Design and simulation of automotive radar for autonomous vehicles

Abstract

Modern automobile technology is pushing towards maximizing road safety, connected vehicles, autonomous vehicles, etc. Automotive RADAR is core sensor technology used for ADAS (Advanced Driver Assistance Technology), ACC (Adaptive Cruise Control), AEB (Automatic Emergency Braking System), traffic assistance, parking aid, and obstacle/pedestrian detection. Despite being inexpensive, RADAR technology provides robust results in harsh conditions such as harsh weather, extreme temperature, darkness, etc. However, the performance of these systems depends on the position of the RADAR and its characteristics like frequency, beamwidth, and bandwidths. Moreover, the characterization of varied materials like layers of paint, polish, primer, or layer of rainwater needs to be analyzed. This performance can be predicted through real-time simulation using advanced FEM software like Altair FEKO&WinProp. These simulations can provide valuable insight into the performance of the system, allowing engineers to optimize the system for specific use cases. For example, simulation can be used to determine the optimal parameters of the RADAR system for a given application. This information can then be used to design and build a physical model or prototype that is optimized for the desired performance. These simulations play a prominent role in determining appropriate data collection and sensor fusion, which reduces the cost and time required for the development of a physical model or prototype. The continued growth and demand for advanced safety features in vehicles further highlight the importance of RADAR technology in modern automobile technology. By accurately characterizing the environment and simulating the system's behavior in real time, engineers can optimize RADAR systems for specific use cases, contributing to safer and more efficient driving experiences