Test Radar-based Autonomous Driving Features with the Radar Scene Emulator

Achieving the next level in vehicle autonomy demands robust algorithms trained to interpret radar reflections detected by automotive radar sensors. Keysight’s first-to-market technology combines hundreds of miniature radar target simulators into a scalable screen that can emulate objects with up to 512-pixel resolution and at distances as close as 1.5 meters. This breakthrough radar scene emulation solution overcomes conventional radar sensor test solutions that have a limited field-of-view (FOV) and cannot simulate objects at distances less than 4 meters.

• Utilizing “total scene generation”, the radar scene emulation solution exercises your automated drive systems and algorithms by applying time-synchronized inputs to the actual sensors. Its open architecture also closes the loop with your existing hardware-in-the-loop (HIL) systems and 3D modelers. These capabilities create a solution that complements—and fills the gap between—software simulation and on-road testing. As such, it overcomes limitations of software simulation that does not test real radar sensor response, while achieving repeatable testing of radar scenes, which cannot be done on the test track.
• The Radar Scene Emulator allows you to emulate real-world driving scenarios, varying speed, distance, and number of targets, across a contiguous FOV. With radar sensors and back-end software confidently tested against the complexity of real-world driving scenarios, you’ll achieve your vision of ADAS and next-generation vehicle autonomy sooner, with less risk.
• In-lab full radar scene emulation
• Thoroughly exercise radar sensors and systems with up to 512-pixel resolution a contiguous horizontal FOV of ±70 degrees and vertical ±15 degrees
• Supports short, medium, and long-range mmWave radars by generating static and dynamic targets at ranges of 1.5 meters to 300 meters and with velocities of 0 to 400 km/h
• Address multi-target, multi-angle scenarios with mechanically fixed RF Front ends that provide repeatable angle of arrival (AoA) accuracy
• Emulate complex, RF-dense urban scenes with realistic interference testing
• Using 3D point clouds and multiple reflections allows for improved detection and differentiation of objects