Provided herein is a method of performing, by a first apparatus, wireless communication. The method may include the steps of receiving configuration related to a downlink (DL) positioning reference signal (PRS) from a location management function (LMF); receiving configuration related to an uplink (UL) PRS from a base station; and performing positioning based on round trip time (RTT), based on the configuration related to the DL PRS and the configuration related to the UL PRS.

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.

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.

Embodiments provide for guided alignment of the orientation of two wireless devices. A first wireless device is at a known position and a known orientation. A signal from a second wireless device is received via a plurality of receive elements of the first wireless device. The first wireless device measures phase differences of the signal at the plurality of receive elements, and determines locations of each of the second wireless device's transmit elements based on the differences. Based on the transmit element locations, and a known antenna layout of the second wireless device, an orientation of the second wireless device is determined. Based on differences between the determined orientation and the known orientation of the first wireless device, instructions for aligning the devices are generated. Once the devices are aligned, location estimates of a third wireless device are made by both the first wireless device and the second wireless device.

A subsurface imaging technique using distributed sensors is introduced. Instead of monostatic transceivers employed in conventional ground penetrating radars, the proposed technique utilizes bi-static transceivers to sample the reflected signals from the ground at different positions and create a large two-dimensional aperture for high resolution subsurface imaging. The coherent processing of the samples in the proposed imaging method eliminates the need for large antenna arrays for obtaining high lateral resolution images. In addition, it eliminates the need for sampling on a grid which is a time-consuming task in imaging using ground penetration radar. Imaging results show that the method can provide high-resolution images of the buried targets using only samples of the reflected signals on a circle with the center at the transmitter location.

A subsurface imaging technique using distributed sensors is introduced. Instead of monostatic transceivers employed in conventional ground penetrating radars, the proposed technique utilizes bi-static transceivers to sample the reflected signals from the ground at different positions and create a large two-dimensional aperture for high resolution subsurface imaging. The coherent processing of the samples in the proposed imaging method eliminates the need for large antenna arrays for obtaining high lateral resolution images. In addition, it eliminates the need for sampling on a grid which is a time-consuming task in imaging using ground penetration radar. Imaging results show that the method can provide high-resolution images of the buried targets using only samples of the reflected signals on a circle with the center at the transmitter location.

Disclosed are techniques for receiving reference radio frequency (RF) signals for positioning estimation. In an aspect, a receiver device receives, from a transmission point, a reference RF signal on a wireless channel receives, from a positioning entity, an indication that the reference RF signal serves as a source for a quasi-collocation (QCL) type(s) for positioning reference RF signals received by the receiver device from the transmission point on the wireless channel, measures an average delay, a delay spread, or both the average delay and the delay spread of the reference RF signal based on the QCL type(s), receives, from the transmission point, a positioning reference RF signal on the wireless channel, and identifies a time of arrival (ToA) of the positioning reference RF signal based on the measured average delay, the delay spread, or both the average delay and the delay spread of the reference RF signal.

Disclosed are techniques for receiving reference radio frequency (RF) signals for positioning estimation. In an aspect, a receiver device receives, from a transmission point, a reference RF signal on a wireless channel receives, from a positioning entity, an indication that the reference RF signal serves as a source for a quasi-collocation (QCL) type(s) for positioning reference RF signals received by the receiver device from the transmission point on the wireless channel, measures an average delay, a delay spread, or both the average delay and the delay spread of the reference RF signal based on the QCL type(s), receives, from the transmission point, a positioning reference RF signal on the wireless channel, and identifies a time of arrival (ToA) of the positioning reference RF signal based on the measured average delay, the delay spread, or both the average delay and the delay spread of the reference RF signal.

Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.

Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.