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Physics-Based, Real-Time MIMO Radar Simulation for Autonomous Driving

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Automatisiertes Fahren 2021

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Abstract

Advanced driver assistance systems (ADAS) and autonomous vehicles (AV) require massive amounts of sensor data to test and train driving algorithms and to design sensor hardware. In many practical cases, these data must be generated at or beyond real-time rates of up to 30 sensor frames per second (fps). General-purpose, high-fidelity radar response simulators can take minutes or hours to simulate a single coherent processing interval (CPI) comprised of hundreds of radar chirps over many MIMO channels. This paper presents an end-to-end GPU implementation of the shooting and bouncing rays (SBR) method combined with algorithmic accelerations to achieve over 160 fps for a single-channel radar operating in a realistically complex traffic environment and sustained real-time performance for five single-channel radars or one 2 0 - channel radar. In addition, this paper illustrates, using open and standardized interfaces, the integration of this technology in closed loop simulation.

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References

  1. Waymo (2020) “Off road, but not offline: How simulation helps advance our Waymo Driver”. [Online]. Available: https://blog.waymo.com/2020/04/off-road-but-not-offline-- simulation27.html

  2. Ansys (2021) “Ansys HFSS: High Frequency Electromagnetic Field Simulation Software”. [Online]. Available: https://www.ansys.com/products/electronics/ansys-hfss

  3. NVIDIA (2020) “CUDA C++ Programming Guide”. [Online]. Available: https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html

  4. H. Ling, R.-C. Chou and S.-W. Lee, "Shooting and bouncing rays: calculating the RCS of an arbitrarily shaped cavity," IEEE Trans. Antennas Propagat., vol. 37, no. 2, pp. 194-205, Feb. 1989, doi: https://doi.org/10.1109/8.18706.

  5. S-K Jeng, “Near-field scattering by physical theory of diffraction and shooting and bouncing rays,” IEEE Trans. Antennas Propagat., vol. 46., no. 4, pp. 551 -558, Apr. 1998.

    Google Scholar 

  6. U. Chipengo, A. Sligar and S. Carpenter, "High Fidelity Physics Simulation of 128 Channel MIMO Sensor for 77GHz Automotive Radar," in IEEE Access, vol. 8, pp. 160643 - 160652, 2020, doi: https://doi.org/10.1109/ACCESS.2020.3021362.

  7. S. Parker, J. Bigler, A. Dietrich, H. Friedrich, J. Hoberock, D. Luebke, D. McAllister, M. McGuire, K. Morley, A. Robison, and M. Stich, "OptiX™: A General Purpose Ray Tracing Engine," ACM Transactions on Graphics, vol. 29, no. 4, July 2010, doi: https://doi.org/10.1145/1778765.1778803.

  8. NVIDIA (2020) “cuFFT Library User’s Guide”. [Online]. Available: https://docs.nvidia.com/cuda/cufft/index.html

  9. Hanke, T., Hirsenkorn, N., van-Driesten, C., Garcia-Ramos, P., Schiementz, M., Schneider, S. & Biebl, E. (2017, February 03). A generic interface for the environment perception of automated driving functions in virtual scenarios. Retrieved January 25, 2020, from https://www.hot.ei.tum.de/forschung/automotive-veroeffentlichungen/

  10. ISO 23150, https://www.iso.org/standard/74741.html.

  11. OpenSimulationInterface, https://github.com/OpenSimulationInterface/open -simulationinterface.

  12. Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, Vladlen Koltun; PMLR 78:1-16. CARLA: An Open Urban Driving Simulator.

    Google Scholar 

  13. ZeroMQ, https://zeromq.org/

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© 2021 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Decker, J., Saad, K., Rey, D., Canta, S.M., Kipp, R.A. (2021). Physics-Based, Real-Time MIMO Radar Simulation for Autonomous Driving. In: Bertram, T. (eds) Automatisiertes Fahren 2021. Proceedings. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-34754-3_7

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