution
title_full MIMO Radar Hardware Acceleration with Enhanced Resolution
title_fullStr MIMO Radar Hardware Acceleration with Enhanced Resolution
title_full_unstemmed MIMO Radar Hardware Acceleration with Enhanced Resolution
title_short MIMO Radar Hardware Acceleration with Enhanced Resolution
title_sort mimo radar hardware acceleration with enhanced resolution
url https://www.itm-conferences.org/articles/itmconf/pdf/2022/08/itmconf_iccwcs2022_01013.pdf
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AT hefnawimostafa mimoradarhardwareaccelerationwithenhancedresolution