Disclosed in the embodiments of the present application are a non-line of sight (NLOS) elimination method and device for a time of arrival (TOA) measurement value, and a terminal. The method includes: modeling the probability density of the TOA measurement value of each base station arriving at a terminal into a Gaussian mixture model, and performing selection and NLOS identification on the TOA measurement value subsequent to performing Gaussian mixture modeling, so as to obtain an identification tag, wherein the identification tag is used for indicating whether the selected TOA measurement values correspond to NLOS; and correcting the selected TOA measurement value according to the identification tag, so as to eliminate an error caused by NLOS in the selected TOA measurement value. The present invention improves the positioning accuracy of a user by performing Gaussian mixture modeling and selection on the probability density of each TOA measurement value, accurately finding the TOA measurement value corresponding to LOS is ensured that in the case that the LOS is aliased with the NLOS, and correcting the selected TOA measurement value to eliminate the error caused by the NLOS in the selected TOA measurement value.

Satellites in a non-terrestrial network may provide positioning reference signals (PRS) to user equipment (UE), with which the UE may determine its position using propagation delay difference measurements, such as Time Difference of Arrival (TDOA) measurement. Due to the large distances between satellites and the UE, the propagation delay differences in the PRS received from satellites may exceed half a radio frame, resulting in a frame level timing ambiguity in the differential measurements. The satellites transmit secondary PRS, along with primary PRS, that include timing information to resolve frame level timing ambiguity of the primary PRS. The positioning occasions in the secondary PRS, for example, may be aligned with corresponding positioning occasions primary PRS within each radio frame, and are transmitted with a periodicity that is an integer multiple (greater than 1) of that of the primary PRS to resolve the frame level timing ambiguity of the primary PRS.

Disclosed are techniques for wireless communication. In an aspect, a band-pass filter of a radio frequency front end (RFFE) of a user equipment (UE) receives an analog radio frequency (RF) signal having a first bandwidth associated with a first sampling rate, the analog RF signal comprising a positioning reference signal (PRS). An analog-to-digital converter (ADC) of the UE samples the analog RF signal at a second sampling rate to generate a digital RF signal representing the analog RF signal, wherein the ADC operates at a second bandwidth lower than the first bandwidth, and wherein the second sampling rate is lower than the first sampling rate by an inverse of a folding factor for the first bandwidth. The digital RF signal is then output to a baseband processor of the UE.

According to one aspect of the disclosure, a location node configured to communicate with a wireless device is provided. The location node includes processing circuitry configured to: receive spatial information; determine the wireless device relationship between a first reference station and a second reference station based at least in part on the spatial information; compare a first integer ambiguity level of the first reference station with a second integer ambiguity level of the second reference station, the second reference station corresponding to a current reference station of the wireless device; and transmit an indication of an applicability of the first integer ambiguity level of the first reference station to the second integer ambiguity level of the second reference station for position estimation, the indication being based on the comparison of the first integer ambiguity level with the second integer ambiguity level.

Systems, methods, apparatuses, and computer program products for user equipment (UE)-based positioning non-line of sight (NLOS) error mitigation. For example, some embodiments described herein may provide for use of a blind-learning-type algorithm for channel bias distribution estimation for UE-based positioning. The UE may perform a calculation of a positioning of the UE using NLOS bias distribution received from a network node, as described elsewhere herein.

An apparatus, computer program and method is described comprising: obtaining, at a receiver, during a first phase of operation, one or more first downlink positioning reference samples from each of a plurality of communication nodes of a mobile communication system, wherein the receiver operates in a wide-beam or omnidirectional mode during the first phase of operation; determining first response estimates of channels between the receiver and each of said each communication nodes, based on the positioning reference samples obtained for the respective communication node; selecting, for each communication node, a receiver beam for receiving positioning signals from the respective communication node, based, at least in part, on the respective first channel response estimate; and receiving, at the receiver, in a second phase of operation, one or more second downlink positioning reference samples from each of the plurality of communication nodes using the selected receiver beams.

In an aspect, a UE receives a set of tracking reference signal (TRS) configurations associated with a respective set of cells, and performs a set of spatial measurements associated with a set of TRSs on resources configured by the respective set of TRS configurations. In a further aspect, a cell (e.g., a serving cell of the UE or a non-serving cell of the UE) determines a TRS configuration, and transmits, to the UE in association with a spatial measurement procedure, a TRS on at least one resource configured by the TRS configuration.

A method of monitoring a kinematic state of an unmanned aerial vehicle (UAV) is provided. The method comprises obtaining one or more predicted pathlosses between a UAV and one or more base stations at a first time instance, wherein the predicted pathlosses are determined using an estimate of a kinematic state of the UAV at the first time instance and one or more pathloss models developed using a machine-learning process. The method further comprises obtaining one or more measurements of a pathloss between each of the one or more base stations and the UAV at the first time instance, and re-determining the estimate of the kinematic state of the UAV at the first time instance based on the one or more predicted pathlosses and the one or more measurements of the pathloss.

Techniques are provided for positioning of user equipment (UE) with paging messages. An example method for positioning a user equipment with paging messages includes receiving a positioning paging message with a user equipment in an idle state, measuring positioning measurements in response to receiving the positioning paging message, determining location information based at least in part on the positioning measurements, and transmitting the location information via a random access procedure.

According to embodiments of the present disclosure, a PRS transmission timing scheme for sidelink assisted positioning is proposed. According to embodiments of the present disclosure, the supporting terminal device measures a receiving-transmitting (Rx-Tx) time difference between receiving the downlink PRS (DL) and transmitting the sidelink (SL) PRS. The supporting terminal device transmits an indication of the RX-TX time difference to the location management device in order to reduce the impact of low synchronization issue on positioning performance as well as the use of wideband PRS for higher measurement accuracy. In this way, the positioning performance of sidelink assisted positioning has been improved.