A sequential method for filtering satellite altimeter measurements

Recent advances in the area of satellite altimetry have provided a data type which is applicable to the detection and monitoring of transient sea surface phenomena. With the extensive altimeter data set collected by the Geos 3 spacecraft there is an associated need for accurate and efficient methods for editing and filtering the altimeter data. In this investigation a sequential filter is developed assuming that the sea surface topography can be approximated by an adaptive Gauss-Markov process. The effect of geoid model errors on the filtered results is illustrated by using both 1° × 1° and 5′ × 5′ geoid models. Finally, an application of the method to the Gulf Stream current boundary identification problem using Geos 3 altimeter data is described.