Advanced driver assistance systems (ADAS) are systems developed to automate/adapt/enhance vehicle systems for safety and better driving. Safety features are designed to avoid collisions and accidents by offering technologies that alert the driver to potential problems or to avoid collisions by implementing safeguards and taking over control of the vehicle. Adaptive features may automate lighting, provide adaptive cruise control, automate braking, incorporate GPS/traffic warnings, connect to smartphones, alert the driver to other cars or dangers, keep the driver in the correct lane, or show what is in blind spots.

Autonomous cars can detect their surroundings using a variety of techniques such as radar. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Among the potential benefits of autonomous cars is a significant reduction in traffic collisions; the resulting injuries; and related costs, including a lower need for insurance. Among the main obstacles and disadvantages due to widespread adoption of autonomous vehicles, in addition to the technological challenges, are disputes concerning liability; the time period needed to turn an existing stock of vehicles from non-autonomous to autonomous; resistance by individuals to forfeit control of their cars; consumer concern about the safety of driverless cars; implementation of legal framework and establishment of government regulations for self-driving cars; risk of loss of privacy and security concerns, such as hackers or terrorism…

To predict certainty in the performance of driverless vehicles, and to ensure safety, automotive companies will have to extend their use of simulation technologies and embrace new ones such as stimulation of real sensor in HIL testing solutions.

The main objectives of radar simulation related to ADAS Systems are:

  • Assessing the performance of radar sensors in their operational environment
  • Assessing the performance of radar sensors in various types of environment
  • Assessing the performance of radar sensors in various types of weather conditions
  • Assessing the performance of radar sensors on various types of platform
  • Replacing expensive, non-flexible and long trials (the usual one million kilometres qualification tests) by cost-effective and flexible simulation.

Technical challenges to be faced in radar sensor simulations

  • Carrier frequency is high: typically, in the mm waveband for radar sensors on vehicles (around 77GHz)
  • Illumination of the scene can be very large due to small antenna size
  • Radar data rate can be very high: typically, up to some kHz
  • For some radar functions, such as Doppler (speed) measurements and angular measurements (subject to Glint effect), RCS is not sufficient
  • Most of the time, coupling (by multiple bounces) between the target and its close environment cannot be neglected.

Combined with a comprehensive software suite dedicated to automotive simulation and a high-fidelity RF scene rendering such as SE-Workbench-RF from OKTAL-SE, the RTS solutions of SYNOPSIS Corporation group are adapted to automotive radar testing in HIL mode. Indeed, our solutions already address radar systems in the W band such as missile seeker. So, our technological bricks are relevant for RF echoes generation at 77GHz, including FMCW type of waveform.

Synopsis Corporation Group has a cooperation with AVSimulation for creating HIL test solutions dedicated to automotive radars.

radar sumilation