Statistical Approach for Automotive Radar Self-Diagnostics

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Abstract

In this paper, the problem of on-the-fly estimation of the radar state (self-diagnostics) is considered. We propose to use repetitive objects of the road infrastructure, such as lampposts, for continuous diagnostics of the radar state. The selected approach allows accounting for the external factors, such as water layer or dirt on the bumper, which can significantly affect radar performance, but cannot be retrieved with the internal calibration. The statistical model for RCS of repetitive targets is considered, and the estimator of the actual radar gain from the received data is derived. It is demonstrated that observing a few tens of targets is sufficient to provide a reasonable estimation of the radar performance within the operational mode.

Original languageEnglish
Title of host publicationEuRAD 2019 - 2019 16th European Radar Conference
PublisherIEEE
Pages117-120
Number of pages4
ISBN (Electronic)978-2-87487-057-6
ISBN (Print)978-1-7281-3733-9
Publication statusPublished - Oct 2019
Event16th European Radar Conference: in the framework of the European Microwave Week 2019 - Paris, France
Duration: 1 Oct 20194 Oct 2019
https://www.eumweek.com/conferences/eurad.html

Publication series

NameEuRAD 2019 - 2019 16th European Radar Conference

Conference

Conference16th European Radar Conference
Abbreviated titleEuRAD 2019
Country/TerritoryFrance
CityParis
Period1/10/194/10/19
Internet address

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

  • Automotive Radar
  • Calibration
  • Quality of Service
  • Self-diagnostics

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