Abstract: A device implementing a system for estimating device orientation includes at least one processor configured to obtain a first estimate for a heading of a device, the first estimate being based on output from a magnetometer of the device. The at least one processor is further configured to capture image data using an image sensor of the device, and determine at least one second estimate of the heading based on correlating the image data with mapping data. The at least one processor is further configured to determine a bias associated with output of the magnetometer based on the first estimate and the at least one second estimate, and adjusting output of the magnetometer based on the determined bias.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to estimate a first position of a device based on a first set of parameters, the first set of parameters derived from first sensor data obtained on the device, the first set of parameters corresponding to device motion. The at least one processor is configured to estimate a second position of a user of the device based on a second set of parameters, the second set of parameters derived from second sensor data obtained on the device, the second set of parameters corresponding to user motion. Estimating the first and second positions is constrained by a predefined relationship between the device motion and the user motion. The at least one processor is configured to provide at least one of the first position of the device or the second position of the user.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals at a sampling interval, each set corresponding to location data. For each sampling period defined by the sampling interval, the at least one processor is configured to obtain first sensor data corresponding to device motion during the sampling period, obtain second sensor data corresponding to atmospheric pressure sampled at a beginning and end of the sampling period, calculate a change in altitude based on a difference in the atmospheric pressure at the beginning and end of the sampling period, and estimate a device state based on the first sensor data and change in altitude.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

Abstract: A system and method of continuous carrier wave reconstruction includes a radio navigation receiver that includes one or more processors, memory coupled to the one or more processors, and an input for receiving a signal from a transmitter. The signal has a phase. The one or more processors are configured to obtain phase lock on the received signal, extract first phase information from the received signal, detect a loss in phase lock on the received signal, and extrapolate second phase information while phase lock is lost using a model of the phase. In some embodiments, the one or more processors are further configured to reconstruct the carrier signal based on the first and second phase information. In some embodiments, the one or more processors are further configured to scale the first and second phase information from a first nominal frequency of the received signal to a different second nominal frequency.

Abstract: Systems, methods, devices and subassemblies for creating and delivering crowd-sourced GNSS models include receiving at one or more navigation receivers first signals transmitted by one or more navigation beacons, determining by the navigation receivers first navigation observables based on the received first signals, receiving at an augmentation server information associated with the first navigation observables, determining by the augmentation server augmentation information based on at least the received information associated with the first navigation observables and computational models, transmitting the augmentation information to the navigation receivers, receiving by the navigation receivers the augmentation information, receiving by the navigation receivers second signals transmitted by the one or more navigation beacon, determining by the navigation receivers second navigation observables based on the received second signals and determining by the navigation receivers a respective high-precision posi

Abstract: Systems, methods, devices and subassemblies for creating and delivering a GNSS augmentation service include one or more reference stations for receiving signals transmitted by navigation beacons and an augmentation server coupled to the reference stations. At least one of the reference stations is able to receive at least one of the signals from a low earth orbit satellite. Each of the reference stations determines first navigation observables based on the received signals and transmit information associated with the first navigation observables to the augmentation server. The augmentation server is configured to determine and distribute augmentation information to a receiver. The augmentation information is based on the received information associated with the first navigation observables, locations of the reference stations, and computational models.

Abstract: Position, navigation and/or timing (PNT) solutions may be provided with levels of precision that have previously and conventionally been associated with carrier phase differential GPS (CDGPS) techniques that employ a fixed terrestrial reference station or with GPS PPP techniques that employ fixed terrestrial stations and corrections distribution networks of generally limited terrestrial coverage. Using techniques described herein, high-precision PNT solutions may be provided without resort to a generally proximate, terrestrial ground station having a fixed and precisely known position. Instead, techniques described herein utilize a carrier phase model and measurements from plural satellites (typically 4 or more) wherein at least one is a low earth orbiting (LEO) satellite. For an Iridium LEO solution, particular techniques are described that allow extraction of an Iridium carrier phase observables, notwithstanding TDMA gaps and random phase rotations and biases inherent in the transmitted signals.

Abstract: Position, navigation and/or timing (PNT) solutions may be provided with levels of precision that have previously and conventionally been associated with carrier phase differential GPS (CDGPS) techniques that employ a fixed terrestrial reference station or with GPS PPP techniques that employ fixed terrestrial stations and corrections distribution networks of generally limited terrestrial coverage. Using techniques described herein, high-precision PNT solutions may be provided without resort to a generally proximate, terrestrial ground station having a fixed and precisely known position. Instead, techniques described herein utilize a carrier phase model and measurements from plural satellites (typically 4 or more) wherein at least one is a low earth orbiting (LEO) satellite. For an Iridium LEO solution, particular techniques are described that allow extraction of an Iridium carrier phase observables, notwithstanding TDMA gaps and random phase rotations and biases inherent in the transmitted signals.

Abstract: A system and method of continuous carrier wave reconstruction includes a radio navigation receiver that includes one or more processors, memory coupled to the one or more processors, and an input for receiving a signal from a transmitter. The signal has a phase. The one or more processors are configured to obtain phase lock on the received signal, extract first phase information from the received signal, detect a loss in phase lock on the received signal, and extrapolate second phase information while phase lock is lost using a model of the phase. In some embodiments, the one or more processors are further configured to reconstruct the carrier signal based on the first and second phase information. In some embodiments, the one or more processors are further configured to scale the first and second phase information from a first nominal frequency of the received signal to a different second nominal frequency.