Aeva, Inc.

James Nakamura

Kumar Bhargav Viswanatha

Jose Krause Perin

Rajendra Tushar Moorti

Esha John

Carlo Giustini

Mina A Rezk

Krishna Toshniwal

Bruno Hexsel

James Reuther

Kshitij Jain

A set of POIs of a point cloud are received at a first filter, where each POI of the set of POIs comprises one or more points. Each POI of the set of POIs is filtered. A set of neighborhood points of a POI is selected. A metric for the set of neighborhood points is computed based on a property of the set of neighborhood points and the POI, wherein the property comprises a velocity. Based on the metric, whether to accept the POI, modify the POI, reject the POI, or transmit the POI to a second filter, to extract at least one of range or velocity information related to the target is determined. Provided the POI is not accepted, modified, or rejected, the POI is transmitted to the second filter to determine whether to accept, modify, or reject the POI to extract the at least one of range or velocity information related to the target.

Techniques for filtering points in a light detection and ranging system

A light detection and ranging (LIDAR) system transmits, towards a target, a set of chirp signals. The LIDAR system receives from the target, a set of adjusted chirp signals. The LIDAR system then determines, based on the set of adjusted chirp signals, a degree of ghosting mitigation to compensate for a ghost target appearing in a point cloud at a location where no real target exists.

Techniques for ghosting mitigation in coherent LIDAR systems using multiple chirp rates

A light detection and ranging (LIDAR) system to transmit optical beams including at least up-chirp frequency and at least one down-chirp frequency toward targets in a field of view of the LIDAR system and receive returned signals of the up-chirp and the down-chirp as reflected from the targets. The LIDAR system may determine multiple frequency peaks associated with the target based on the returned signals. Upon determining that at least one of the multiple frequency peaks is within one or more sets of frequency ranges, the LIDAR system may combine an in-phase signal and a quadrature signal of the returned signals to generate a complex signal that enables determining whether the at least one of the multiple frequency peaks is associated with ghosting. Upon determining to be free from ghosting, the LIDAR system determines one or more of the target location, a target velocity, and a target reflectivity.

Techniques for ghosting mitigation in coherent LIDAR systems using in-phase/quadrature phase (IQ) processing

A method transmits a first optical beam towards targets within a field of view (FOV). The first optical beam is modulated at a first chirp rate for a first set of scan lines that correspond to a first distance of the targets. The method identifies conditions based on the FOV to calculate a second chirp rate, and generates a scan pattern by transmitting a second optical beam towards the targets within the FOV. The second optical beam is modulated at the second chirp rate for a second set of scan lines that corresponds to a second distance of the one or more targets. The method generates, based on the first and second optical beams, the point cloud that includes multiple data points related to the target in which some of the data points are related to a first target and other data points are related to a second target.

Techniques for foveated and dynamic range modes for FMCW LIDARs

A light detection and ranging (LIDAR) technique that includes dividing the field of view into a grid including a plurality of cells. The technique also includes generating a baseband signal based on a returned optical beam. The baseband signal includes a plurality of peaks corresponding with up-chirps and down-chirps in the transmitted signal. A plurality of points are computed based on the peaks. Each point includes information describing a range and a velocity and corresponds to a respective cell. A point confidence score is computed for each point, and a cell confidence score is computed for each cell based on the point confidence scores of the points within the cell. Each point can be accepted or rejected for inclusion in a point cloud based on the point confidence score for the point and the cell confidence scores for the plurality of cells.

Techniques for improving probability of detection in light detection and ranging (LIDAR) systems

A set of POIs of a point cloud are received at a first filter, where each POI of the set of POIs comprises one or more points. Each POI of the set of POIs is filtered. A set of neighborhood points of a POI is selected. A metric for the set of neighborhood points is computed. Based on the metric, whether to accept the POI, modify the POI, reject the POI, or transmit the POI to a second filter, to extract at least one of range or velocity information related to the target is determined. Provided the POI is accepted or modified, the POI is transmitted to a filtered point cloud; provided the POI is rejected, the POI is prevented from reaching the filtered point cloud; provided the POI is not accepted, modified, or rejected, the POI is transmitted to a second filter.

Techniques for point cloud filtering

A light detection and ranging (LIDAR) system to transmit optical beams including at least two up-chirp signals and at least two down-chirp signals toward targets in a field of view of the LIDAR system and receive returned signals of the up-chirp and the down-chirp as reflected from the targets. The LIDAR system generates a baseband signal in a frequency domain of the returned signals of the at least two up-chirp signals and the at least two down-chirp signals. The baseband signal includes a first set of peaks associated with the at least one up-chirp signal and a second set of peaks associated with the at least one down-chirp signal. The LIDAR system determines the target location using the first set of peaks and the second set of peaks.

A light detection and ranging (LIDAR) system to transmit optical beams including at least up-chirp frequency and at least one down-chirp frequency toward targets in a field of view of the LIDAR system and receive returned signals of the up-chirp and the down-chirp as reflected from the targets. The LIDAR system may perform IQ processing on one or more returned signals to generate baseband signals in the frequency domain of the returned signals during the at least one up-chirp and the at least one down-chirp. The baseband signal includes a first set of peaks associated with the at least one up-chirp frequency and a second set of peaks associated with the at least one down-chirp frequency. The LIDAR system determines the target location using the first set of peaks and the second set of peaks.

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Chicago, IL, United States of America

James Nakamura