Gm Global Technolgoy Operations, Inc.

Bilik, Igal

Stainvas Olshansky, Inna

Gazit, Ran Y.

Inna Stainvas Olshansky

Igal Bilik

Oded Bialer

Yosi Buda

Ariel Lipson

Dan Levi

Avshalom Suissa

Ran Yehoshua Gazit

Ran Y Gazit

Methods and systems are provided for selectively analyzing radar signals of a radar system of a vehicle. A receiver is configured to receive a plurality of radar signals of a radar system of a vehicle. The interface is configured to obtain data from one or more sensors of the vehicle having a modality that is different from the radar system. The processor is coupled to the receiver and to the interface, and is configured to selectively analyze the plurality of radar signals based upon the data.

Vehicle radar methods and systems

A method for processing a sequence of images is provided. The method receives a sequence of images. Each image includes a plurality of pixels. The pixels include radial velocity information. The method compresses the sequence of images based on the radial velocity information. The method stores the compressed sequence of images in a storage device.

Doppler-based compression of imaging radar data

In an embodiment, a method for processing an image is provided. The method receives an image including a plurality of pixels. Each pixel includes radial velocity information. The method categorizes the plurality of pixels of the image into a plurality of groups of pixels based on radial velocity information of the pixels. The method associates at least one of the groups of pixels with an object.

Doppler-based segmentation and optical flow in radar images

An automotive radar system includes a radar camera that captures a sequence of frames of radar images of a field of view of the radar. A boundary detector receives the radar data from the radar camera and detects object boundary data in the radar data. An image processor receives the radar data and the object boundary data and performs image analysis including image deblurring and generating response control signals based at least in part on the radar data and the object boundary data. Response equipment implements one or more response actions based on the response control signals. Object boundary detection includes performing pixel-level Doppler analysis to associate pixel velocities to pixels of the radar data and identifying discontinuities in the pixel velocities. Response equipment may include, for example, one or more of a navigation display, collision avoidance warning, automatic cruise control, automatic braking, and automatic steering.

Object boundary detection for automotive radar imaging

Methods and apparatus are provided for controlling a beam pattern of a sensor array. The apparatus includes a plurality of sensors, wherein a distance is defined between at least two of the sensors. A shape memory alloy ('SMA') is coupled to at least one of the sensors. The SMA is controllably deformable to vary the distance between the sensors.

Dynamic sensor array

A detection system to detect an object and a method of performing detection of an object are described. The system includes a radar system to transmit radiation and receive resulting reflections, the object being a distributed radar target reflecting multi-point reflections. The system also includes an auxiliary sensor to estimate one or more parameters of the object, and a processor to estimate a probability density function based on estimates of the one or more parameters of the object and the multi-point reflections and to detect the object based on the probability density function.

Detection of a distributed radar target based on an auxiliary sensor

In an embodiment, a method for processing a sequence of images is provided. The method receives a sequence of images generated by a radar. Each image includes a plurality of pixels. Each pixel includes radial velocity information. The method estimates optical flow for the pixels within an image in the sequence of images by using the radial velocity information for the pixels as a constraint.

A target detection system and a method of performing radar target detection are described. The system includes a radar system to obtain radar echoes from a target with multiple point reflectors. The system also includes a processor to obtain a cluster of multi-dimensional point spread function from the radar echoes, each multi-dimensional point spread function being associated with a reflection from one of the multiple point reflectors, and also to perform object detection based on three or more dimensions of each of the multi-dimensional point spread functions of the cluster.

Radar target detection via multi-dimensional cluster of reflectors

Methods and systems are provided for controlling a radar system of a vehicle. One or more transmitters are configured to transmit radar signals. A plurality of receivers are configured to receive return radar signals after the transmitted radar signals are deflected from an object proximate the vehicle. A processor is coupled to the plurality of receivers, and is configured to generate a plurality of feature vectors based on the returned radar signals and generate a three dimensional representation of the object using the plurality of feature vectors.

Vehicle radar control

Methods and systems are provided for object classification for a radar system of a vehicle. The radar system includes a transmitter that transmits radar signals and a receiver that receives return radar signals after the transmitted radar signals are deflected from an object proximate the vehicle. A processor is coupled the receiver, and is configured to: obtain spectrogram data from a plurality of spectrograms pertaining to the object based on the received radar signals; aggregate the spectrogram data from each of the plurality of spectrograms into a computer vision model; and classify the object based on the aggregation of the spectrogram data from each of the plurality of spectrograms into the computer vision model.

Object classification for vehicle radar systems

A method of detecting curb-like barriers along a route of travel using a lidar sensing system. Sparse measurement per each ray tracing is captured from a sensor using the lidar sensing system. Each ray tracing is analyzed separately by a processor. Curb candidates are identified for each respective beam. Curb candidates are combined to generate multiple curb representative hypotheses. A weighting factor is applied to each curb hypothesis. Curb hypothesis that represents the curb is selected. The curb detection is applied to an autonomous guidance system related to guiding a vehicle along the route of travel.

Curb detection using lidar with sparse measurements

A method of determining a surface condition of a road of travel. A light beam directed at a surface in the road of travel is transmitted utilizing a lidar system. A response is analyzed at a photodetector of the lidar system after transmitting the light beam. A determination is made whether a form of precipitation is present on the road of travel in response to analyzing the response at the photodetector. A precipitation indicating signal is generated in response to the determination that the ground surface includes a form of precipitation on the road of travel.

Road surface reflectivity detection by lidar sensor

A method of creating a shadow-reduced image from a captured image. An image of a scene exterior of a vehicle is captured by a vehicle-based image capture device. A first object profile of an object in the captured image is identified by a processor. A second object profile of the object is detected using a non-vision object detection device. Shadows in the captured image are removed by the processor as a function of the first object profile and the second object profile. A shadow reduced image is utilized in a vehicle-based application.

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Modiin, Israel

Inna Stainvas Olshansky