For geophysical purposes, gravity is measured in many ways, from static-point observations, using a gravimeter, to mean-value determinations from gravimeter and gravity gradiometer data collected by airplanes, ships, and satellites. We tested estimates of vertical and horizontal components of the gravity vector by combining Global Positioning System (GPS) data with a Honeywell H764G inertial navigation system (INS) on a land vehicle traversing highways in southwestern Montana. The estimation methods were based on techniques applied successfully to airborne INS/GPS data. In addition, we used wavelet denoising and wavenumber correlation procedures to enhance the estimates. Analyses of multiple traverses along the roads verified levels of repeatability as good as [Formula: see text] (all numerical accuracy values refer to standard deviations) in the vertical gravity-disturbance component. Control data, interpolated onto each road segment from an available database of gravity values, had an accuracy better than [Formula: see text]. Compared with this interpolated control, our vertical gravity estimates compare as well as [Formula: see text]. Resolution of the estimated vertical component is about [Formula: see text], based on [Formula: see text] data smoothing and a vehicle averaging about [Formula: see text]. Large scale-factor errors exist in the horizontal gravity estimates. Removing those on the basis of extensive deflection-of-the-vertical (DOV) control yields repeatability in the horizontal components of [Formula: see text] and agreement with the control at [Formula: see text]. Our tests confirm that a land-vehicle INS/GPS system is capable of along-track gravity mapping with precision and resolution that have used in local geophysical modeling (e.g., continental rifts) as well as in mineral exploration.
Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm