Disclosed is a method and apparatus for measuring a distance to a target object by using a radar signal in an environment where an obstacle is present. The disclosed method of measuring a distance by using a radar includes: receiving a radar signal reflected from a target object by passing through a target obstacle; estimating material of the target obstacle by using an obstacle material learning result which uses a waveform of a reference radar signal, and by using a waveform of the reflected radar signal; estimating a thickness of the target obstacle by using an obstacle thickness learning result which uses a frequency feature of the reference radar signal, and by using a frequency feature of the reflected radar signal; and calculating a distance to the target object by using a permittivity according to the material of the target obstacle, and the thickness of the target obstacle.

A system (1) is configured to cause a first set of one or more radio frequency signals to be transmitted with a first transmission characteristic and/or a first reception characteristic, e.g. by lighting devices (31-37), detect whether changes in said first set of radio frequency signals are caused by a human (49) presence, detect whether the changes in the first set of radio frequency signals have a further cause, and cause a second set of one or more radio frequency signals to be transmitted with a second transmission characteristic and/or received with a second reception characteristic upon detecting that the changes in the first set of radio frequency signals have a further cause. The system is further configured to identify the further cause based on changes in the second set of radio frequency signals and provide output comprising the further cause or in dependence on the further cause.

The invention is related to a pair-assignment device (100) comprising a sensing-node position ascertainment unit (102) configured to ascertain position information (P.I.) pertaining to respective positions of external RF-sensing nodes (104,106) with respect to a predefined sensing volume (108) of a RF context-sensing arrangement and a pair-assigning unit (110) configured to assign, using the ascertained position information, at least one transmitter-receiver pair among the individual RF-sensing nodes of the RF context-sensing arrangement to perform a RF context-sensing function, to assign to the RF sensing nodes of the given transmitter-receiver pair a transmitter role (Tx) and a receiver role (Rx), respectively. The pair-assignment device then provides pair information indicative of the at least one assigned transmitter-receiver pair and the assigned transmitter and receiver roles and thus enables an increase of tolerance of the RF context-sensing arrangement against changes in the position of movable objects.

An active radio-frequency (RF) sensing technology for determining the relative and/or absolute state (e.g., position, velocity, and/or acceleration) of a target object (e.g., a person, a car, a truck a lamp post, a utility pole, a building) is described. The sensors described herein operate in the Terahertz band (300 GHz to 3 THz). An active RF sensing device comprises a substrate and first and second semiconductor dies mounted on the substrate. The first semiconductor die has an RF transmit antenna array integrated thereon, and the transmit antenna array comprises a first plurality of RF antennas configured to generate an RF signals having frequency content in the 300 GHz-3 THz band. The second semiconductor die has an RF receive antenna array integrated thereon, and the receive antenna array comprises a second plurality of RF antennas configured to receive RF signals having frequency content in the 300 GHz-3 THz band.

A drone classification device is provided. The drone classification device includes a radio signal receiver configured to receive a radio signal, and a radio signal analyzer configured to determine physical characteristics of the received radio signal, to compare the determined physical characteristics of the received radio signal with a plurality of reference characteristics, each reference characteristics describing a drone class of a plurality of drone classes, and to classify a drone into a drone class of a plurality of drone classes depending on a result of the comparison.

A terahertz frequency-based sensing system for an agricultural harvester is provided. The system includes a terahertz sensor mounted to the agricultural harvester. The terahertz sensor at least one a terahertz source disposed to direct electromagnetic radiation toward a harvest material of the agricultural harvester. At least one terahertz detector is disposed to detect the terahertz electromagnetic radiation after the terahertz electromagnetic radiation interacts with the harvest material. A controller is operably coupled to the at least one terahertz detector and is configured to detect at least one harvest-related parameter based on a signal from the at least one terahertz detector and to perform an action based on the at least one detected parameter.

A reflectivity correction method using a double polarization variable-based bright band detection result includes a preprocessing operation for correcting a double polarization variable observation error and calculating a depolarization ratio; a fuzzy classifier generation operation for calculating a weighting and a membership function of each characteristic variable using a bright band height extracted from a quasi-vertical profile generated from specific elevation angle data, a bright band detection operation for detecting a bright band using a depolarization ratio and a fuzzy classifier for each elevation angle, and a reflectivity correction operation for correcting reflectivity over-observation for a detected bright band region on the basis of a correction factor calculated using an apparent profile of reflectivity generated by averaging reflectivity data for the bright band region for each elevation angle. Thus, it is possible to improve the accuracy of precipitation estimation by using the corrected reflectivity.

A tree harvesting head for a tree harvesting machine, wherein the tree harvesting head comprises at least one cutting device, at least two feed wheels and a radar device. The radar device comprises at least one radar transmitter antenna arranged to transmit a signal to a tree trunk to be measured, at least two radar receiver antennas arranged to receive a radar signal reflected in at least a first and a second location in response to the transmitted radar signal, wherein the first and second locations are different locations. The radar device further comprises means for obtaining characteristics related to the tree trunk based on the signal(s) reflected at the first and second locations. The means for obtaining characteristics related to the tree trunk is arranged to determine a tree trunk signature of a tree trunk segment located at the first location, to identify the determined tree trunk signature when the tree trunk segment has travelled to the second location and to determine a length of the tree trunk based thereon.

Aspects and implementations of the present disclosure address challenges of the existing technology by enabling lidar-assisted identification and characterization of visibility-reducing media (VRM) such as fog, rain, snow, dust in autonomous vehicle applications, using lidar sensing. VRM can be identified and characterized using a variety of techniques, including analyzing a spatial distribution of low-intensity lidar returns, detecting pulse elongation of VRM-returns associated with reflection from VRM, determining intensity of VRM-returns, determining reduction of intensity of returns from various reference objects, and other techniques.

A system for controlling operation of a vehicle includes a millimeter-wave radar sensor, a processor, and a memory communicably coupled to the processor. The memory stores a sensor control module configured to automatically control operation of the radar sensor to perform at least one radar scan of at least a portion of an interior of the vehicle. The sensor control module is also configured to determine, using information acquired by the at least one radar scan of the vehicle interior, at least one characteristic of a child car seat positioned in the interior. The sensor control module is also configured to compare the at least one determined characteristic of the child car seat with child car seat comparison information and, responsive to the comparison of the at least one determined characteristic with the child car seat comparison information, control an operation of the vehicle.