sensor fusion for improved sensing performance

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Sensor fusion is the ability to bring together inputs from multiple radars, lidars and cameras to form a single model or image of the environment around a vehicle. The resulting model is more accurate because it balances the strengths of the different sensors.






Each sensor type, or “modality,” has inherent strengths and weaknesses. Radars are very strong at accurately determining distance and speed — even in challenging weather conditions — but can’t read street signs or “see” the color of a stoplight. Cameras do very well reading signs or classifying objects, such as pedestrians, bicyclists or other vehicles. However, they can easily be blinded by dirt, sun, rain, snow or darkness. Lidars can accurately detect objects, but they don’t have the range or affordability of cameras or radar.

Sensor fusion brings the data from each of these sensor types together, using software algorithms to provide the most comprehensive, and therefore accurate, environmental model possible. It can also correlate data pulled from inside the cabin, through a process known as interior and exterior sensor fusion.

A vehicle could use sensor fusion to fuse information from multiple sensors of the same type as well — for instance, radar. This improves perception by taking advantage of partially overlapping fields of view. As multiple radars observe the environment around a vehicle, more than one sensor will detect objects at the same time. Interpreted through global 360° perception software, detections from those multiple sensors can be overlapped or fused, increasing the detection probability and reliability of objects around the vehicle and yielding a more accurate and reliable representation of the environment.

6th Edition of International Conference on Sensing Technology | 23-24 June 2023 | San Francisco, US

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