Abstract: A wireless device includes a satellite receiver to receive data from multiple satellites. The wireless device also includes processing circuitry and memory. The memory stores one or more neural network models. The processing circuitry is operative to identify a neural network model that has been trained to adapt to a region in which the wireless device operates, classify satellite raw measurements from each satellite at a given time into a corresponding quality level using the neural network model, and identify satellite raw measurements with a quality level higher than a threshold. The location of the wireless device is calculated using the identified satellite raw measurements.

Abstract: Techniques are provided for non-linear satellite state modeling. First global navigation satellite systems (GNSS) signal data is obtained from a set of GNSS satellites. First satellite state data is obtained. The first satellite state data includes orbit data for the set of GNSS satellites. A non-linear satellite state model that includes a plurality of model parameters is generated. The non-linear satellite state model is generated by adjusting the plurality of model parameters based on the first GNSS signal data and the first satellite state data. The non-linear satellite state model outputs satellite state data based on GNSS signal data. Second GNSS signal data is obtained from the set of GNSS satellites. A set of updated satellite state data is calculated using the non-linear satellite state model and the second GNSS signal data.

Abstract: A method for creating a correction function for improving the accuracy of a GPS device collects multiple time samples at multiple known locations wherein each time sample consists of GPS coordinates and associated satellite data from multiple satellites. The satellite data includes or permits determination of (i) satellite azimuth and elevation of an associated satellite, (ii) Signal-to-Noise Ratio of a received signal from the associated satellite, and optionally (iii) pseudo-range. For each time sample a respective error between the known location and the corresponding GPS coordinates is computed and an error correction function is created as a function of the respective GPS coordinates and the satellite data by applying deep learning/machine learning techniques to the multiple time samples.

Abstract: In one embodiment, a method includes accessing global positioning system (GPS) data indicating a raw location associated with the computing system; accessing, based on the raw location, environmental model data including one or more structures; generating GPS correction data by processing the GPS data and the environmental model data using a machine-learning (ML) model that has been trained to compensate inaccurate GPS readings due to environmental interference; and determining an accurate location by correcting the raw location using the GPS correction data.

Abstract: A device receives sensor data for a group of user equipment (UE) that are located within or on a structure. The device determines, based on a set of measured barometric pressures identified by the sensor data, a set of relative altitudes that identify altitudes of the group of UEs relative to each other. The device determines, based on at least a portion of the sensor data and relative altitude data that identifies the set of relative altitudes, and for each UE of the group of UEs, a floor on which the UE is located. The device causes, based on determining respective floors on which the UEs of the group of UEs are located, a data structure to store a mapping of each UE to the respective floors. The device performs one or more actions based on the mapping.

Abstract: A device receives sensor data for a group of user equipment (UE) that are located within or on a structure. The device determines, based on a set of measured barometric pressures identified by the sensor data, a set of relative altitudes that identify altitudes of the group of UEs relative to one or more known geographic locations. The device determines, based on at least a portion of the sensor data and relative altitude data that identifies the set of relative altitudes, and for each UE of the group of UEs, a floor on which the UE is located. The device causes, based on determining respective floors on which the UEs of the group of UEs are located, a data structure to store a mapping of each UE to the respective floors. The device performs one or more actions based on the mapping.

Abstract: An intrabuilding location estimating apparatus and a method thereof are provided. The method includes operations of measuring a user's location by using a global positioning system (GPS) or a wireless communication-based location obtaining device in the mobile terminal, obtaining interfloor movement information of the user that is detected via a sensor in the mobile terminal, and determining a floor on which the user is located, via map information and the interfloor movement information of the user.

Abstract: Systems and methods are described for determining position of a receiver. The positioning system comprises a transmitter network including transmitters that broadcast positioning signals. The positioning system comprises a remote receiver that acquires and tracks the positioning signals and/or satellite signals. The satellite signals are signals of a satellite-based positioning system. A first mode of the remote receiver uses terminal-based positioning in which the remote receiver computes a position using the positioning signals and/or the satellite signals. The positioning system comprises a server coupled to the remote receiver. A second operating mode of the remote receiver comprises network-based positioning in which the server computes a position of the remote receiver from the positioning signals and/or satellite signals, where the remote receiver receives and transfers to the server the positioning signals and/or satellite signals.

Abstract: A geospatial object property assessment apparatus comprises a processing resource (102) arranged to support a geospatial object property processor (206) comprising a subject data source input (212) capable of receiving a first metadata associated with 10 quality of current source information content used to define a property (408) of a geospatial object; a resource data source input (214) capable of receiving a second metadata associated with quality of candidate resource information content for updating the definition of the property (408) of the geospatial object.

Abstract: A prediction method that estimates the real-time position of a mobile device based on previously observed data is provided. The present invention can be used in real-time navigation, including providing real-time alerts of an upcoming destination and notifications of emergency events in close geographic proximity. The prediction method utilizes neural networks and/or functions generated using genetic algorithms in estimating the mobile device's real-time position. The prediction method provides reliable Location-Based Services (LBS) in events where traditional positioning technologies become unreliable. It is also seamless, as the user remains unaware of any interruption in accessing the positioning technology.

Abstract: In certain embodiments, the system of the invention automatically replicates a user's personal computing environment and provides associated remote server access using authentication credentials and data files supplied by a local handheld device as coordinated by session level software common to the handheld device, the replicated system, the system on which the replication occurs, and the remote servers. The application enables a handheld computing device to transfer a user's various online account credentials to a user's other computing devices securely and automatically. Thereafter the other computing device accesses a user's cloud-based storage and various on-line accounts and also pulls selected documents, bookmarks and related information directly from a user's handheld.

Abstract: An exemplary method includes a content hub subsystem receiving a content posting from an access device connected to a wireless network and associated with a first user. The content posting includes data representative of a content instance and a geographic location associated with the content instance. The exemplary method further includes the content hub subsystem storing the content posting and selectively distributing the content instance to at least one other access device connected to the wireless network based on the geographic location, the at least one other access device associated with a second user. A past or present physical location of the at least one other access device within a predefined proximity of the geographic location is requisite to the distribution of the content instance to the at least one other access device. Corresponding methods and systems are also disclosed.

Abstract: A prediction method that estimates the real-time position of a mobile device based on previously observed data is provided. The present invention can be used in real-time navigation, including providing real-time alerts of an upcoming destination and notifications of emergency events in close geographic proximity. The prediction method utilizes neural networks and/or functions generated using genetic algorithms in estimating the mobile device's real-time position. The prediction method provides reliable Location-Based Services (LBS) in events where traditional positioning technologies become unreliable. It is also seamless, as the user remains unaware of any interruption in accessing the positioning technology.

Abstract: A navigation device and computer implemented method for predicting the destination of a trip, the method being executed by a navigation device, the method comprising the steps of: determining starting parameters, the starting parameters comprising at least the starting point, starting time and date of the trip, executing a destination prediction algorithm, the destination prediction algorithm taking the starting parameters as input and predicting a destination, wherein the destination prediction algorithm is generated by using information of a trip history; determining, upon arrival at the predicted or another destination, the actual destination.

Abstract: An auxiliary satellite positioning system is applied to a first satellite positioning apparatus. The auxiliary positioning system includes a detection module, a transmission interface and a positioning module. A second satellite positioning module having a satellite data can be detected by the detection module via a wireless transmission protocol. The satellite data can be transmitted by the transmission interface to the first satellite positioning module from the second satellite positioning module. The satellite data can be used by the positioning module to implement a satellite positioning action.