A device for monitoring a health parameter of a person is disclosed. The device includes a device body, a radio frequency (RF) front-end connected to the device body and including a semiconductor substrate and an antenna array including at least one transmit antenna configured to transmit radio waves below the skin surface of a person and a two-dimensional array of receive antennas configured to receive radio waves, the received radio waves including a reflected portion of the transmitted radio waves, wherein the semiconductor substrate includes circuits configured to generate signals in response to the received radio waves, and an alignment feature integrated into the device body and configured to align the antenna array with an object.

The disclosure relates to a sensor assembly for a vehicle, comprising: a sensor body; and a positioning bracket for positioning the sensor body. A first rotary shaft and a second rotary shaft are respectively provided on the opposing first and second sides of the sensor body, and the first rotary shaft and the second rotary shaft are respectively rotatably accommodated in a first rotary shaft receiving portion and a second rotary shaft receiving portion provided on the positioning bracket so as to achieve the rotation of the sensor body relative to the positioning bracket. A toothed structure is provided on a third side of the sensor body, other than the first side and the second side, and a detent structure is correspondingly provided on the positioning bracket, and when the sensor body rotates to a desired angle relative to the positioning bracket, fixing of the sensor body relative to the positioning bracket is enabled by means of the engagement between the toothed structure and the detent structure. The disclosure further relates to a vehicle comprising the sensor assembly.

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.

This document describes techniques for fine-motion virtual-reality or augmented-reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or sub-millimeter scale, for user control actions even when those actions are small, fast, or obscured due to darkness or varying light. Further, these techniques enable fine resolution and real-time control, unlike conventional RF-tracking or optical-tracking techniques.

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.

This document describes techniques and systems for independent transmit and receive channel calibration for multiple-input multiple-output (MIMO) systems. Antenna responses are collected from each virtual channel of a MIMO system at an angle respective to an object. The transmit components and the receive components of the virtual channels are separated and organized into vectors (one for the transmit components and one for the receive components). Calibration values for elements of the vectors are computed and maintained in a transmit calibration matrix and a receive calibration matrix, respectively. Together, the transmit calibration matrix and the receive calibration matrix may include fewer elements than a calibration matrix for the virtual channels and, therefore, may require less memory and fewer computations to calibrate a MIMO system than using other calibration techniques. As such, described is a less expensive and less complex way to calibrate MIMO system by accurately approximating an ideal antenna array.

The present disclosure relates to a detection circuit for detecting oscillations of a regulated supply signal. The detection circuit includes a filter circuit to filter the regulated supply signal in order to obtain a filtered supply signal. A peak value detector circuit is designed to detect an extremum of the filtered supply signal. A comparator circuit is designed to compare the detected extreme value with a threshold value and to indicate an understepping or exceedance of the threshold value.

An electronically aligned wideband tracking modulator system is described. The wide band tracking modulator system comprises a waveguide coupled to an antenna. The wide band tracking modulator system also comprises waveguide tuning circuitry configured to convert RF energy from a waveguide of the wideband tracking modulator system into an RF signal that can be processed by the waveguide tuning circuitry. The waveguide tuning circuitry is also configured to shift a phase of the RF signal. The waveguide tuning circuitry is further configured to convert the phase-shifted RF signal into phase-shifted RF energy and return the phase-shifted RF energy to the waveguide to electrically align the wideband tracking modulator system.

Various embodiments of the teachings herein include a method for determining a target position of a surroundings sensor of a vehicle using a vehicle-side attachment element as a calibration object, wherein the sensor and the attachment element are movable relative to each other. The method includes: ascertaining a first position of the surroundings sensor in a first relative pose; moving the sensor and/or the element from the first pose to a second pose between the sensor and the element; ascertaining a second actual position of the surroundings sensor in the second relative pose; and determining the target position of the surroundings sensor by averaging the first position and the second position to form an averaged actual position and assigning the averaged actual position as the target position.