US 12,246,748 B2
Radar object classification based on radar cross-section data
Badeea Ferdaous Alferdaous Alazem, Redwood City, CA (US); and Chuang Wang, Woodside, CA (US)
Assigned to Zoox, Inc., Foster City, CA (US)
Filed by Zoox, Inc., Foster City, CA (US)
Filed on Jan. 31, 2022, as Appl. No. 17/589,504.
Prior Publication US 2023/0242149 A1, Aug. 3, 2023
Int. Cl. B60W 60/00 (2020.01); B60W 40/06 (2012.01); G01S 13/89 (2006.01); G06V 10/764 (2022.01); G06V 20/56 (2022.01)
CPC B60W 60/0011 (2020.02) [B60W 40/06 (2013.01); G01S 13/89 (2013.01); G06V 10/764 (2022.01); G06V 20/56 (2022.01); B60W 2420/408 (2024.01); B60W 2552/00 (2020.02); B60W 2554/20 (2020.02)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
one or more processors; and
one or more computer-readable media storing computer-executable instructions that, when executed, cause the one or more processors to perform operations comprising:
receiving, from a radar device, radar data captured at a first time, the radar data associated with a first region relative to a vehicle operating in an environment;
determining, based at least in part on radar cross-section data associated with the radar data, a variance of the radar cross-section data;
determining, based at least in part on determining that the variance is between a first lower variance threshold and a second higher variance threshold, that the radar data represents multiple objects having different object classifications within the first region;
determining, based at least in part on the object classifications of the multiple objects, a driving path for the vehicle; and
controlling the vehicle within the environment based at least in part on the driving path.