Abstract: Using gravity gradient data to estimate local terrain can get a perfect precision.But traditional estimation algorithms are mainly for large-scale and in an off-line way,which have hindered them from transplanting and combining with other data source.This paper studied a bathymetry estimation algorithm based on kalman filter,and focused on its system error equation modeling by introducing terrain slope theory.Terrain slope and those statistical methods are equivalent in describing terrain correlation,but compared with those statistical methods,the former reduced complexity of the model.The biggest advantage of the new model is that it avoids the lack of theoretical basis when statistical methods determine statistical parameters,consequently,further improves adaptability of estimation algorithm.