Using Markov random fields for gravity modeling in the vector airborne gravimetry problem

Abstract

Strapdown airborne gravimetry can contribute to the gravity disturbance vector determination along the flight trajectory. In the paper the problem of the gravity disturbance vector estimation is posed given strapdown airborne gravimetry data at a set of parallel flight lines. Anomalous gravity field is assumed to be a markov random field. The estimation algorithm is developed using Kalman filtering and smoothing techniques. The algorithm is optimal in the set of all linear algorithms under the minimum mean-square-error criterion.