US 12,246,748 B2 · Radar object classification based on radar cross-section data

Abstract

This disclosure describes techniques for using radar cross-section (RCS) data to classify objects detected by autonomous vehicles within driving environments. In some examples, the variance of the RCS data associated with an object may be evaluated to determine signal interference caused by multipath fading. The variance of the RCS data may be used to classify the object and to determine whether the autonomous vehicle can safely drive over the object. For instance, objects such as manhole covers, storm drains, and expansion joints may provide a significant radar signal, but low RCS variance indicating that they can be driven over by the vehicle. Based on the classification of the object, the autonomous vehicle may determine a trajectory around the object or directly over the object.

Claims20

Dependent claims

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.

6 more elements

A method 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.

3 more elements

One or more non-transitory computer-readable media storing instructions executable by a processor, wherein the instructions, when executed, cause the processor 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.

3 more elements

Dependencies are inferred from the claim text.

Radar object classification based on radar cross-section data

Life of this patent

Radar object classification based on radar cross-section data

Life of this patent

Abstract

Claims20