Embodiments of the present disclosure provide a method, an apparatus, a device, and a medium for determining an angle of yaw, relating to a field of automatic driving. The method includes: obtaining, during a vehicle being driving straightly on a straight road, data of each obstacle in an environment located by the vehicle, the data of each obstacle being detected by a millimeter wave radar sensor located in the vehicle, at least one metal obstacle being provided on the straight road; recognizing the metal obstacle based on the data of each obstacle, and obtaining a metal obstacle line by fitting positions of the metal obstacle at different time points; and determining an angle between the metal obstacle line and a direction of a vehicle body as an angle of yaw between the millimeter wave radar sensor and the vehicle body.

A method for determining an ego-velocity estimated value and an angle estimated value of targets using a synthetic aperture radar sensor. A distance is measured between the synthetic aperture radar sensor and each respective target. A relative velocity of the respective target is measured using the Doppler effect. An angle estimation of an angle estimated value takes place, which characterizes the angle between the direction of the ego-velocity of the synthetic aperture radar and the respective target. An individual ego-velocity estimated value of the synthetic aperture radar sensor is ascertained using the relative velocity and the angle estimated value for each target. A classification and distribution of the individual ego-velocity estimated values relating to stationary targets takes place, whose individual ego-velocity estimated values are situated within a predefinable range relative to one another, and relating to moving targets, whose individual ego-velocity estimated values are situated outside the range.

Aspects of the disclosure are directed to spatial imaging using an imaging radar including generating a plurality of range/Doppler/channel images from a detected image and a four-dimensional image; generating a transfer matrix for each of the plurality of range/Doppler/channel images; generating a plurality of scatterer parameters using maximum likelihood (ML) processing on the plurality of range/Doppler/channel images; generating a plurality of refined scatterer parameters from the plurality of scatterer parameters and the transfer matrix; determining a minimal-order scatterer configuration using the plurality of refined scatterer parameters and the transfer matrix; and generating a set of determined scatterer parameters from the minimal-order scatterer configuration and the transfer matrix.

Aspects of the disclosure are directed to spatial imaging using an imaging radar including generating a plurality of range/Doppler/channel images from a detected image and a four-dimensional image; generating a transfer matrix for each of the plurality of range/Doppler/channel images; generating a plurality of scatterer parameters using maximum likelihood (ML) processing on the plurality of range/Doppler/channel images; generating a plurality of refined scatterer parameters from the plurality of scatterer parameters and the transfer matrix; determining a minimal-order scatterer configuration using the plurality of refined scatterer parameters and the transfer matrix; and generating a set of determined scatterer parameters from the minimal-order scatterer configuration and the transfer matrix.

A radar data processing method and apparatus. The radar data processing apparatus calculates phase information of a radar signal received by a radar sensor, calculates noise representative information from the calculated phase information, and determines driving-related information based on the noise representative information and radar data calculated from the radar signal.

Systems may include at least one processor configured to determine a predicted value of an unwrap factor using a machine learning model, wherein the machine learning model is a trained machine learning model configured to provide a predicted value of an unwrap factor for dealiasing a measurement of range rate of a target object as an output, dealiase a measurement value of range rate from a radar of an autonomous vehicle (AV) based on the predicted value of the unwrap factor to provide a true value of range rate, and control an operation of the AV in a real-time environment based on the true value of range rate. Methods, computer program products, and autonomous vehicles are also disclosed.

In one aspect, a system for monitoring soil flow around a ground-engaging tool of an agricultural implement. The system may include a ground-engaging tool configured to be moved through the soil as the agricultural implement travels across a field. Furthermore, the system may include a radar sensor configured to capture data indicative of a flow of the soil around the ground-engaging tool within a detection zone of the radar sensor. Additionally, the system may include a controller communicatively coupled to the radar sensor. The controller may, in turn, be configured to generate a representation of the flow of the soil around the ground-engaging tool within the detection zone based on data received from the radar sensor.

Multiple exemplary systems for preventing jackknifing are disclosed. The systems comprise an electric motor for extending a shaft into a fifth wheel coupling when a tractor trailer is traveling at above a predetermined speed in a forward direction, physically preventing the tractor trailer from jackknifing. In order to avoid dependence on integration with a tractor, sensors on a trailer are used to determine speed without communication with the tractor or any instruments therein, via reception of one or more waves. When the trailer is determined to be traveling at below the predetermined speed in a forward direction, or at any speed in a backward direction, the shaft is retracted to allow the trailer to freely rotate with respect, to the tractor.

A method for active neutralization of the effect of the vibrations of a rotary-wing aircraft for a monostatic Doppler radar includes a first step of measuring and temporally extrapolating the vibration modes at the transmitting-receiving radar antenna, using a 3-axis vibration sensor, fixed to the antenna and near the phase centre of the antenna; then a second step of estimating the expected movements of the transmitting-receiving antenna or of the first transmitting antenna and the second receiving antenna; then a third step of compensating the expected movements of the transmission radar antenna in the transmission chain or in the reception chain of the radar transmitter, wherein the projection of the movement vector of the phase centre O on an aiming direction is calculated to determine the value of the compensation phase shift to be applied.

A method for active neutralization of the effect of the vibrations of a rotary-wing aircraft for a monostatic Doppler radar includes a first step of measuring and temporally extrapolating the vibration modes at the transmitting-receiving radar antenna, using a 3-axis vibration sensor, fixed to the antenna and near the phase centre of the antenna; then a second step of estimating the expected movements of the transmitting-receiving antenna or of the first transmitting antenna and the second receiving antenna; then a third step of compensating the expected movements of the transmission radar antenna in the transmission chain or in the reception chain of the radar transmitter, wherein the projection of the movement vector of the phase centre O on an aiming direction is calculated to determine the value of the compensation phase shift to be applied.