Intelligent Transport Systems, From Research and Development to the Market Uptake. 4th EAI International Conference, INTSYS 2020, Virtual Event, December 3, 2020, Proceedings

Research Article

Automotive Radar Signal and Interference Simulation for Testing Autonomous Driving

  • @INPROCEEDINGS{10.1007/978-3-030-71454-3_14,
        author={Alexander Prinz and Leo-Tassilo Peters and Johannes Schwendner and Mohamed Ayeb and Ludwig Brabetz},
        title={Automotive Radar Signal and Interference Simulation for Testing Autonomous Driving},
        proceedings={Intelligent Transport Systems, From Research and Development to the Market Uptake. 4th EAI International Conference, INTSYS 2020, Virtual Event, December 3, 2020, Proceedings},
        proceedings_a={INTSYS},
        year={2021},
        month={7},
        keywords={Driver assistance Automotive radar Radar interference Sensor modelling Sensor model validation Testing process},
        doi={10.1007/978-3-030-71454-3_14}
    }
    
  • Alexander Prinz
    Leo-Tassilo Peters
    Johannes Schwendner
    Mohamed Ayeb
    Ludwig Brabetz
    Year: 2021
    Automotive Radar Signal and Interference Simulation for Testing Autonomous Driving
    INTSYS
    Springer
    DOI: 10.1007/978-3-030-71454-3_14
Alexander Prinz1, Leo-Tassilo Peters1, Johannes Schwendner2, Mohamed Ayeb3, Ludwig Brabetz3
  • 1: Bayerische Motoren Werke AG
  • 2: Expleo Germany GmbH
  • 3: Universität Kassel

Abstract

With the development of automated driving functions, more and more environmental sensors are combined for the vehicle perception. A problem that arises with the extensive use of radar sensing is called interference. It describes the confounding effects from the wave overlay of two or more radar sensors operating in the same frequency-band. At this point, methods for interference avoidance and mitigation come to apply. For a valid design and development of such methods, real sensor measurements were required in the past. This publication instead proposes a novel sensor modelling technique that represents the interference mechanisms within the radar sensor signals. It is based on a full radar time signal simulation coupled with a broad range of influencing factors. The concept is validated by comparing the simulated signal processing steps to the real sensor measurement behavior. As a result, mitigation methods for the sensor fault behavior can be fully assessed within a simulation environment. The opportunity for applying new scenario data and a variable set of radar sensors underlines the importance of this approach in the development of future radar systems.