Embodiments of this application provide an antenna and a preparation method thereof, a millimeter-wave sensor, and a terminal. Gaps exist between a plurality of coupling stubs and a microstrip feeder.

Embodiments of this application provide an antenna and a preparation method thereof, a millimeter-wave sensor, and a terminal. Gaps exist between a plurality of coupling stubs and a microstrip feeder.

Remote recovery of acoustic signals from passive sources is provided. Wideband radars, such as ultra-wideband (UWB) radars can detect minute surface displacements for vibrometry applications. Embodiments described herein remotely sense sound and recover acoustic signals from vibrating sources using radars. Early research in this domain only demonstrated single sound source recovery using narrowband millimeter wave radars in direct line-of-sight scenarios. Instead, by using wideband radars (e.g., X band UWB radars), multiple sources separated in ranges are observed and their signals isolated and recovered. Additionally, the see-through ability of microwave signals is leveraged to extend this technology to surveillance of targets obstructed by barriers. Blind surveillance is achieved by reconstructing audio from a passive object which is merely in proximity of the sound source using clever radar and audio processing techniques.

In accordance with a first aspect of the present disclosure, a system is provided for facilitating guiding a vehicle to a predefined location, said system configured to be included in a vehicle and comprising: one or more ultra-wideband (UWB) communication units configured to establish UWB communication with a UWB-enabled system installed at said predefined location; a controller configured to control said UWB communication units; wherein the controller is configured to cause the UWB communication units to switch between a communication mode of operation, a ranging mode of operation and a radar mode of operation.

A method for forming 3D image data representative of the subsurface of infrastructure located in the vicinity of a moving vehicle. The method includes: rotating a directional antenna, mounted to the moving vehicle, about an antenna rotation axis; performing, using the directional antenna whilst it is rotated about the antenna rotation axis, a plurality of collection cycles in which the directional antenna emits RF energy and receives reflected RF energy; collecting, during each of the plurality of collection cycles performed by the directional antenna.

A polarimetric radar system for object classification and road condition estimation includes a radar transmitter unit for transmitting radar waves of different polarizations, a radar receiving unit for receiving radar waves of different polarizations, a radar signal generating unit for generating and providing the radar waves to be transmitted, a signal processing circuitry for processing the generated and received radar waves, and a signal evaluation unit. The signal evaluation unit receives processed signals from the signal processing circuitry, estimates values for a set of predetermined object parameters on the basis of the received processed signals, and selects an object class from a plurality of predetermined object classes upon detecting a match of the estimated values with one out of a plurality of predetermined sets of object parameters. The signal evaluation unit is configured to provide information that is indicative of the at least one classified object.

A polarimetric radar system for object classification and road condition estimation includes a radar transmitter unit for transmitting radar waves of different polarizations, a radar receiving unit for receiving radar waves of different polarizations, a radar signal generating unit for generating and providing the radar waves to be transmitted, a signal processing circuitry for processing the generated and received radar waves, and a signal evaluation unit. The signal evaluation unit receives processed signals from the signal processing circuitry, estimates values for a set of predetermined object parameters on the basis of the received processed signals, and selects an object class from a plurality of predetermined object classes upon detecting a match of the estimated values with one out of a plurality of predetermined sets of object parameters. The signal evaluation unit is configured to provide information that is indicative of the at least one classified object.

Provided are systems and methods of using of optical delay lines in RF imagers, e.g., Ultra-wideband (UWB) imagers. In an embodiment, a modulator can be configured to convert radio-frequency signals to optical signal. First and second optical delay lines delay respective first and second optical signals converted by the modulator, and a photodetector can convert the delayed optical signals to at least one electrical signal corresponding to at least one pixel of a radio frequency image. The disclosed systems and methods can also further form a radio-frequency image based on output from the photodetector. In still further embodiments, the photodetector can receive modulated optical signals from an array of optical delays. Also provided are related methods of using the disclosed systems and devices.

There is provided a method performed by a system for obtaining a relative location of an anchor-free UWB-based node. The method includes obtaining relative distances between a plurality of nodes based on UWB sensor values between the nodes, constructing a relative coordinate system having a center node of the plurality of nodes as a base, and calculating coordinate values of other nodes in the relative coordinate system. The constructing of the relative coordinate system having the center node of the plurality of nodes as a base includes constructing the relative coordinate system based on a relative distance between the center node and another node and absolute values of y axis values.

A positioning system and a method based on neural network models are provided. The positioning method includes collecting WI-FI® fingerprint data; configuring a computing device to receive the WI-FI® fingerprint data, and the computing device includes a processor and a database storing positioning map data and a group of neural network models including a global positioning model, a coarse positioning model and a fine positioning model; configuring the processor to input the WI-FI® fingerprint data and perform the following steps: estimating a global coordinate through the global positioning model; obtaining the corresponding coarse positioning model from a corresponding primary sub-region to estimate an estimated coarse coordinate of a current position; estimating a plurality of estimated fine coordinates of the current position from the corresponding fine positioning model; and performing a merging process on the estimated fine coordinates to generate a final coordinate.