Superimposed-Fft/Ifft For Sar And Other Microwave Measurement Applications

Abstract

Synthetic Aperture Radar (SAR) is a method of constructing high resolution images from radar transmissions. SAR is widely used in a broad range of applications, including satellite imaging and remote sensing, ground penetrating radar and medical imaging. The response of radar systems often suffer from high sidelobe level resulting in resolution degradation. These sidelobes are caused by band-limited property of measured signal. One technique to reduce sidelobes is windowing, but this has a broadening effect on the main-lobe. The proposed technique of superimposition (SI) attempts to reduce sidelobes while enhancing the resolution as oppose to broadening the target’s main-lobe as caused by many conventional techniques. Furthermore, the superimposition technique preserves the amplitude of the targets’ main-lobe while conventional sharpening techniques tend to distort it in one way or another. Results show minimal resolution loss, noteworthy sidelobe reduction and negligible distortion of peak position and amplitude from the original spectrum. SAR images generated by the Superimposed Fast Fourier Transform (SI-FFT) showed significant enhancement in focus when compared to the images generated by using the standard Fourier Transform method using the same data set, with negligible extra computational requirement. Moreover, two new techniques of superimposition are presented in this thesis: Repetitive Superimposition (RSI) and Normalized Superimposition (NSI). Results have shown significant improvement in sidelobe suppression even when compared to the standard superimposition results and more importantly, it also have shown noticeable reduction in both additive and multiplicative noise. What’s more, these techniques have also been applied to other microwave measurement techniques, mainly in Vector Network Analyzer (VNA) and Ground Penetrating Radar (GPR) where superimposed Inverse Fourier Transform (SI-IFFT) is developed and utilized for simulation and measurement and produced results are as impressive as in SI-FFT.

Date of Award	25 Feb 2015
Original language	English
Awarding Institution	University of Bath
Supervisor	Stephen Pennock (Supervisor) & Manuchehr Soleimani (Supervisor)