Date of Award

8-2004

Degree Type

Thesis

Degree Name

M.S.

Degree Program

Engineering

Department

Electrical Engineering

Major Professor

Alsamman, AbdulRahman

Second Advisor

Charalampidis, Dimitrios

Third Advisor

Jovanovich, Kim

Abstract

In this thesis we propose an automated process for the removal of non-precipitation echoes present in weather radar signals and accurate detection of rainfall. The process employs multifractal analysis using directional Gabor wavelets for accurate detection of the rain events. An optoelectronic joint transform correlator is proposed to provide ultra fast processing and wavelet analysis. Computer simulations of the proposed system show that the proposed algorithm is successful in the detecting rainfall accurately in radar images. The accuracy of the algorithms proposed are compared to accurate results that were generated under expert supervision. Results of the proposed system are also compared to results of QC algorithm for the ground validation software (GVS) used by TRMM ground validity Project and a previous QC algorithm. Several statistical measures computed for different reflectivity ranges show that the proposed algorithm gives accuracy as high as 98.95%, which exceed the 97.46% maximum accuracy for the GVS results. Also, the minimum error rate obtained by the proposed algorithm for different dB ranges decreases to 1.09% whereas the GVS results show a minimum error rate of 1.80%. The rain rate accumulation confirms the success of the proposed algorithm in the accurate removal of nonprecipitation echoes and a higher precision in rain accumulation estimates.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.

Download

Share

COinS