Cited by 374Radar Systems and Signal ProcessingAdvanced SAR Imaging TechniquesNon-Invasive Vital Sign Monitoring

The Rise of Radar for Autonomous Vehicles: Signal Processing Solutions and Future Research Directions

Bilik, Igal, Longman, Oren, Villeval, Shahar, Tabrikian, Joseph·2019·IEEE Signal Processing Magazine

Abstract

Automotive radar is the most promising and fastest-growing civilian application of radar technology. Vehicular radars provide the key enabling technology for the autonomous driving revolution that will have a dramatic impact on everyone's day-to-day lives. They play a central role in the autonomous sensing suit because of the significant progress in the radio-frequency (RF) CMOS technology that enables high-level radar-on-chip integration and thus reduces the automotive radar cost to the level of consumer mass production. However, this would not be sufficient without high spatial resolution performance, which can be obtained by multiple-input, multiple-output (MIMO) and cognitive approaches at a lower cost. The uniqueness of automotive radar scenarios mandates the formulation and derivation of new signal processing approaches beyond classical military radar concepts. The reformulation of vehicular radar tasks, along with new performance requirements, provides an opportunity to develop innovative signal processing methods. In this article, we first revise conventional techniques for signal processing in automotive radar. Then, we emphasize the limitations of the historically driven conventional processing approaches in practical roadway scenarios and present alternative signal processing solutions. Finally, we propose several future research directions to enhance vehicular radar performance

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Crossref · 10.1109/msp.2019.2926573

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51 of 51 references verified0 citation errors · 0 not checkable

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  • The main obstacle for the automotive RADAR system is to yield high-resolution information in an environment that incorporates several dynamic objects in an immensely clustered automotive scene with a high update rate.

    “However, the main obstacle for the automotive RADAR system is to yield high-resolution information in an environment that incorporates several dynamic objects in an immensely clustered automotive scene with a high update rate [82,83].”

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Authors
Bilik, I., Longman, O., Villeval, S., & Tabrikian, J.
Affiliations
  • Duke University (US)
  • Bar-Ilan University (IL)
  • Ben-Gurion University of the Negev (IL)
Venue
IEEE Signal Processing Magazine
Published
2019-09
Volume
36
Issue
5
Pages
20-31
ISSN
  • 1053-5888 (ISSN-L)
  • 1558-0792
OpenAlex
W2973146207
Cited by
374
References
51
Citations by year
2026: 29 · 2025: 65 · 2024: 67 · 2023: 76 · 2022: 50 · 2021: 56 · 2020: 29 · 2019: 2
FWCI
25.19
Type
journal article
Language
en
Open access
closed
Locations
IEEE Signal Processing Magazine (publishedVersion)
Topics
  • Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
  • Physical Sciences › Engineering › Aerospace Engineering › Advanced SAR Imaging Techniques
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
Keywords
automotive radar, autonomous vehicles, radar signal processing, MIMO radar, cognitive radar, spatial resolution, vehicular sensing

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