Head-mounted augmented reality (AR) devices can track pose of a wearer's head or pose of a hand-held user input device to enable wearer interaction in a three-dimensional AR environment. A pose sensor (e.g., an inertial measurement unit) in the user input device can provide data on pose (e.g., position or orientation) of the user input device. An electromagnetic (EM) tracking system can also provide pose data. For example, the handheld user input device can include an EM emitter that generates an EM field, and the head-mounted AR device can include an EM sensor that senses the EM field. The AR device can combine the output of the pose sensor and the EM tracking system to reduce drift in the estimated pose of the user input device or to transform the pose into a world coordinate system used by the AR device. The AR device can utilize a Kalman filter to combine the output of the pose sensor and the EM tracking system.

The invention relates to a method and a system for position determination of at least one object, in particular inside a building. In a method for position determination of at least one object, at least four transmitters transmit circularly polarized signals and a receiver to be localized receives the circularly polarized signals. At least two and in particular all transmitters transmit periodic signals of different frequencies, these frequencies being closely adjacent.

A user equipment (UE) generates a positioning state information (PSI) report to be transmitted in a lower layer channel, e.g., in the Physical or Medium Access Control channel, to a network entity to reduce latency. The PSI reports may be generated based on information from uplink (UL), downlink (DL) or UL and DL positioning measurements performed by the UE. When multiple PSI reports collide, e.g., to be transmitted simultaneously, or when a PSI report and a Channel State Information (CSI) report collide, prioritization of the reports is performed using priority rules based at least in part on positioning related content of the PSI reports. The PSI report or CSI report with the highest priority is transmitted to the network entity on the lower layer channel, and lower priority reports may be omitted. A network entity may receive and process the PSI report based on the priority based rules.

A method, performed in a wireless device, for obtaining position information of user equipment, UE, in a wireless communication system is described. The method includes transmitting, to a network, an indication comprising beam information defining beams that are suitable to be used for transmitting Positioning Reference Signals, PRS, to the wireless device, receiving, from the network, control signaling comprising PRS scheduling information for upcoming transmission of the PRS in beams, performing measurements on the PRS based on the PRS scheduling information that was received, and providing the measurements to the network.

An apparatus including multiple antennas and means for converting measurements of time of arrival of a positioning reference signal at the multiple antennas to a compensation value and using the compensation value to produce a compensated time of arrival measurement for the positioning reference signal. The apparatus also includes means for providing compensated time of arrival measurements for a plurality of positioning reference signals from different reference points to enable positioning of the apparatus.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, an assisting node in a cellular positioning system may obtain one or more carrier phase measurements. The assisting node may transmit, and a positioning node in the cellular positioning system may receive, phase error related information associated with the one or more carrier phase measurements. Numerous other aspects are described.

Disclosed are techniques for wireless communication. In an aspect, a position estimation entity determines a set of position estimates associated with a set of user equipments (UEs), obtains first measurement information associated with a set of signals as reflected off of a target intelligent reflecting surface (IRS), determines a position estimate of the target IRS based on the set of position estimates and the first measurement information, and determines an orientation, relative to a common orientation reference frame, of the target IRS based on the set of position estimates and at least the first measurement information.

Disclosed are techniques for wireless communication. In an aspect, a position estimation entity determines a set of position estimates associated with a set of user equipments (UEs), obtains first measurement information associated with a set of signals as reflected off of a target intelligent reflecting surface (IRS), determines a position estimate of the target IRS based on the set of position estimates and the first measurement information, and determines an orientation, relative to a common orientation reference frame, of the target IRS based on the set of position estimates and at least the first measurement information.

This disclosure provides methods, devices, and systems for beam group reporting for positioning in new radio (NR) wireless communications systems. In some wireless communications systems, multiple PRS resources, e.g., a beam group, received by a user equipment (UE) from the same network entity may be used to produce a combined Time of Arrival (TOA) measurement for the reference or target to derive an Reference Signal Time Difference (RSTD) estimate. The UE provides to a network entity an indication of the PRS resources in the beam group, which may be specifically or generally identified. Additionally, parameters associated with the beam group are provided, such as a relative quality of the TOA measurement for each PRS resource in the subset, a spread of the TOA measurements in the subset, a relative signal strength of each PRS resource in the subset, or a spread of the signal strength in the subset.

An internet of things is disclosed, comprising plural SDR receivers and possibly a centralised system, where one or more of the receivers may be mobile. The internet of things thus allows for a very large proportion of RF signals present within a city, for example, to be monitored and analysed for the purpose of identifying, tracking and/or preventing criminal behaviour. The receivers may be equipped with secure SDRs for increased security and privacy and the system preferably includes artificial intelligence using machine learning technology, for increased adaptability among others. The system is flexible due to the programmability of the SDRs.