Abstract
ABSTRACTHigh-frequency (HF) radars sense the surface of ocean using electromagnetic waves and provide data of current vectors over a large spatial domain in the form of current maps at short intervals of time. Due to reasons such as failure of hardware or software, vandalism, or environmental issues, small or large gaps can always be found in collected data. In-filling of such missing information calls for special procedures owing to the typical sensing and reporting style of these current maps. In this article HF radar observations made at five different locations in India are analysed with the aim of providing consistent and synthesized information after noticing that there were significant missing values. This task is accomplished by selecting the most appropriate and state of the art methods of spatial data interpolation. An exhaustive experimentation in this regard showed that the statistical method of ‘inverse distance weighting’ or the soft computing technique of artificial neural network can work satisfactorily for this purpose.
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