ИСТИНА

We propose a new approach to the vector gravimetry problem using a spatial stochastic model of the gravity field. It is known that the gravity spatial correlations taken into account can improve the accuracy of the gravity disturbance vector estimates (Y.Bolotin, V.Vyazmin, 2016). We suppose that the disturbing potential is a two-dimensional homogeneous random field at the flight level. Consider airborne measurements along parallel survey lines. For simplicity, we assume that the lines are flown in the same direction. The gravity disturbance vector and the INS systematic errors satisfy the INS error propagation equations. The disturbance potential model is governed by two autoregressive equations, one of which is defined along the lines and the other across the lines. The airborne vector gravimetry problem is reduced to optimal estimation of the disturbing potential and the INS systematic errors simultaneously along all the lines. The Kalman filtering and smoothing algorithms provide the estimates.