According to an example aspect of the present invention, there is provided a method comprising, transmitting by a wireless device, during a first phase, a first probe signal associated with a user and receiving a reflected version of the first probe signal, transmitting by the wireless device, during the first phase, the reflected version of the first probe signal to a ground truth classifier, transmitting by the wireless device, during a second phase, a second probe signal associated with the user and receiving a reflected version of the second probe signal and transmitting by the wireless device, during the second phase, the reflected version of the second probe signal to a trusted apparatus.

An automatic wall climbing type radar photoelectric robot system for damages of a bridge and tunnel structure, mainly including a control terminal, a wall climbing robot and a server. The wall climbing robot generates a reverse thrust by rotor systems, moves flexibly against the surface of a rough bridge and tunnel structure by adopting an omnidirectional wheel technology, and during inspection by the wall climbing robot, bridges and tunnels do not need to be closed, and the traffic is not affected. Bridges and tunnels can divide into different working regions only by arranging a plurality of UWB base stations, charging and data receiving devices on the bridge and tunnel structure by means of UWB localization, laser SLAM and IMU navigation technologies, a plurality of wall climbing robots supported to work at the same time, automatic path planning and automatic obstacle avoidance realized, and unattended regular automatic patrolling can be realized.

A method of automatically detecting damage following a loss causing incident is disclosed. The method includes capturing image information about a group of physical objects in their initial states and comparing these with image information about the group of physical objects in their modified states following a loss causing incident. The method includes detecting discrepancies between the initial and modified states and automatically assesses the degree of damage and/or loss.

A system and bent-pipe transponder component for determining a location of an individual or object in three dimensional space. The system includes a transmitter configured to transmit a first wireless electromagnetic signal at a first frequency and at least one transponder that is configured to responsively emit a second wireless electromagnetic signal having a second frequency that is frequency-shifted from the first frequency. An included receiver detecting the first and second wireless electromagnetic signals is configured to provide an output of location information for the at least one transponder. A bent-pipe transponder component may include a receiving antenna, an emitting antenna, and a frequency shift stage comprising an oscillator and a first mixer, with the frequency stage mixing a received first wireless electromagnetic signal with the output of the oscillator via the first mixer to produce the emitted second wireless electromagnetic signal.

Examples of imaging systems are described herein which may implement microwave or millimeter wave imaging systems. Examples described may implement partitioned inverse techniques which may construct and invert a measurement matrix to be used to provide multiple estimates of reflectivity values associated with a scene. The processing may be partitioned in accordance with a relative position of the antenna system and/or a particular beamwidth of an antenna. Examples described herein may perform an enhanced resolution mode of imaging which may steer beams at multiple angles for each measurement position.

An example system and method provides radiating into the 3D environment a millimeter wave (mmWave) radio frequency (RF) radiation signal that interacts with reflective surfaces, penetrable surfaces, scattering surfaces of the 3D environment, producing respective multipath components, determining information from two or more of the multipath components, including two among, or, optionally, all of angle of arrival (AoA), angle of departure (AoD), time of arrival, relative time of arrival (RTA), and phase and, based on the information and the received multipath components, performs computing the user device’s relative or absolute mobile device location in relation to the surrounding 3D environment, and providing images or video of the surrounding 3D environment to a display or a storage of the user’s mobile device, for displaying or storing.

Various embodiments wirelessly detect micro gestures using multiple antenna of a gesture sensor device. At times, the gesture sensor device transmits multiple outgoing radio frequency (RF) signals, each outgoing RF signal transmitted via a respective antenna of the gesture sensor device. The outgoing RF signals are configured to help capture information that can be used to identify micro-gestures performed by a hand. The gesture sensor device captures incoming RF signals generated by the outgoing RF signals reflecting off of the hand, and then analyzes the incoming RF signals to identify the micro-gesture.

Certain embodiments provide an imaging method for a non-line-of-sight object and an electronic device. In certain embodiments, the method includes: detecting a first input operation; and generating first image data in response to the first input operation. The first image data is imaging data of the non-line-of-sight object obtained by fusing second image data and third image data. The first image data includes position information between the non-line-of-sight object and a line-of-sight object. The second image data is imaging data of the line-of-sight object captured by the optical camera. The third image data is imaging data of the non-line-of-sight object captured by the electromagnetic sensor.

Methods and a device for imaging objects including unsupervised classifying and data analyzing of the object to detect and identify the structure of the object and further display the object's structure underlying structure, for example the arrangement of and relationships between the parts or elements of the object by using a location module configured to record the physical location of an antenna array.

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.