Modified multilook cross correlation technique for doppler centroid estimation in SAR image signal processing


Sew, Bee Cheng (2012) Modified multilook cross correlation technique for doppler centroid estimation in SAR image signal processing. Masters thesis, Multimedia University.

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Synthetic Aperture Radar (SAR) is one of the widely used remote sensing sensors which produces high resolution image by using advance signal processing technique. SAR managed to operate in all sorts of weather and cover wide range of area. To produce a high-quality image, accurate parameters such as Doppler centroid are required for precise SAR signal processing. In the azimuth matched filtering of SAR signal processing, Doppler centroid is an important azimuth parameter that helps to focus the image pixels. Doppler centroid has always been overlooked during SAR signal processing. It is due to the fact that estimation of Doppler centroid involved complicated calculation and increased computational load. Therefore, researcher used to apply only the approximate Doppler value which is not precise and cause defocus effort in the generated SAR image. In this study, several conventional Doppler centroid estimation algorithms are reviewed and developed using Matlab software program to extract the Doppler parameter from received SAR data, namely Spectrum Fit Algorithm, Wavelength Diversity Algorithm (WDA), Multilook Cross Correlation Algorithm (MLCC), and Multilook Beat Frequency Algorithm (MLBF). Two sets of SAR data are employed to evaluate the performance of each estimator, i.e. simulated point target data and RADARSAT-1 Vancouver scene raw data. These experiments gave a sense of accuracy for the estimated results together with computational time consumption. Point target is simulated to generate ideal case SAR data with pre-defined SAR system parameters.

Item Type: Thesis (Masters)
Additional Information: Call No.: TK6592.S95 S49 2012
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 22 Apr 2014 07:23
Last Modified: 22 Apr 2014 07:23


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