Advanced high resolution methods for radar imaging and micro-Doppler signature extraction

• Main Author: Clemente, Carmine
• Published: University of Strathclyde 2013
• Subjects: 621.3
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.576474

This Thesis presents radar concepts and signal processing techniques including the fractional Fourier transform (FrFT), Chebyshev polynomial approximation and Singular Spectrum Analysis (SSA) for advanced high resolution radar imaging and micro-Doppler signature extraction. Two novel SAR focussing algorithms in the time-frequency domain are developed using the FrFT. These are called the Fractional Range Doppler Algorithm (FrRDA) and the enhanced Fractional Chirp Scaling Algorithm (eFrCSA. The new methods are tested on simulated and real data sets and are shown to provide higher performances in terms of image quality and resolution than existing frequency domain based methods. The state of the art signal spectrum models of a bistatic point target spectrum for bistatic SAR imaging has been improved by deriving Chebyshev polynomial approximations in place of the conventional Taylor based approximations. This new model increases the accuracy and the efficiency of frequency domain focussing algorithms. Models for micro-Doppler signatures in bistatic SAR are developed and the effect of the different acquisition geometries are considered, including the effect on the final image. A new concept for a Passive Bistatic Radar is introduced for micro-Doppler analysis of helicopters rotor blades. The proposed system exploits the forward scattering enhancement to increase the radar cross section of the helicopters rotor blade allowing an acceptable operative range. The analysis shows how the proposed system could be considered as a good candidate for cheap coast and border control. A detailed analysis on the effect of micro-Doppler from wind turbines and their impact on SAR images is presented. The signal model for such a distributed target is presented and simulation results show how the presence of such a target can significantly decrease and corrupt the image quality. Singular Spectrum Analysis (SSA) is developed for micro-Doppler signature extra ction from SAR clutter and from the direct signal interference and clutter of a passive bistatic radar. The SSA is shown to be robust and capable of performing as a useful tool with the capability of mitigating the effects of clutter on micro-Doppler signatures.