Qualcomm Incorporated

Eride,. Inc.

Seiko Epson Corporation

William J Morrison

Wyatt Thomas Riley

Joseph Czompo

Jie Wu

Benjamin A Werner

Gautam Nirula

Dominic Gerard Farmer

Paul W McBurney

Ning Luo

Himanshu H Shah

Bo Zheng

Vinod Kumar Saini

Songwon Jee

Ming Sun

Krishnaranjan Rao

Abdelmonaem Lakhzouri

Tong Lin

Kenneth U Victa

Vesa Veikko Ruuska

Tao Jia

Justin A Vandegrift

Hsiao Chien Liang

Guttorm Ringstad Opshaug

Han Zhang

Ashok Bhatia

Murray Robert Jarvis

Grant Alexander Marshall

Chandrakant Mehta

Lalitaprasad Daita

Benjamin Tarlow

Yuhua Hu

Vivek Sankaravadivel

Yunxiang Liu

Neha Nagori

A mobile device in a moving vehicle initializes a Global Navigation Satellite System (GNSS)—Inertial Navigation System (INS) system while the vehicle is in-motion with the orientation of the mobile device with respect to a global reference frame. The mobile device uses gyroscope measurements made while the vehicle is turning to determine a gravity vector. The gravity vector and accelerometer measurements may be used to determine a forward vector for the mobile device. A north vector is determined using the GNSS measurements. After the GNSS-INS system is calibrated, the mobile device may be positioned with respect to the vehicle. The orientation of the mobile device, prior to repositioning, may be compared to a current orientation, determined while the vehicle is in motion, in order to determine whether the GNSS-INS system should be re-initialized.

Method and apparatus for in motion initialization of global navigation satellite system—inertial navigation system

A method being for facilitating positioning determination of a UE includes: obtaining motion information indicative of motion of the UE; obtaining positioning information based on positioning signals received by the UE; determining a validity status of map data based on whether the positioning information, the motion of the UE, and the map data, that include locations of physical environmental features, are consistent, wherein the validity status is determined to be valid in response to the positioning information, the motion of the UE, and the map data being consistent; and determining at least one of a position estimate for the UE, or a direction of motion of the UE, based on the map data and based on the validity status being valid.

Validating and using map data for positioning

Aspects presented herein may enable a positioning device or entity to perform PR measurement error detection and classification based on SV geometry via ML. In one aspect, a UE or a location server determines for each SV of a set of SVs at least a geometric orientation with respect to the UE. The UE or the location server determines, based on an ML classifier and the determined geometric orientation with respect to the UE for each SV of at least a subset of the set of SVs, a relative PR weight for each SV of the set of SVs. The UE or the location server estimates a position of the UE based on PR measurements of each SV of the set of SVs and the relative PR weight for each SV of the set of SVs.

Space vehicle geometry based machine learning for measurement error detection and classification

Aspects presented herein may improve the performance and accuracy of GNSS-based positioning, where a position-grid based ML may be implemented by a UE or a location server to improve the accuracy of identifying a warm-start position of the UE. In one aspect, a UE or a location server determines, for each grid point within a range of an initial position of a UE, a set of PR residuals based on PRs for each SV of a set of SVs. The UE or the location server determines an estimated position of the UE based on the sets of determined PR residuals.

Position-grid based machine learning for GNSS warm-start position accuracy improvement

Techniques are provided for determining a location of a mobile device based on visual positioning solution (VPS). An example method for determining a position estimate of a mobile device includes obtaining sensor information, detecting one or more identifiable features in the sensor information, determining a range to at least one of the one or more identifiable features, obtaining coarse map information, determining a location of the at least one of the one or more identifiable features based on the coarse map information, and determining the position estimate for the mobile device based at least in part on the range to the at least one of the one or more identifiable features.

Position accuracy using sensor data

Aspects presented herein may improve the performance of positioning devices by enabling the positioning devices to utilize transformed map data with limited third party knowledge of the transformation. Aspects presented herein may enable a positioning device to make the map data from another coordinate system usable for positioning algorithms without knowledge of the transformation. In one aspect, a UE transmits a request for map data based on a first set of coordinates in a first coordinate system. The UE receives the map data based on a second set of coordinates in a second coordinate system, where the first set of coordinates in the first coordinate system is distinct from the second set of coordinates in the second coordinate system. The UE calculates a set of relative distances between the second set of coordinates and one or more objects corresponding to the map data.

Usage of transformed map data with limited third party knowledge

Aspects presented herein may enable an electronic device to determine gyroscope biases and calibrate a gyroscope without a magnetometer or without relying on data generated from a magnetometer. In one aspect, an apparatus estimates a set of gyroscopic biases for a plurality of temperatures or temperature ranges to create a mapping that maps the plurality of temperatures or temperature ranges to the set of gyroscopic biases. The apparatus monitors temperatures of a gyroscope via a gyroscope temperature sensor. The apparatus calibrates the gyroscope in response to the gyroscope changing from a first temperature to a second temperature based on the mapping or based on a predicted value derived from the mapping. In some aspects, the apparatus calculates a DR trajectory of the apparatus based at least in part on the calibrated gyroscope and the accelerometer without using a magnetometer or without using data generated from the magnetometer.

Pedestrian sensor accuracy with minimal dependence on magnetometer

A mobile device in a moving vehicle initializes a Global Navigation Satellite System (GNSS)-Inertial Navigation System (INS) system while the vehicle is in-motion with the orientation of the mobile device with respect to a global reference frame. The mobile device uses gyroscope measurements made while the vehicle is turning to determine a gravity vector. The gravity vector and accelerometer measurements may be used to determine a forward vector for the mobile device. A north vector is determined using the GNSS measurements. After the GNSS-INS system is calibrated, the mobile device may be positioned with respect to the vehicle. The orientation of the mobile device, prior to repositioning, may be compared to a current orientation, determined while the vehicle is in motion, in order to determine whether the GNSS-INS system should be re-initialized.

Method and apparatus for in motion initialization of global navigation satellite system&#x2014;inertial navigation system

Aspects of the disclosure relate to initializing an inertial navigation system (INS) of a mobile device. Accelerometer bias of a plurality of accelerometers of the mobile device, and gyroscope bias of a plurality of gyroscopes of the mobile device, are determined. A first spatial relationship between a first frame of reference of the mobile device and a second frame of reference of a vehicle transporting the mobile device is determined. A second spatial relationship between the first frame of reference and a third frame of reference of a surface beneath the vehicle is determined. Each of the frames of reference are determined based on output of at least two of the GNSS receiver, the plurality of accelerometers, or the plurality of gyroscopes. The INS is provided with the accelerometer bias, the gyroscope bias, the first spatial relationship, and the second spatial relationship to initialize the INS.

Correction of motion sensor and global navigation satellite system data of a mobile device in a vehicle

A UE includes: at least one sensor configured to provide at least one sensor measurement; and a processor configured to: determine first and second ranges between the UE and a positioning signal source based on first and second positioning signal measurements of first and second positioning signals from the positioning signal source corresponding to first and second times; determine whether a selected range of the first range or the second range is a multipath range based on the first range, the second range, and movement of the UE between the first time and the second time indicated by the at least one sensor measurement; and discount use of the selected range in a positioning technique in response to the selected range being determined to be a multipath range.

Multi-path positioning signal determination

Techniques are provided which may be implemented using various methods and/or apparatuses in a mobile GNSS device to compensate for arm swing. An example of an method for compensating for arm swing according to the disclosure includes determining an arm swing signal, such that the arm swing signal is approximately sinusoidal with a period of approximately T seconds, determining a position signal measurement period, receiving a plurality of positioning signals at intervals corresponding to the position signal measurement period, and determining current position information based on the plurality of positioning signals.

Arm swing compensation techniques

Disclosed embodiments facilitate accuracy and decrease error in terrestrial positioning systems, including errors induced by multipath (e.g. ground reflections) in doppler based measurements of SVs. In some embodiments, one or more Global Navigation Satellite System (GNSS) doppler measurements and one or more corresponding GNSS pseudorange measurements for one or more satellites may be obtained. One or more GNSS doppler estimates corresponding to the one or more GNSS doppler measurements may be determined, wherein for a GNSS doppler measurement, the corresponding GNSS doppler estimate may be determined based, in part, on the GNSS doppler measurement and a GNSS pseudorange measurement corresponding to the GNSS doppler measurement. A speed of the UE may be determined based, in part, on the one or more GNSS doppler estimates.

Error mitigation in doppler based satellite positioning system measurements

Certain aspects of the present disclosure generally relate to magnetometer calibration. In some aspects, a device may obtain multiple sets of magnetic field measurements corresponding to multiple local magnetic field strengths, wherein each set of magnetic field measurements is measured in association with an unknown local magnetic field strength. The device may calculate multiple error values using the multiple sets of magnetic field measurements, estimated values of the multiple local magnetic field strengths, and estimated hard iron bias values. The device may identify a set of hard iron bias values for magnetometer calibration based at least in part on comparing the multiple error values. The device may calibrate a magnetometer using the identified set of hard iron bias values.

Techniques for magnetometer calibration using selected measurements over time

Techniques provided herein are directed toward enabling on-device learning to create user-specific movement models that can be used for dead reckoning. Because these moving models are user-specific, they can be later used to identify user-specific motions in a manner that provides for a dead reckoning location estimation. In some embodiments, these models can be focused on pedestrian movement, based on the repetitive motion that occurs when a user takes a stride (walking, jogging, running, etc.) or other repetitive motion (swimming, riding a horse, etc.).

Growing community of inventors

San Diego, CA, United States of America

William J Morrison