US 12,092,734 B2
Partially-learned model for speed estimates in radar tracking
Simon Roesler, Neuss (DE); Adrian Becker, Leverkusen (DE); and Jan K. Schiffmann, Newbury Park, CA (US)
Assigned to Aptiv Technologies AG, Schaffhausen (CH)
Filed by Aptiv Technologies AG, Schaffhausen (CH)
Filed on Dec. 15, 2021, as Appl. No. 17/644,464.
Claims priority of provisional application 63/265,189, filed on Dec. 9, 2021.
Claims priority of provisional application 63/169,038, filed on Mar. 31, 2021.
Claims priority of provisional application 63/166,108, filed on Mar. 25, 2021.
Prior Publication US 2022/0308205 A1, Sep. 29, 2022
Int. Cl. G01S 13/931 (2020.01); G01S 3/02 (2006.01); G01S 13/58 (2006.01); G01S 13/89 (2006.01); G06N 3/02 (2006.01)
CPC G01S 13/931 (2013.01) [G01S 13/58 (2013.01); G01S 13/89 (2013.01); G06N 3/02 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method, comprising:
generating, from radar signals, a data cube that represents an environment of a vehicle;
determining, based on the radar signals or the data cube, radial-velocity maps of potential detections in the environment of the vehicle, the radial-velocity maps including radial velocity data and Doppler data for the potential detections;
determining, using a model applied to the data cube, predicted boxes corresponding to respective groups of the potential detections, the predicted boxes including at least modeled speed estimates associated with each of the predicted boxes;
determining Doppler measurements associated with groups of the potential detections associated with each of the predicted boxes, the Doppler measurements including, for each of the box predictions, a list of measured radial velocities produced independent from an output from the model such that the list of measured radial velocities are associated with the groups of the potential detections determined for each of the box predictions;
determining, using the Doppler measurements associated with the groups of the potential detections determined for each of the predicted boxes, improved speed estimates for each of the predicted boxes by fusing ones of the corresponding measured radial velocities that align with areas of the box predictions generated using the model to replace the modeled speed estimates from the data cube with the improved speed estimates determined from the measured radial velocities; and
providing the improved speed estimates for the predicted boxes as an input to an autonomous-driving system or an assisted-driving system that operates the vehicle on a roadway.