An outside sensor unit includes an outside sensor, a main bracket, a support bracket, a rotation device, and a position adjustment device. The outside sensor detects the outside of a vehicle. The main bracket is attached to a vehicle body. The support bracket supports the outside sensor and is attached to the main bracket. The rotation device has a rotation axis line which is substantially parallel to a roll axis of the vehicle and connects the support bracket and the main bracket together rotatably around the rotation axis line. The position adjustment device is capable of adjusting the relative rotation position between the support bracket and the main bracket around the rotation axis line.

A low range altimeter (LRA) may include a transmitter, a receiver, at least one antenna, an active leakage cancellation circuit, and a microcontroller unit (MCU). The transmitter may be configured to transmit a first signal (or transmitted signal) via the at least one antenna. The receiver may be configured to receive a second signal (or received signal) via the at least one antenna. The active leakage cancellation circuit may be configured to receive a portion of the transmitted signal from the transmitter, and may be configured to inject the portion of the transmitted signal into the receiver after an adjustment of the portion of the transmitted signal to reduce leakage observed in the received signal. The MCU may be coupled to the transmitter and the receiver, and may be configured to adjust the portion of the portion of the transmitted signal.

An apparatus for correcting an error of a radar sensor for a vehicle and a method thereof can correct a target measurement error of the radar sensor installed inside a bumper of the vehicle based on target information obtained from a camera image. The apparatus includes: a radar sensor that is installed inside a bumper of the vehicle to detect a target, a camera that photographs a surrounding image of the vehicle, and a controller that corrects a target detection error of the radar sensor based on target information obtained from an image photographed by the camera.

A system for intelligently implementing an autonomous agent that includes an autonomous agent, a plurality of infrastructure devices, and a communication interface. A method for intelligently calibrating infrastructure (sensing) devices using onboard sensors of an autonomous agent includes identifying a state of calibration of an infrastructure device, collecting observation data from one or more data sources, identifying or selecting mutually optimal observation data, specifically localizing a subject autonomous agent based on granular mutually optimal observation data, identifying dissonance in observation data from a perspective of a subject infrastructure device, and recalibrating a subject infrastructure device.

A system for intelligently implementing an autonomous agent that includes an autonomous agent, a plurality of infrastructure devices, and a communication interface. A method for intelligently calibrating infrastructure (sensing) devices using onboard sensors of an autonomous agent includes identifying a state of calibration of an infrastructure device, collecting observation data from one or more data sources, identifying or selecting mutually optimal observation data, specifically localizing a subject autonomous agent based on granular mutually optimal observation data, identifying dissonance in observation data from a perspective of a subject infrastructure device, and recalibrating a subject infrastructure device.

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 GPR system the implements a modified multistatic mode of operation is provided. The GPR is suitable for mounting on an unmanned aerial vehicle. The GPR system has radar transceivers. The GPR system transmits transmit signal serially via the transceivers. For each transceiver that transmits a transmit signal, the GPR system receives a return signal acquired by each transceiver except for a return signal for the transceiver that transmits the transmit signal. The GPR system outputs of matrix of return signals that includes a null value for the return signals of the transceivers that transmit.

A conventional millimeter wave radar cannot detect a failure when there is not satisfied the condition that a road exists in front of a vehicle or that in two or more radar apparatuses, a leakage electric wave from another radar can be detected. A failure detection apparatus according to the present disclosure calculates reception power values from a reception processing signal for each antenna and compares the reception power value with a reference power value determined by a reference power calculation unit so as to perform a failure determination. There is provided a failure determination unit that compares the reference power value for a failure determination with the power value obtained from a reception processing signal outputted from each of receivers so as to perform a failure determination for each of the receivers.

This document describes techniques for enabling radar system calibration with bistatic sidelobe compensation. Radar signals reflect off of a flat plate that changes orientation (e.g., elevation and/or azimuth angle) and position relative to a mounting position of a specific radar sensor being calibrated. For each radar sensor, measurements may be obtained across a range of translational positions of the flat plate. Highly accurate calibration errors are determined for each radar sensor this way. By calibrating radar systems repositioning the target during the data collection in this way, the prominence of any bistatic sidelobes appearing in measurements may be reduced or prevented, which may enable less-complex and more-accurate calibration of each unique radar system installation. An indication of each calibration error may be output for use in individually adjusting the mounting position of each specific radar sensor within a radar system.

This document describes techniques for enabling radar system calibration with bistatic sidelobe compensation. Radar signals reflect off of a flat plate that changes orientation (e.g., elevation and/or azimuth angle) and position relative to a mounting position of a specific radar sensor being calibrated. For each radar sensor, measurements may be obtained across a range of translational positions of the flat plate. Highly accurate calibration errors are determined for each radar sensor this way. By calibrating radar systems repositioning the target during the data collection in this way, the prominence of any bistatic sidelobes appearing in measurements may be reduced or prevented, which may enable less-complex and more-accurate calibration of each unique radar system installation. An indication of each calibration error may be output for use in individually adjusting the mounting position of each specific radar sensor within a radar system.