Abstract
A variety of mathematical models exist with which to combine long-wavelength geoid information from an Earth gravity model (EGM) with terrestrial gravity data. As new data become available, such as an extended or refined EGM and/or some variance–covariance information from terrestrial gravity data, this new information can be combined with a previous geoid model through a so-called hybrid estimator. The hybrid estimator is defined as a two-step estimator, which provides a solution that is a compromise between computational labour and matching of the entire data set. Some commonly used geoid modifications are compared, and several hybrid estimators are introduced. It is concluded that, in general, hybrid estimators linking the new information to old data by the least squares principle should be preferred to deterministic combinations.
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