The effect of stochastic gravity models in airborne vector gravimetry

Abstract

Measurements of specific force using inertial measurement units (IMU) combined with Global Positioning System (GPS) accelerometry can be used on an airborne platform to determine the total gravitational vector. Traditional methods, originating with inertial surveying systems and based on Kalman filtering, rely on choosing an appropriate stochastic model for the gravity disturbance components included in the set of system error states. An alternative procedure that uses no a priori stochastic model has proven to be as effective, or moreso, in extracting the gravity vector from airborne IMU/GPS data. This method is based on inspecting acceleration residuals from a Kalman filter that estimates only sensor biases. Using actual data collected over the Canadian Rocky Mountains, this method was compared to the traditional approach adapted for different types of stochastic models for the gravity disturbance vector. In all test cases, the estimation filter without a gravitational model yielded better results-up to 50%. This implies that accurate gravity vector determination from airborne IMU/GPS need not rely on an a priori stochastic model of the field, even though the theory of optimal estimation requests it. However, no filter was able to remove all systematic errors from the data; these remaining errors could only be reduced by elementary methods such as endpoint matching and correlative processing of adjacent passes of the system over the gravity field. The final, best gravity estimates had standard deviations with respect to control data of 6 mGal in the horizontal components and 3-4 mGal in the vertical component.

Calculation method for deflection of the vertical based on path gravity anomaly compensation

“…Additionally, Rose and Nash were the first to infer the DOV via an inertial navigation system (INS)-based method using horizontal accelerometers [16]. Jekeli and Kwon implemented the airborne experiment using INS and Global Positioning System [17]. The DOV is considered as the main navigation error in INS.…”

An Accurate Gravity Compensation Method for High-Precision Airborne POS

“…The method based on absolute gravimeter can obtain the accurate result of each measuring position [15]; however, it is inefficient and restricted by the terrain and other objective factors. The method based on the gravity disturbance model can acquire the optimal estimation of gravity disturbance in theory, relying on an appropriate stochastic model for the gravity disturbance, whereas it is difficult and problematic to establish an accurate gravity disturbance model when remote sensing applications are implemented in strange survey areas [16]. The direct difference method is generally adopted for measuring gravity disturbance at present, which takes the difference of the accelerations from the GPS and the accelerometers to extract the gravity disturbance [17], [18].…”

A Method of Deflection of the Vertical Measurement Based on Phase Correction

“…Yu et al carried out the vehicle experiment of direct difference method [20]. Kwon compared the optimal estimation method with the direct difference method, and supposed that the accuracy of the direct difference method is higher than that of the optimal estimation method in general [21]. However, Dai supposed that the direct difference method cannot be used to calculate the DOV [22].…”