Feature extraction and connectionist classification of SODAR echograms

Sonic detection and ranging (SODAR) systems are efficient and economical tool to probe the lower planetary boundary layer on a continuous basis. The lower atmospheric patterns (each depicting a different atmospheric condition) recorded by this system can prove to be extremely useful if classified and interpreted correctly. The manual identification of these SODAR patterns is a laborious task and requires considerable expertise. A connectionist system has already been developed by the authors to automate the process to some extent. In this letter, we enhance its generalization of performance, by incorporating feature extraction using the fast Fourier transform. The results are compared with that in earlier work to demonstrate its effectiveness.