Gravity field recovery from airborne gradiometer data using collaction andtaking into account correlated errors

Least squares collocation is a very comprehensive method for gravity field modelling, since it may use known noise characteristics of the data. In man y earlier applications the errors affecting the data were considered uncorr elated, mainly due to the difficulty in estimating the systematic character of such kind of errors, In this study, error covariance functions of airbo rne gravity gradiometer data are estimated by comparing model covariance fu nctions with empirical covariance functions of the gravity gradiometer data . The model covariance functions were estimated from accurate surface gravi ty data and continuated upward to the height of the airborne measurements u sing the covariance propagation law. The estimated error covariance functio ns were modeled as finite ones and used as an additional information for th e prediction of gravity anomalies from gravity gradiometer data. The assess ment of the prediction results was made by comparing the gravity values pre dicted from the airborne gradient data and showed up to 25% improvement com pared to not using correlated errors. (C) 1999 Elsevier Science Ltd. Ail ri ghts reserved.