Wind Streamline Ambiguity Removal of Microwave Scatterometer Data

There is a class of satellite microwave scatterometers that return oceanographic information which includes wind vectors with directional ambiguity. The first part of the ambiguity removal process is to reduce the data to a directional ambiguity of 180°. This thesis shows that wind direction change contains the information required for streamline ambiguity removal and that syntactic pattern recognition techniques can be used to locate the areas of wind direction change. Spreading the information along the areas of wind direction change results in the removal of the streamline ambiguity. The algorithm is implemented and the results are presented showing that it is a good candidate for removing streamline ambiguity.