A radar target emulator with a superimposition apparatus, having a first input provided to receive a first signal, a second input provided to receive a second signal, a first attenuation device that is connected to the first input in signal-carrying fashion and configured to attenuate the first signal, in particular to a predetermined extent, and to provide a first attenuated signal, a second attenuation device that is connected to the second input in signal-carrying fashion and configured to attenuate the second signal, in particular to a predetermined extent, and to provide a second attenuated signal, an addition device that is configured to add the first attenuated signal and the second attenuated signal and to output a corresponding output signal.

This document describes techniques and systems for an adaptive ray-launcher for an electromagnetic response simulator. An adaptive ray-launching process is used to shoot electromagnetic rays at targets in a simulated environment. Uniformly distributed sparse electromagnetic rays are launched at the targets and the angular ray densities relative to the targets are calculated. Several propagation paths that include multipath effects are considered to determine the angular ray densities. Based on the length of the propagation paths of sparse electromagnetic rays with multipath related to each target, denser electromagnetic rays can be launched. The denser electromagnetic rays enable the fidelity related to targets in a far-range to be similar to the fidelity of closer targets. Additionally, any sparse electromagnetics that cannot be detected by a sensor can be disregarded. In this manner, an efficient and accurate electromagnetic response model may be approximated.

Apparatus for detecting misalignment of a radar unit (2; 22) of a vehicle (3; 23), the apparatus comprising: a magnet (1; 21), which may be a permanent magnet or an electromagnet, arranged to be mounted on the vehicle (3; 23) spaced from the radar unit (2; 22); a magnetic field sensor (4; 24), typically a three-axis magnetic field sensor, such as a Hall Effect Sensor, arranged to be coupled to the radar unit (2; 22) and having an output at which a signal indicative of the magnetic field at the magnetic field sensor (4; 24); and a processor (5; 25) coupled to the output and arranged to determine a misalignment of the radar unit (2; 22) based on the output of the magnetic field sensor (4; 24). Where the magnet is an electromagnet (21), the field strength of the electromagnet (21) can be varied by its drive circuit (30).

Devices and methods for testing altimeters are provided. A radio-frequency (RF) signal may be received from an altimeter and passed through an RF delay module to delay the RF signal. The delayed RF signal may be converted to an optical signal, which may be passed through an optical delay module to delay the optical signal. The system tests the accuracy of the altimeter based on the combined RF signal delay and optical signal delay.

A system and method of calibrating an ADAS sensor of a vehicle by aligning a target with the sensor, where the vehicle is initially nominally positioned in front of a target adjustment stand that includes a stationary base frame and a movable target mount configured to support a target, with the target adjustment stand including one or more actuators for adjusting the position of the target mount. A computer system is used to determine an orientation of the vehicle relative to the target adjustment stand, with the position of the target mount being adjusted based on the determined orientation of the vehicle relative to the target adjustment stand. Upon properly orienting the target mount, and the target supported thereon, a calibration routine is performed whereby the sensor is calibrated using the target.

A simulation system for use in testing a radar system comprises a coarse delay module, a fine delay module, and a doppler shift module. The coarse delay module is configured to receive a first stream of digital data samples that are sampled from a radar signal at a sample time period or a second stream of digital data samples that are processed by another simulation system component and delay the digital data samples by a selectable first delay time that is greater than or equal to the sample time period. The fine delay module is configured to receive the digital data samples and filter the digital data samples to represent delay by a selectable second delay time that is less than the sample time period. The doppler shift module is configured to receive the digital data samples and adjust a value of a frequency content of the fine delayed samples.

Disclosed is a method for detecting a faulty state of an FMCW-based fill level measuring device. For this, a correlation coefficient is ascertained by correlation, especially cross correlation, of the measurement signal with a reference signal. The faulty state is accordingly detected when the correlation coefficient subceeds a predefined minimum value. In this way, the functioning of the fill level measuring device can be monitored with a degree of safety allowing the fill level measuring device to be applied also in process plants and measuring environments, which require extremely reliable measuring apparatuses, and measurement data.

A radar system (2) for a vehicle (1), having a radar transceiver (3) and a control unit (4), where the control unit (4) is adapted to control the radar transceiver to apply an initial signal power level (P.sub.i) for transmitted radar signals (5); and to receive reflected radar signals (6) that have been reflected by at least one object (7). The control unit (4) is further adapted to determine a total signal reduction level (L) for which at least one predetermined criterion is not met; to compare the total signal reduction level (L) to a threshold; and to determine whether the radar transceiver (3) is working in an acceptable manner or not in dependence of the comparison.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for positioning a radio signal receiver at a first location within a three dimensional space; positioning a transmitter at a second location within the three dimensional space; transmitting a transmission signal from the transmitter to the radio signal receiver; processing, using a machine-learning network, one or more parameters of the transmission signal received at the radio signal receiver; in response to the processing, obtaining, from the machine-learning network, a prediction corresponding to a direction of arrival of the transmission signal transmitted by the transmitter; computing an error term by comparing the prediction to a set of ground truths; and updating the machine-learning network based on the error term.

A sensor calibration system for calibrating a sensor system associated with a device under test and methods for making and using same. The sensor calibration system can include a turntable system for supporting and rotating the device under test relative to at least one calibration target system and one or more imaging systems distributed about a periphery of the turntable system. The calibration target system can comprise a calibration target device with calibration indicia and a calibration target positioning system for positioning the calibration target device relative to the sensor system; whereas, the imaging systems can capture an image of the device under test as the turntable system rotates the device under test. In selected embodiments, the calibration target system advantageously can calibrate sensor systems that support one or more Advanced Driver Assistance (ADAS) and Autonomous Vehicle (AV) applications when the sensor systems are associated with a passenger vehicle.