Advanced Signal Processing Strategy for Automotive sensors
2022-01-0087
03/29/2022
- Event
- Content
- As automotive domain is moving from automation to autonomy, advanced signal processing is inevitable for automotive sensors. Signal processing plays a major role by enabling new functionality and better performance. As sensors are becoming more intelligent, there is a need of advanced signal processing to make better decisions and improve the control on vehicle operations. The extraction of information from intricate signals in the presence of noise, generally by conversion of the signals or applying various processing algorithms to enhance signal quality, can be defined as signal processing in very broad sense. This paper aims to deliver strategy of signal processing algorithms which can be applied to various automotive sensors such as Radars, Lidars and Cameras for efficient data processing to extract useful data. This paper provides demonstration of signal processing algorithms applied to real-time problems such as CW doppler radar speed processing to report accurate speed. Ultra-wide band radars are becoming increasingly popular in automotive sensors space. These sensors can have very high range resolution and they can be used to detect objects beyond obstacles like walls / corners. Time frequency analysis of reflected UWB radar signals can be used to extract useful information about the size and shape of objects. These signals can be processed to derive important material properties like moisture content and permittivity of the material. Overall, the signal processing strategy has become need of hour for automotive domain to deliver highly robust performance of the sensors at low cost. The signal processing strategy discussed in this paper can be utilized for innovative and cost competitive sensing solution development for automotive domain.
- Citation
- Koparde, P., and Wagh, R., "Advanced Signal Processing Strategy for Automotive sensors," SAE Technical Paper 2022-01-0087, 2022, .