Statistical Approach for Automotive Radar Self-Diagnostics
N Petrov (TU Delft - Microwave Sensing, Signals & Systems)
O. Krasnov (TU Delft - Microwave Sensing, Signals & Systems)
A. Yarovoy (TU Delft - Microwave Sensing, Signals & Systems)
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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.