This surveillance system is provided with: a radar device which generates information indicating the reflection positions of radiated radio waves; and a surveillance device which, on the basis of the information indicating the reflection positions, detects a moving body in a radiation range of the radio waves, and determines whether an occlusion region, which is a region in the radiation range that cannot be reached by the radio waves, has arisen, and which generates surveillance information including information indicating the result of the moving body detection, and information indicating whether an occlusion region has arisen.

The described aspects and implementations enable efficient calibration of a sensing system of an autonomous vehicle (AV). In one implementation, disclosed is a method and a system to perform the method, the system including the sensing system configured to collect sensing data and a data processing system, operatively coupled to the sensing system. The data processing system is configured to identify reference point(s) in an environment of the AV, determine multiple estimated locations of the reference point(s), and adjust parameters of the sensing system based on a loss function representative of differences of the estimated locations.

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.

The technologies described herein relate to a domain adaptation system for sensor data. A computer-implemented model is trained using a set of training sensor data to facilitate classification of objects that are in the vicinity of an autonomous vehicle (AV). The set of training data corresponds to a first domain, such as firmware version of a sensor system, model of a sensor system, position of the sensor system on a vehicle, an environmental condition, etc. The set of training data is generated based upon pre-existing training data that corresponds to a second domain that is different from the first domain. Put differently, the pre-existing training data is transformed to correspond to the domain of a sensor system as it will be used on the AV.

Techniques and architectures for managing radar sensor processing chains. A first high-frequency radio signal is received with a first RF receiver in the plurality of RF sensor suites on a host platform. The received high-frequency radio signal is converted to a lower second frequency range. A chirplet transform is performed on the signal in the second frequency range. Stored relative location information for a second RF receiver in the plurality of RF sensor suites is retrieved. Radar waveform information corresponding to the second RF receiver in a processing stream corresponding to the first RF receiver is extracted by utilizing the retrieved information and results from the chirplet transform. A point cloud is generated based on the converted signal in the second frequency range and the extracted radar waveform information.

Provided herein is a system on a vehicle, the system comprising an active Doppler sensor; one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: obtaining a Doppler signature from each of one or more entities; and determining one or more calibration parameters of the active Doppler sensor based on the Doppler signature from at least a portion of the one or more entities.

There is provided a radar device which is mounted on a moving object and configured to detect a target on the basis of reception signals acquired by receiving reflected waves from the target by receiving antennae. A transmitting unit has a transmission axis substantially parallel to a traveling direction of the moving object. The transmitting unit is configured to transmit transmission waves around the transmission axis as a center thereof. A determining unit is configured to determine upward axis misalignment or downward axis misalignment of the transmission axis, on the basis of the reception signals acquired by receiving the reflected waves of the transmission waves.

The invention is a radar level gauge comprising a signal generator for generating electromagnetic waves and an antenna for emitting the electromagnetic waves in a container and for receiving electromagnetic waves reflected by the container. The radar level gauge also comprises a safety device for verifying the functional capability or for improving the measuring quality of the radar level gauge, said safety device having a reflector and an adjustment device and/or a reduction device and being suitably designed to adjust the reflector and/or the reduction device at least between a first position and a second position, in which the reflector reflects the electromagnetic waves in a reduced manner. The adjustment device acts on the reflector and/or the reduction device in a contactless manner.

A method of the present disclosure is a method of adjusting a radio wave sensor configured to transmit a radio wave to a reference object including a reflection portion and receive a reflected wave which is the radio wave reflected by the reflection portion. The method includes at least one of moving the reference object or moving the reflection portion, to cause a temporal change in detection data obtained from the reflected wave; and distinguishing the reflected wave and noise from each other by using the temporal change in the detection data.

The present teaching relates to different configurations for facilitating calibration of multiple sensors of different types. A plurality of fiducial markers are arranged in space for simultaneously calibrating multiple sensors of different types. Each of the plurality of fiducial markers has a feature point thereon and is provided to enable the multiple sensors to calibrate by detecting the features points and estimating their corresponding 3D coordinates with respect to respective coordinate systems of the multiple sensors.