In an aspect, a wireless node may determine a sub-panel configuration associated with a reconfigurable intelligence surface (RIS) that includes a plurality of sub-panels. The wireless node may transmit or receive one or more signals via one or more sub-panels of the plurality of sub-panels in accordance with the sub-panel configuration.

This document describes techniques and devices for non-line-of-sight radar-based gesture recognition. Through use of the techniques and devices described herein, users may control their devices through in-the-air gestures, even when those gestures are not within line-of-sight of their device's sensors. Thus, the techniques enable users to control their devices in many situations in which control is desired but conventional techniques do permit effective control, such as to turn the temperature down in a room when the user is obscured from a thermostat's gesture sensor, turn up the volume on a media player when the user is in a different room than the media player, or pause a television program when the user's gesture is obscured by a chair, couch, or other obstruction.

Smart surveillance data processing systems support safe uncrewed aircraft system (UAS) or uncrewed surface vessels/vehicles operations where remote pilots are operating their uncrewed aircraft beyond visual line of sight (BVLOS) or near controlled areas, by providing: (i) real-time situational awareness in dense crewed aircraft and uncrewed drone environments while providing automated detection and alerting of intruders to remote pilots in command; (ii) surveillance network performance assessments through radar and ADS-B quantifiable measures; (iii) detection and alerting of any appreciable degradation of surveillance sensor performance, allowing remote pilots to suspend or alter operations to ensure safety; (iv), standardized airspace reporting including traffic patterns; (v) certification of portions of the airspace where the surveillance network is capable of meeting a minimum standard; (vi) assessment and reporting of drone compliance and non-compliance with UAS operating regulations.

This document describes techniques and devices for non-line-of-sight radar-based gesture recognition. Through use of the techniques and devices described herein, users may control their devices through in-the-air gestures, even when those gestures are not within line-of-sight of their device's sensors. Thus, the techniques enable users to control their devices in many situations in which control is desired but conventional techniques do permit effective control, such as to turn the temperature down in a room when the user is obscured from a thermostat's gesture sensor, turn up the volume on a media player when the user is in a different room than the media player, or pause a television program when the user's gesture is obscured by a chair, couch, or other obstruction.

A centralized occupancy detection system enables monitoring of multiple seats, or more generally, multiple stations, with a single sensor. One illustrative vehicle includes: one or more stations each configured to accommodate an occupant of the vehicle, a radar-reflective surface, and a radar transceiver configured to use the radar-reflective surface to detect an occupant of at least one of the stations. Another illustrative vehicle includes: multiple stations to each accommodate an occupant of the vehicle, and a radar transceiver configured to examine each of the multiple stations to determine whether that station has an occupant.

False detection of a ghost is prevented. A radar apparatus includes: transmission circuitry, which, in operation, transmits a radar signal; main reflective object detection circuitry, which, in operation, detects a main reflective object in a detection area using a reflected wave of the radar signal; in-area determination circuitry, which, in operation, determines a main area where a ghost caused by a reflective object outside the detection area and the main reflective object is located, the main area being inside the detection area; and auxiliary reflective object detection circuitry, which, in operation, detects a position of an auxiliary reflective object in the main area using a reception signal of the reflected wave of the radar signal, the auxiliary reflective object being located farther than the main reflective object on an extension of a line connecting the radar apparatus and the main reflective object.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) in a vehicle-to-everything (V2X) system may receive configuration information from an assisting node, such as a roadside unit (RSU), for calculating location information for a target UE in the V2X system. The assisting node may reflect one or more radar signals from the UE towards the target, and from the target back towards the UE according to the configuration information. That is, the assisting node may modify one or more waveform parameters of the reflection according to the configuration information. The UE may calculate location information for the target based on the reflection, such as by classifying the target as non-line-of-sight (NLOS) based on modified waveform parameters, location information of the assisting node, or both.

Described herein are devices, systems, methods, and processes for improving the accuracy of fine timing measurement (FTM)-based ranging in wireless networks. An initiating device may select optimal transmit and receive chains for ranging measurements between the initiating device and a responding device. The selection can be based on the quality of the link between the devices, determined through the analysis of channel state information. The initiating device can further detect non-line-of-sight conditions and can apply correction factors to minimize the error caused by multipath reflections. The outcome is a more accurate estimate of the distance between devices, enhancing the precision of location determination in wireless networks, particularly in challenging indoor environments. Moreover, the initiating device may dynamically select the best transmit and receive chains as the initiating device ranges with different responding devices in various directions and orientations.

This document describes techniques and systems to detect and localize NLOS objects using multipath radar reflections and map data. In some examples, a processor of radar system can identify a detection of an object using reflected EM energy and determine, using map data, whether a direct-path reflection associated with the detection is within a roadway. In response to determining that the direct-path reflection is not located within the roadway, the processor can determine whether a multipath reflection (e.g., a multipath range and multipath angle) associated with the detection is viable. In response to determining that the multipath reflection is viable, the processor can determine that the detection corresponds to an NLOS object. The processor can also provide the NLOS object as an input to an autonomous or semi-autonomous driving system of the vehicle, thereby improving the safety of such systems.

Techniques are disclosed for determining an object's location by using a Reconfigurable Intelligent Surface (RIS) to aid in RF sensing. Radar techniques can be used in which one or more base stations act as a transmitter and a receiving device acts as a receiver in a bistatic or multi-static radar configuration where an RIS directs signals transmitted by the one or more base stations to the receiving device. By comparing the time a line-of-sight (LOS) signal (redirected to the receiving device by the RIS) is received by the receiving device with that of an echo signal (redirected to the receiving device by the RIS) from a reflection of an RF signal from the object, a position of the object can be determined. Depending on desired functionality, this position can be determined by the receiving device or by a location server or other network entity.