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ON Semiconductor to demonstrate long-range and in-vehicle automotive imaging and detection technology at CES 2020

Latest LiDAR technology sets new performance standards in photon detection efficiency (PDE) and image resolution

Latest LiDAR technology sets new performance standards in photon detection efficiency (PDE) and image resolution

ON Semiconductor (Nasdaq: ON), driving energy efficient innovations, will have its latest LiDAR technology front-and-center among the company’s automotive solutions at CES 2020. Recognized as a leading provider of detectors for LiDAR, the company will demonstrate the industry’s first, high-resolution, wide field-of-view (FoV) Single Photon avalanche diode (SPAD) array family designed for short-, mid- and long-range LiDAR applications.

SPAD arrays are low-light photon detectors that produce simultaneous monochromatic images and depth maps of a scene, making them ideal for time-of-flight (ToF) applications. Low density versions of the technology have been used in consumer applications, but these devices do not work beyond 2 meters and are not reliable enough in bright lighting conditions. The new devices are far more flexible and can be used with a variety of scene illumination architectures for ToF including scanning and flash. An evaluation kit featuring the new technology will be showcased during CES 2020.

ON Semiconductor’s SPAD-based silicon photomultiplier (SiPM) technology is the detector of choice in the LiDAR industry due to its single photon sensitivity, high gain and photon detection efficiency, and high manufacturing uniformity compared to legacy detectors like avalanche photodiodes (APD). Multiple LiDAR sensor manufacturers will showcase products enabled by ON Semiconductor SiPM detectors at CES 2020, including the CES Innovation Award-winning RS-LiDAR-M1 from RoboSense.

“The CES 2020 award winning RS-LiDAR-M1 offers excellent range, accuracy, and market leading price/performance in an automotive qualified design,” said Dr. Leilei Shinohara, RoboSense Co-Partner and Vice President. “By working with ON Semiconductor and utilizing the RD-Series SiPM family we have quickly moved past the performance offered by legacy LiDAR manufacturers using older APD technology and mechanical scanning architectures. ON Semiconductor’s SiPM detector technology enabled the desired LiDAR performance.”

“SiPMs are quickly displacing APDs in solid-state LiDAR systems at the near-infrared (NIR), 905nm wavelength,” said Wade Appelman, Vice President of the SensL Division, Intelligent Sensing Group atON Semiconductor. “We are excited to be highlighting our LiDAR partners who have designed in our latest AEC-Q101 qualified R-Series detectors because of their market leading 15% photon detection efficiency (PDE), a critical performance parameter to achieve long distance ranging.”

Completing the comprehensive line-up of automotive imaging technology will be a number of other demonstrations. These will include an 8.3MP advanced driver assistance system (ADAS) automotive image sensor performing in low light and foggy environments in RGB and NIR+ modes, and a 12MP image sensor for driver and occupant monitoring that is intended to address the needs of the emerging robot taxi market. A tabletop racetrack will demonstrate the global and rolling shutter performance of the sensor in an HDR setting.

MIMO+, a novel multi-modal radar function for ADAS that allows the implementation of both long and short-range operation in a single sensor, will also be demonstrated. ON Semiconductor’s high-performance radar mmIC will form the heart of this demonstration displaying the range, velocity and angle of detected targets, including people and objects.

In-cabin monitoring is becoming an important safety application and a solution for this will be shown using the 2.3MP RGB-IR sensors that produce color images in daylight and monochromatic images with NIR illumination at night. The set-up will demonstrate the tracking of both body and face analytics including the ability to recognize emotions.

SOURCE: ON Semiconductor

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