Use of Crossovers to Evaluate Airborne Gravity Data

The RMS of crossover mismatch has long been used as a measure of quality in airborne gravity. Some groups even adjust the bias and slope of each line in a survey to minimize the crossover mismatch. Is the expectation that airborne gravity measurements are path independent, leading to a zero crossover mismatch, correct? If the measurements are filtered along the track, the answer is no, we should not expect the same reading at the same location measured from different directions. This presentation will demonstrate the effects of along-track filtering, interpolation and altitude correction that cause a mismatch unrelated to measurement error. A method for computing the expected crossover mismatch will be presented. A comparison of evaluation methods for several GRAV-D airborne gravity surveys will illustrate the magnitude, contributing factors and systematic nature of the differences between these methods.