A calibration utilizes reference data indicative of a position of a target element relative to a reference location, of a position of a reference point on a rotatable support relative to the reference location, orientation data indicative of at least one angular position of the rotatable support, and antenna measurement data indicative of electromagnetic echo signals received by a radar antenna from the target element. A measured position of the target element relative to the radar antenna is determined based on at least a portion of the antenna measurement data. A reference position of the target element relative to the radar antenna is determined based on the reference data and on at least a portion of the orientation data. At least one bias value or function associated with the orientation data and/or the antenna measurement data is determined based on a deviation between the determined measured position and reference position.

A method for estimating correction angles in a radar sensor for motor vehicles, by which method a correction angle that considers a misalignment of the radar sensor is calculated by a statistical evaluation of positioning data that were recorded by the radar sensor. The positioning angle range of the radar sensor is subdivided into multiple sectors. The statistical evaluation of the positioning data for the different sectors is performed separately for the different sectors so that an individual correction angle is obtained for each sector.

A computer includes a processor and a memory storing instructions executable by the processor to receive optical data from an optical sensor of a vehicle, adjust the optical data using an adjustment model, measure a first value from the optical data over a duration, predict a second value from the optical data over the duration based on the first value, measure the second value from the optical data over the duration, and modify the adjustment model using the predicted second value and the measured second value. The first value and the second value are time-varying and aggregated from the optical data per time step.

A multi-target dynamic simulation test system for vehicle-mounted millimeter-wave (MMW) radar. The test system includes an antenna turntable, a radar pan-and-tilt head (PTH), a radar echo simulation module, a control module, a signal acquisition module and a display. A test radar is driven by the radar PTH to pan or tilt. The radar PTH and the test radar are both placed in a darkroom module. An antenna is driven by the antenna turntable to pan. The control module sends expected states of the test radar and the antennas to the radar PTH and the antenna turntable, respectively, and sends relative states between host vehicle and virtual targets to the test radar after processing by the radar echo simulation module. The signal acquisition module acquires and stores a detection signal of the test radar, and transmits the detection signal of the test radar to the display for real-time display.

A method for calibrating two receiving units of a radar sensor that includes an array of receiving antennas formed by two sub-arrays and an evaluation unit, which is designed to carry out an angle estimation for located radar targets based on phase differences between the signals received by the receiving antennas, each receiving unit including parallel reception paths for the signals of the receiving antennas of one of the sub-arrays. The method includes: analyzing the received signals and deciding whether a multi-target scenario or a single-target scenario is present, in the case of a single-target scenario, measuring phases of the signals received in the sub-arrays and calculating a phase offset between the two sub-arrays, and calibrating the phases in the two receiving units based on the calculated offset.

The present invention relates to the field of vehicle correction, and provides a calibration system and a calibration bracket thereof. The calibration bracket includes: a base, a stand assembly and a beam assembly. The stand assembly is fixedly connected to the base. The beam assembly is supported by the stand assembly, and includes a beam, the beam being configured to mount a calibration element and including a left beam portion, a right beam portion and a connecting portion, the connecting portion being supported by the stand assembly, one end of the connecting portion being pivotally connected to the left beam portion, and the other end of the connecting portion being pivotally connected to the right beam portion. In the foregoing structure, the left beam portion and the right beam portion can respectively rotate toward each other relative to the connecting portion, to fold the beam assembly, so that a volume of the calibration bracket can be reduced to facilitate shipment.

A method, a control arrangement and a sensor target for enabling calibration of vehicle sensors. The sensor target comprises a plurality of recognition zones, each comprising a recognition pattern dedicated to a distinct sensor modality, for enabling calibration of vehicle sensors of the respective sensor modality; and localization dependent information associated with at least one recognition zone, provided to the vehicle via a vehicle sensor reading.

A vehicle control system may include a controller that detects an object outside a vehicle, calculates an angle based on a ratio of a relative speed between the object and the vehicle to a speed of the vehicle, and updates a phase curve reflecting a phase distortion of an input signal based on the calculated angle.

A vehicular radar auxiliary jig includes a transverse extensible bar, two longitudinal extensible bars and two upright bars. The longitudinal extensible bars are perpendicularly connected to two ends of the transverse extensible bar, respectively. One end of each longitudinal extensible bar is positioned distal to the transverse extensible bar and provided with a tire securing portion. The upright bars are perpendicularly connected to two ends of the transverse extensible bar and are perpendicular to the longitudinal extensible bars, respectively. One end of each upright bar is positioned distal to the transverse extensible bar and provided with a mounting portion, thereby connecting to an electromagnetic wave component. A vehicular radar mounting method and vehicular radar detecting method, each using the vehicular radar auxiliary jig, are provided. The vehicular radar auxiliary jig, vehicular radar mounting method and vehicular radar detecting method enable a vehicular radar to be mounted and tested efficiently.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular estimation using machine learning. In particular, a radar system 102 includes an angle-estimation module 504 that employs machine learning to estimate an angular position of one or more objects (e.g., users). By analyzing an irregular shape of the radar system 102's spatial response across a wide field of view, the angle-estimation module 504 can resolve angular ambiguities that may be present based on the angle to the object or based on a design of the radar system 102 to correctly identify the angular position of the object. Using machine-learning techniques, the radar system 102 can achieve a high probability of detection and a low false-alarm rate for a variety of different antenna element spacings and frequencies.