Statistical Approach for Automotive Radar Self-Diagnostics

Statistical Approach for Automotive Radar Self-Diagnostics

Petrov, N. (TU Delft Microwave Sensing, Signals & Systems)
Krasnov, O.A. (TU Delft Microwave Sensing, Signals & Systems)
Yarovoy, Alexander (TU Delft Microwave Sensing, Signals & Systems)

2019-10

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.

Automotive Radar
Calibration
Quality of Service
Self-diagnostics

http://resolver.tudelft.nl/uuid:615a1123-64da-4adc-9d04-30b88a0c2e2c

IEEE

2020-05-01

978-1-7281-3733-9

EuRAD 2019 - 2019 16th European Radar Conference

16th European Radar Conference, 2019-10-01 → 2019-10-04, Paris, France

EuRAD 2019 - 2019 16th European Radar Conference

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.

Institutional Repository

conference paper

© 2019 N. Petrov, O.A. Krasnov, Alexander Yarovoy