A method of orienting a mobile device to a vehicle includes determining an orientation of a gravity vector and aligning a first axis of the mobile device with respect to the gravity vector. The method also includes determining an orientation of a magnetic direction and aligning a second axis of the mobile device with respect to the magnetic direction. The method further includes determining a direction of travel for the vehicle and orienting the mobile device to the vehicle.

An airborne gravity-based transducer is disclosed as two embodiments with similar physical structures but different operating principles. The first design includes a particle acting as an active interface characterized by internal vibrations relating to its de Broglie wave, a resonant cavity for trapping the particle, and a phonon-wave source wherein the de Broglie and phonon waves interact over a junction area. In the second design, mechanical displacements between the transducer elements can be monitored through electromechanical transduction. Both designs include a power source and a biasing circuit for producing an electrical current across the junction, and a sensing system for measuring voltage. Both designs are capable of cancelling slowly-varying gravitational acceleration due to dynamic interaction in motion with the gravitational field and responding to small-scale gravity anomalies. The transducer can be utilized in hydrocarbon exploration to provide information on areas conducive to fluid entrapment in the sedimentary column.

An integrated method and system for communication, positioning, navigation, and timing of a deep-sea vehicle. The method implements integration and deep fusion of communication, positioning, navigation, and timing, and can achieve uniformity of space references and time references between sensors and systems, can reduce difficulty in information fusion, and can implement convenient underwater acoustic communication, real-time/high-update-rate/low-power-consumption/high-precision positioning, high-precision/fault-tolerant navigation, and precise timing. The present invention implements simultaneous operation of four working modes: communication, positioning, navigation, and timing, to fundamentally resolve problems such as insufficient practicability of underwater acoustic communication, low accuracy of navigation and positioning, and no timing function, so as to improve underwater operation efficiency of a deep-sea vehicle.

An integrated method and system for communication, positioning, navigation, and timing of a deep-sea vehicle. The method implements integration and deep fusion of communication, positioning, navigation, and timing, and can achieve uniformity of space references and time references between sensors and systems, can reduce difficulty in information fusion, and can implement convenient underwater acoustic communication, real-time/high-update-rate/low-power-consumption/high-precision positioning, high-precision/fault-tolerant navigation, and precise timing. The present invention implements simultaneous operation of four working modes: communication, positioning, navigation, and timing, to fundamentally resolve problems such as insufficient practicability of underwater acoustic communication, low accuracy of navigation and positioning, and no timing function, so as to improve underwater operation efficiency of a deep-sea vehicle.

Examples disclosed herein involve a computing system configured to (i) obtain (a) a first set of sensor data captured by a first sensor system of a first vehicle that indicates the first vehicle's movement and location with a first degree of accuracy and (b) a second set of sensor data captured by a second sensor system of a second vehicle that indicates the second vehicle's movement and location with a second degree of accuracy that differs from the first degree of accuracy, (ii) based on the first set of sensor data, derive a first trajectory for the first vehicle that is defined in terms of a source-agnostic coordinate frame, (iii) based on the second set of sensor data, derive a second trajectory for the second vehicle that is defined in terms of the source-agnostic coordinate frame, and (iv) store the first and second trajectories in a database of source-agnostic trajectories.

Examples disclosed herein involve a computing system configured to (i) obtain (a) a first set of sensor data captured by a first sensor system of a first vehicle that indicates the first vehicle's movement and location with a first degree of accuracy and (b) a second set of sensor data captured by a second sensor system of a second vehicle that indicates the second vehicle's movement and location with a second degree of accuracy that differs from the first degree of accuracy, (ii) based on the first set of sensor data, derive a first trajectory for the first vehicle that is defined in terms of a source-agnostic coordinate frame, (iii) based on the second set of sensor data, derive a second trajectory for the second vehicle that is defined in terms of the source-agnostic coordinate frame, and (iv) store the first and second trajectories in a database of source-agnostic trajectories.

A geoid calculation data is collected easily. A geoid calculation data collection device of the present invention comprises an inertial measurement data acquisition part, a comparison data acquisition part, and a recording part. In the inertial measurement data acquisition part, data related to velocity, position, and attitude angle is acquired as inertially-derived data based on an output of an inertial measurement part having a three-axis gyro and a three-axis accelerometer attached to a moving body. In the comparison data acquisition part, data related to velocity is acquired as comparison data from a source other than the inertial measurement part. In the recording part, inertially-derived data and comparison data are recorded in association with each other. In the inertial measurement part, a bias stability is acquired that allows error arising from plumb line deviation to be distinguished to a predetermined degree.

A change in geoid height is measured easily. A geoid measurement method of the present invention executes an inertial measurement data acquiring step, a comparison data acquiring step, a state variable estimating step, and a geoid calculating step. In the inertial measurement data acquiring step, data related to velocity, position, and attitude angle is acquired as inertially-derived data based on the output of an inertial measurement part having a three-axis gyro and a three-axis accelerometer attached to a moving body. In the comparison data acquiring step, data related to velocity is acquired as comparison data from a source other than the inertial measurement part. In the state variable estimating step, state variables including a plumb line deviation are estimated by using the inertially-derived data and the comparison data to apply a Kalman filter in which the plumb line deviation is included in the state variables.

A system implementing a method for generating a navigation output is provided. The method includes determining a gravitational anomaly estimate based at least in part on inertial sensor data and navigation output; generating navigation and sensor corrections that are due at least in part on inherent sensor errors that include vertical accelerometer/gravimeter corrections from at least a navigation output estimate, the gravitational anomaly estimate, and the gravity map data; and generating the navigation output based on the inertial sensor data, gravity map data and the navigation and sensor corrections.

A system implementing a method for generating a navigation output is provided. The method includes determining a gravitational anomaly estimate based at least in part on inertial sensor data and navigation output; generating navigation and sensor corrections that are due at least in part on inherent sensor errors that include vertical accelerometer/gravimeter corrections from at least a navigation output estimate, the gravitational anomaly estimate, and the gravity map data; and generating the navigation output based on the inertial sensor data, gravity map data and the navigation and sensor corrections.