The disclosure provides methods, apparatus, and products for updating a positioning map and a position estimate based on the detection of delivery events. An example method comprises obtaining a delivery address corresponding to a delivery to be made by an entity associated with a mobile device; obtaining sensor data captured by the mobile device; based on processing the sensor data, determining occurrence of one or more events indicating a moment in time that the delivery took place at the delivery address; obtaining (a) a position estimate for the mobile device substantially corresponding to the moment the delivery occurred and/or (b) delivery moment data captured by one or more sensors of the mobile device substantially at the moment the delivery took place; and updating a positioning map and/or the position estimate for the mobile device.

A chip-scale gyrometric apparatus is disclosed. In embodiments, the chip-scale gyrometric apparatus includes a dielectric substrate and an antenna element attached thereto for receiving an inbound signal having an initial phase. The apparatus includes a splitter for splitting the inbound signal into two equivalent signals, and two coils connected to the splitter. The first coil carries one of the split signals in a clockwise (CW) path relative to a rotational axis, while the second coil carries the other split signal in a counterclockwise (CCW) path relative to the same axis. An integrated circuit (IC) on the substrate and connected to the first and second coils measures a phase shift between the first and second signals (e.g., deviation from the initial phase) based on their respective CW and CCW paths and determines, based on the measured phase shift, a degree of rotation relative to the common rotational axis.

A chip-scale gyrometric apparatus is disclosed. In embodiments, the chip-scale gyrometric apparatus includes a dielectric substrate and an antenna element attached thereto for receiving an inbound signal having an initial phase. The apparatus includes a splitter for splitting the inbound signal into two equivalent signals, and two coils connected to the splitter. The first coil carries one of the split signals in a clockwise (CW) path relative to a rotational axis, while the second coil carries the other split signal in a counterclockwise (CCW) path relative to the same axis. An integrated circuit (IC) on the substrate and connected to the first and second coils measures a phase shift between the first and second signals (e.g., deviation from the initial phase) based on their respective CW and CCW paths and determines, based on the measured phase shift, a degree of rotation relative to the common rotational axis.

A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

Disclosed are some examples of techniques for positioning of a user equipment (UE) using positioning reference signal (PRS). One or more units of messages may be communicated between an initiator UE and a responder UE. A unit of message may include a pre-PRS message, a PRS message and a post-PRS message. The pre-PRS message and the post-PRS message may be sent or received using a license spectrum. The PRS message may be sent or received using an unlicensed spectrum. The communication between the initiator UE and the responder UE may be initiated by the initiator UE identifying the responder UE from a plurality of UEs based on positioning properties of the responder UE. The positioning properties of the responder UE may include one or more of a direction, a velocity, a location confidence and a location of the responder UE.

Disclosed are some examples of techniques for positioning of a user equipment (UE) using positioning reference signal (PRS). One or more units of messages may be communicated between an initiator UE and a responder UE. A unit of message may include a pre-PRS message, a PRS message and a post-PRS message. The pre-PRS message and the post-PRS message may be sent or received using a license spectrum. The PRS message may be sent or received using an unlicensed spectrum. The communication between the initiator UE and the responder UE may be initiated by the initiator UE identifying the responder UE from a plurality of UEs based on positioning properties of the responder UE. The positioning properties of the responder UE may include one or more of a direction, a velocity, a location confidence and a location of the responder UE.

A method of determining an integer ambiguity search space includes: obtaining, at an apparatus, a code phase measurement of a satellite vehicle signal comprising a pseudorandom noise code and a carrier signal; obtaining, at the apparatus, spatial information corresponding to a wireless terrestrial signal transferred between the apparatus and a terrestrial base station; determining, at the apparatus, a satellite positioning system carrier phase integer ambiguity search space based on the code phase measurement; and constraining a size of the satellite positioning system carrier phase integer ambiguity search space based on the spatial information.

A method of determining an integer ambiguity search space includes: obtaining, at an apparatus, a code phase measurement of a satellite vehicle signal comprising a pseudorandom noise code and a carrier signal; obtaining, at the apparatus, spatial information corresponding to a wireless terrestrial signal transferred between the apparatus and a terrestrial base station; determining, at the apparatus, a satellite positioning system carrier phase integer ambiguity search space based on the code phase measurement; and constraining a size of the satellite positioning system carrier phase integer ambiguity search space based on the spatial information.

A method of monitoring swimming activity includes: determining at least one of an actual relationship of a mobile device to water or an expected relationship of the mobile device to water; determining ranges to satellites, based on signals received by a satellite positioning system (SPS) receiver of the mobile device, in response to the signals being received by the SPS receiver when the at least one of the actual relationship of the mobile device to water or the expected relationship of the mobile device to water is a desired relationship of the mobile device to water; and determining a location of the mobile device based on the ranges to the satellites.