Adaptive MEMS Mirror Control for Reliable Automotive Driving Assistance Applications

Abstract

A continuously growing interest towards autonomous vehicles highlights the need of robust sensors that will reliably operate under harsh environmental conditions. In this paper, we analyze environmental disturbances that influence the optical sensing accuracy of a MEMS-based LiDAR (Light Detection and Ranging) sensor, and propose an adaptive control scheme of the MEMS mirror that lower the impact of disturbances on the sensing accuracy. This scheme exploits data from various internal and external monitors and adapts MEMS mirror control parameters such that the angular RMS jitter does not exceed 15m° when environmental conditions change. Measurement results show that this approach not only introduces robustness in the MEMS mirror control loop but also improves overall reliability of ADAS applications.