Qualcomm Incorporated

Smithkline Beecham Corporation

Other

Redcoat Solutions, Inc.

Deere & Company

Alere Switzerland Gmbh

Technology Transfer, Inc.

Texas Instruments Corporation

Sharp Corporation

Atheros Communications, Inc.

Inverness Medical Switzerland Gmbh

Navcom Technology, Inc.

Coppergate Communications Ltd.

Qualcomm Atheros Inc.

Sigma Designs Israel S.d.i. Ltd.

Min Wang

Deborah Dee Jaworski

Richard Lloyd Warren

Christopher Michael Traini

Ning Luo

Gengsheng Zhang

Lisa Kathleen Shilling

Xipeng Zhu

Michael Terence Black

Tom Chin

Martin M Rosenberg

Judith M Ward

John Edward Hodgson

Nikolai Konrad Leung

James Raymond Brown

David John Holmes

Kuo-Chun Lee

Masato Kitazoe

Elizabeth Jane Lawlor

Ralph Akram Gholmieh

Shyamal Ramachandran

Nicola Gail Wallis

Leslie Marie Palmer

Karen Anne Ingraham

Gavin Bernard Horn

Srinivasan Balasubramanian

Arvind Vardarajan Santhanam

Michael Arthur Lonetto

Richard Oakley Nicholas

Charles Nung Lo

Magdalena Zalacain

Sanjoy Biswas

Sivaramakrishna Veerepalli

Imed Bouazizi

Martin Karl Russel Burnham

Liwen L Dai

David Justin Charles Knowles

Lenaig Genevieve Chaponniere

Ajith Tom Payyappilly

Ananthapadmanabhan Arasanipalai Kandhadai

Raymond Winfield Reichard

Mangesh M Chansarkar

Julie M Pratt

Vikram Singh

Umesh Phuyal

Arnaud Meylan

Haris Zisimopoulos

Thomas Stockhammer

Amir Aminzadeh Gohari

Leena Zacharias

Vivek Rajendran

Han Zhang

Carlos Marcelo Dias Pazos

Martin Karl Burnham

Sanjay Vishin

Alberto Rico Alvarino

Aleksandar Damnjanovic

Ozcan Ozturk

Rajat Prakash

Linhai He

Sai Yiu Duncan Ho

Aziz Gholmieh

Madhavan Srinivasan Vajapeyam

Liangping Ma

Muhammed Zeyd Coban

Peng Cheng

Joseph R Zbiciak

Brian Clarke Banister

Sitaramanjaneyulu Kanamarlapudi

Prasad Reddy Kadiri

Rashid Ahmed Akbar Attar

Jingchao Bao

Lawrence W Yonge, Iii

Venkatraman Atti

Srinivas Katar

Yu-Cheun Jou

Yong He

Thomas Klingenbrunn

Arungundram C Mahendran

Qingxin Chen

Juan Zhang

Supratik Bhattacharjee

Luis Fernando Brisson Lopes

Suli Zhao

Nan Zhang

Ravindra Manohar Patwardhan

Nagaraju Naik

Arvind Swaminathan

Osama Lotfallah

Huichun Liu

Louis Joseph Kerofsky

Ramachandran Subramanian

Ronald R Hatch

Zoltan F Biacs

Deepak V Ayyagari

Sherman Leon Gavette

David J Hoyle

Chih-Ping Hsu

Daniel Robert Gentry

David Justin Knowles

An integer ambiguity resolution method includes: receiving SPS signals; determining, for the SPS signals, candidate float ambiguity values indicative of float numbers of carrier signal wavelengths of the SPS signals between respective satellite sources, of the SPS signals, and the mobile device; and performing, in response to failure of an integer ambiguity resolution validation check based on at least a first subset of the candidate float ambiguity values, an integer ambiguity search using at least a second subset of the candidate float ambiguity values; wherein each candidate float ambiguity value of the at least second subset of the candidate float ambiguity values corresponds to a second indication of candidate float ambiguity accuracy that is higher than a first indication of candidate float ambiguity accuracy, if any, corresponding to the at least first subset of the candidate float ambiguity values.

Carrier signal positioning

In an aspect, a user equipment (UE) receives a spoofing alert message from either a server or an internet-of-things (IOT) device that indicates whether a spoofed Global Navigation Satellite System (GNSS) condition is present. Based on determining that the spoofing alert message indicates that a spoofed GNSS condition is present, the UE determines, based on the spoofing alert message, a location of a spoofer broadcasting a spoofed GNSS signal, determines, based on the location of the spoofer and a current location of the UE, that the UE is within a receiving area of the spoofed GNSS signal, and determines a position of the UE without using the spoofed GNSS signal.

Detecting spoofed global navigation satellite system (GNSS) signals

Systems and techniques are provided for determining positioning. For example, the systems and techniques can include obtaining an inertial height measurement, wherein the inertial height measurement is obtained based on a determination that one or more positioning signals are unavailable. A height constraint can be generated using the inertial height measurement, wherein the height constraint is generated based at least in part on a transition matrix. One or more positioning measurements can be determined based on using the height constraint as a real-time kinematic (RTK) positioning input.

Kinematic positioning with inertial constraints

A mobile device supports carrier phase based positioning using positioning signals received from positioning signals from a plurality of satellites in a satellite positioning system (SPS). In the presence of a discontinuous carrier phase, e.g., if a cycle slip is detected, the mobile device is configured to generate a continuous carrier phase using the device history of the mobile device. The mobile device, for example, may track the carrier phase of positioning signals and determine a position estimate for the mobile device at a first time. If a cycle clip of the carrier phase is detected at a second time, the mobile device resolves the integer ambiguity in the carrier phase at the second time based on the carrier phase and position estimate for the mobile device from the first time.

Methods and apparatus for carrier phase continuity in satellite positioning system signals

In some implementations, a global navigation satellite system (GNSS) device may determine a plurality of position estimates of the GNSS device for a plurality of epochs spanning a period of time beginning with a first epoch and ending with a second epoch. The GNSS device may determine position change values comprising a position change value of the GNSS device for each successive epoch of the plurality of epochs based at least in part on delta carrier phase (DCP) values for the plurality of epochs. The GNSS device may perform backward smoothing on the plurality of position estimates, modifying at least a portion of the plurality of position estimates based at least in part on the position estimate of the second epoch and the position change values. The GNSS device may output information indicative of at least a portion of the modified position estimates of the GNSS device.

Simplified precise positioning engine (PPE) backward smoothing

An integer ambiguity validation method includes: obtaining, at an apparatus in conjunction with the one or more receivers, a plurality of feature values that are based on satellite signals received by a mobile device; determining, at the apparatus, an integer ambiguity vector indicative of integer numbers of carrier phase cycles of the satellite signals between the apparatus and respective satellites; determining, at the apparatus, a probability of the integer ambiguity vector being correct by using the integer ambiguity vector in a machine learning algorithm; and determining, at the apparatus, whether the integer ambiguity vector is correct based on the probability of the integer ambiguity vector being correct and an integer ambiguity vector probability threshold.

Integer ambiguity validation with machine learning

Aspects presented herein may enable a UE to reduce sensor initialization time for one or more sensors that are to be used for DR positioning during a GNSS signal outage. In one aspect, a UE initiates a first positioning engine based on an availability of a GNSS signal, where the first positioning engine measures a relative position of the UE without ambiguity processing. The UE calibrates at least one IMU sensor based on the relative position of the UE measured by the first positioning engine. The UE performs a positioning calculation of the UE via the at least one IMU sensor in response to the GNSS signal being unavailable.

Fast sensor initialization

Aspects presented herein may improve the performance and accuracy of RF-based positioning. Aspects presented herein may enable a device to use RF Doppler measurements to detect and mitigate multipath effects in RF-based positioning. The RF-based positioning may include satellite navigation, terrestrial positioning system, and/or indoor positioning. In one aspect, a UE receives, via a receiver, signals from one or more entities. The UE determines whether each received signal is a multipath signal based on a Doppler shift measurement. The UE de-weights or excludes one or more signals of the received signals in estimating a position of the UE based on whether the respective received signal is determined to be a multipath signal.

Using doppler for multipath detection and mitigation in RF-based positioning

Aspects presented herein may improve the positioning accuracy and latency of a positioning engine that receives at least one position constraint for assisting the positioning. A wireless device obtains an indication of at least one position constraint for a positioning engine. The wireless device detects whether the at least one position constraint exceeds an error threshold based on a set of PR residuals between the wireless device and at least one satellite. The wireless device excludes the at least one position constraint from a calculation at the positioning engine if the at least one position constraint exceeds the error threshold, or includes the at least one position constraint in the calculation at the positioning engine if the at least one position constraint is below the error threshold.

Precise positioning engine

An example method performed at a mobile device for determining a position may comprise receiving correction data associated with (1) a first pseudorange measurement of a first GNSS signal sent from a satellite vehicle on a first GNSS carrier frequency and (2) a second pseudorange measurement of a second GNSS signal sent from the satellite vehicle on a second GNSS carrier frequency. The method also may comprise measuring a third GNSS signal sent from the satellite vehicle and received at the mobile device on a third GNSS carrier frequency, to generate a third pseudorange measurement. The method also may comprise determining the position of the mobile device using (a) the third pseudorange measurement of the third GNSS signal on the third GNSS carrier frequency and (b) the correction data associated with the first pseudorange measurement and the second pseudorange measurement.

Cross-frequency correction for precise positioning

Described are methods, systems, and devices for correcting ionospheric error. In some aspects, a mobile device equipped with a Global Navigation Satellite System (GNSS) receiver is configured to determine a positioning measurement of a GNSS signal. The mobile device is further configured to receive augmentation data from an augmentation system. When the mobile device is unable to obtain newer augmentation data, the mobile device can instead obtain augmentation data associated with historical Total Electron Content (TEC) values. In such instances, the augmentation data will have been generated to represent ionospheric delay during a time period that ended before the augmentation data is obtained. Based on the augmentation data associated with historical TEC values and a pierce point of the received GNSS signal, an ionospheric error in the positioning measurement of the GNSS signal can be determined and corrected.

Ionosphere grid history and compression for GNSS positioning

A tracking module processes the determined correlations to track a carrier of the received composite signal for estimation of a change in phase over a time period between a receiver antenna and one or more satellite transmitters that transmit the received signal as the receiver changes position with respect to an initial position during the time period. A relative position estimator estimates the relative position of the navigation receiver with respect to an initial position over the time period time by time-differencing of the phase measurements of the one or more tracked carrier signals. Bias estimators can estimate or compensate for errors in initial position and temporal changes in receiver clock and tropospheric delay.

Satellite navigation receiver for relative positioning with bias estimation

System and method embodiments for analyzing a test fluid to detect prior or present infestations of bed bugs are described. In an embodiment, the method may include receiving the test fluid on a test strip within the detection device. The test strip may include a reaction portion and a reagent portion containing an antibody or antigen-binding fragment that is conjugated to a colored particle. The test fluid may include bed bug antigen that reacts with the conjugated antibody. The detection device may include a first and a second optical sensor for monitoring a reaction and a background color intensity, respectively. Upon a predetermined time delay elapsing, the detection device determines whether bed bug antigen is present in the test fluid using the monitored color intensities and minimum and maximum color intensity thresholds associated with bed bugs. Then, the detection device outputs a result using a visual display.

Bed bugs detection device

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may identify that the UE is operating in a dual-connectivity configuration with a master node (MN) and a secondary node (SN). The UE may receive at least one request that the UE report MDT measurements. The UE may perform a first portion of measurements associated with the first base station and perform a second portion of measurements associated with the second base station. The UE may perform the measurements while the UE is operating in the dual-connectivity configuration. The UE may transmit one or more reports including information indicative of the first portion of measurements, information indicative of the second portion of measurements, or both.

Minimization of drive test for dual connectivity

Growing community of inventors

San Diego, CA, United States of America

Min Wang