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Estimation of systematic errors in tracked datasets using least squares crossing point analysis

Morgan Brown

morgan@sep.stanford.edu

ABSTRACT

Geophysical data often contains both systematic and random errors. If left unchecked, the systematic errors can cause acquisition footprint in the final map. I present a method to estimate systematic error by analyzing measurements at points where two acquisition swaths cross. I then subtract the estimated systematic error from the data and generate a map with a familiar least squares formulation. I test the method on bathymetric data from the Sea of Galilee. Compared to two previous least squares formulations, my new method produces final maps which are relatively free of acquisition footprint, and which exhibit preservation of underlying bathymetric features.



 
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Stanford Exploration Project
9/18/2001