Radar-tracked object velocity and/or yaw
Some radar sensors may provide a Doppler measurement indicating a relative velocity of an object to a velocity of the radar sensor. Techniques for determining a two-or-more-dimensional velocity from one or more radar measurements associated with an object may comprise determining a data structure that comprises a yaw assumption and a set of weights to tune the influence of the yaw assumption. Determining the two-or-more-dimensional velocity may further comprise using the data structure as part of regression algorithm to determine a velocity and/or yaw rate associated with the object.
1. A method comprising:
receiving radar data associated with an object;
determining, based at least in part on the radar data, a data structure comprising a first parameter portion and a second parameter portion, wherein the first parameter portion comprises:
a lateral contribution to a velocity of the object, the lateral contribution being associated with a first radar observation,
a longitudinal contribution associated with the first radar observation,
a yaw rate contribution associated with the first radar observation; and
wherein the second parameter portion comprises an assumption of a yaw rate associated with the object;
determining a set of weights to apply to the data structure, the set of weights comprising at least a first weight associated with the first radar observation and a second weight associated with the yaw rate contribution;
determining, based at least in part on the data structure and the set of weights, a final yaw rate associated with the object; and
controlling an autonomous vehicle based at least in part on the final yaw rate.
2. The method of claim 1 , wherein determining the velocity comprises determining a weighted regression based at least in part on the data structure and the set of weights.
3. The method of claim 1 , further comprising:
determining a velocity based at least in part on the data structure and the set of weights;
providing the velocity and the final yaw rate to a prediction system; and
receiving a predicted trajectory of the object from the prediction system,
wherein controlling the autonomous vehicle is further based at least in part on the predicted trajectory.
4. The method of claim 1 , further comprising receiving a track associated with the object, the track comprising at least one of a yaw or yaw rate associated with the object, wherein the yaw rate assumption is based at least in part on at least one of the yaw or yaw rate of the track.
5. The method of claim 1 , wherein determining the final yaw rate comprises determining a proposed yaw rate and the method further comprises:
determining a covariance based at least in part on the data structure; and
determining, based at least in part on the covariance and the proposed yaw rate, the final yaw rate of the object,
wherein controlling the vehicle is further based at least in part on the final yaw rate and the covariance.
6. A system comprising:
one or more processors; and
a memory storing processor-executable instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
receiving radar data associated with an object;
determining, based at least in part on the radar data, a data structure comprising a first parameter portion and a second parameter portion, wherein the second parameter portion comprises an assumption of a yaw rate associated with the object;
determining a set of weights to apply to the data structure, the set of weights comprising at least a first weight associated with a first radar observation and a second weight associated with a yaw rate contribution;
determining, based at least in part on the data structure and the set of weights, a final yaw rate associated with the object; and
controlling an autonomous vehicle based at least in part on the yaw rate.
7. The system of claim 6 , wherein the operations further comprise:
determining a velocity based at least in part on the data structure and the set of weights;
providing the velocity and the final yaw rate to a prediction system; and
receiving a predicted trajectory of the object from the prediction system,
wherein controlling the autonomous vehicle is further based at least in part on the predicted trajectory.
8. The system of claim 6 , wherein the data structure comprises a radar observation comprising at least one of a Doppler observation associated with the object, a Doppler direction vector, or an angle associated with the vector.
9. The system of claim 6 , wherein the operations further comprise receiving a track associated with the object, the track comprising at least one of a yaw or yaw rate associated with the object, wherein the yaw rate assumption is based at least in part on at least one of the yaw or yaw rate of the track.
10. The system of claim 6 , wherein determining the final yaw rate comprises determining a proposed yaw rate and the operations further comprise:
determining a covariance based at least in part on the data structure; and
determining, based at least in part on the covariance and the proposed yaw rate, the final yaw rate of the object,
wherein controlling the vehicle is further based at least in part on the final yaw rate and the covariance.
11. The system of claim 6 , wherein the operations further comprise:
associating a velocity with a previously-generated track associated with the object, or
generating a new track associated with the object and associating the velocity with the new track.
12. The system of claim 6 , wherein the operations further comprise at least one of determining a center or size of the object.
13. A non-transitory computer-readable medium storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
receiving radar data associated with an object;
determining, based at least in part on the radar data, a data structure comprising a first parameter portion and a second parameter portion, wherein the second parameter portion comprises an assumption of a yaw rate associated with the object;
determining a set of weights to apply to the data structure, the set of weights comprising at least a first weight associated with a first radar observation and a second weight associated with a yaw rate contribution;
determining, based at least in part on the data structure and the set of weights, a final yaw rate associated with the object; and
controlling an autonomous vehicle based at least in part on the final yaw rate.
14. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:
determining a velocity based at least in part on the data structure and the set of weights;
providing the velocity and the final yaw rate to a prediction system; and
receiving a predicted trajectory of the object from the prediction system,
wherein controlling the autonomous vehicle is further based at least in part on the predicted trajectory.
15. The non-transitory computer-readable medium of claim 13 , wherein the data structure comprises a radar observation comprising at least one of a Doppler observation associated with the object, a Doppler direction vector, or an angle associated with the vector.
16. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise receiving a track associated with the object, the track comprising at least one of a yaw or yaw rate associated with the object, wherein the yaw rate assumption is based at least in part on at least one of the yaw or yaw rate of the track.
17. The non-transitory computer-readable medium of claim 13 , wherein determining the final yaw rate comprises determining a proposed yaw rate and the operations further comprise:
determining a covariance based at least in part on the data structure; and
determining, based at least in part on the covariance and the proposed yaw rate, the final yaw rate of the object,
wherein controlling the vehicle is further based at least in part on the final yaw rate and the covariance.
18. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:
associating a velocity with a previously-generated track associated with the object, or
generating a new track associated with the object and associating the velocity with the new track.
19. The non-transitory computer-readable medium of claim 13 , wherein determining the first weight comprises:
determining a residual based at least in part on the data structure and the yaw rate; and
altering the first weight to reduce the residual.
20. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise at least one of determining a center or size of the object.