The inertial system for gravity difference measurement uses COTS nano accelerometer and a strapdown Global Navigation Satellite System (GNSS)-aided inertial measurement unit (IMU). The former has low measurement noise density, while the latter is used to analytically stabilize the platform. Stochastic modeling of the gravity anomaly is utilized (as opposed to the deterministic modeling of causes and effects) to simplify the algorithm. The algorithm aims at finding relative changes between points, as opposed to absolute values at the points, which allows for high relative precision required in many applications.

The inertial system for gravity difference measurement uses COTS nano accelerometer and a strapdown Global Navigation Satellite System (GNSS)-aided inertial measurement unit (IMU). The former has low measurement noise density, while the latter is used to analytically stabilize the platform. Stochastic modeling of the gravity anomaly is utilized (as opposed to the deterministic modeling of causes and effects) to simplify the algorithm. The algorithm aims at finding relative changes between points, as opposed to absolute values at the points, which allows for high relative precision required in many applications.

A method for calculating performance of satellite gravity field measurement by low-to-low satellite-to-satellite tracking, includes: acquiring parameters of gravity satellite system; calculating an effect of satellite loads on the power spectrum of nonspherical perturbation potential, so as to obtain an degree error variance; comparing degree error variance with degree variance given by Kaula Rule, and when degree error variance equals degree variance, considering that the highest degree of gravity field measurement is obtained, calculating geoid degree error and its accumulative error, gravity anomaly degree error and its accumulative error, so as to obtain the performance of satellite gravity field measurement by low-to-low satellite-to-satellite tracking. The method is capable of evaluating gravity field measurement performance quickly and effectively, obtaining a rule of effects of the gravity satellite system parameters on the gravity field measurement performance, so as to avoid shortcoming caused by numerical simulation.

A method for calculating performance of satellite gravity field measurement by low-to-low satellite-to-satellite tracking, includes: acquiring parameters of gravity satellite system; calculating an effect of satellite loads on the power spectrum of nonspherical perturbation potential, so as to obtain an degree error variance; comparing degree error variance with degree variance given by Kaula Rule, and when degree error variance equals degree variance, considering that the highest degree of gravity field measurement is obtained, calculating geoid degree error and its accumulative error, gravity anomaly degree error and its accumulative error, so as to obtain the performance of satellite gravity field measurement by low-to-low satellite-to-satellite tracking. The method is capable of evaluating gravity field measurement performance quickly and effectively, obtaining a rule of effects of the gravity satellite system parameters on the gravity field measurement performance, so as to avoid shortcoming caused by numerical simulation.

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 capsule comprising two non-directly contacting halves enables otherwise coupling loads between experiment and gauging to be re-routed through the outer-most portable body (e.g. a logging sonde housing) having substantial inertia, thus serving to attenuate the parasitic loads. For co-located leveled experiment and gauging, a pair of concentric bearings (shaft in shaft) is utilized. Independent bearing sets and shock/vibration isolation support each capsule half within the outer sonde housing. A first half of the capsule supports the experiment, which the second half supports the gauging apparatus.

This disclosure describes a system and method for determining the center of gravity of a payload engaged by an automated aerial vehicle and adjusting components of the automated aerial vehicle and/or the engagement location with the payload so that the center of gravity of the payload is within a defined position with respect to the center of gravity of the automated aerial vehicle. Adjusting the center of gravity to be within a defined position improves the efficiency, maneuverability and safety of the automated aerial vehicle. In some implementations, the stability of the payload may also be determined to ensure that the center of gravity does not change or shift during transport due to movement of an item of the payload.

A gradient of gravity is defined by a change in the optical path length required to maintain equality in optical path lengths of two beam arms which direct light beams to impinge upon and reflect from two freefalling test masses.

A gradient of gravity is defined by a change in the optical path length required to maintain equality in optical path lengths of two beam arms which direct light beams to impinge upon and reflect from two freefalling test masses.