Application Of The Fractional Fourier Transform To Target Detection And Imaging In SAR

As a high resolution radar with all-weather, all-time capability, Synthetic Aperture Radar (SAR) can obtain the image from a long distance. Now it is used widely both for civilian and military. The signal received from the targets of SAR is normally non-stationary, and has the characteristics of Linear Frequency Modulation (LFM) signal.With good cross-terms reduction and high time-frequency resolution, Fractional Fourier Transform (FRFT) is a linear and full time domain analysis tool for non-stationary signal processing. It has been widely used in the multi-component LFM signal processing for its perfect property.In this thesis, application of the FRFT to target detection and imaging in SAR is discussed. Firstly, the definition and the basic characteristics of FRFT are presented, and then, the time-frequency properties of LFM signal are summed up. Further more, two methods for the detection and chirp rate parameter estimation of LFM signal: maximum method and kurtosis method are discussed, with a good capability of suppressing noise, kurtosis method can detect LFM signals when the SNR is -12dB. After that, a new method for detecting the weak components of the signal among the strong components of the signal is proposed, which combines the technique of filtering in fractional Fourier domain and kurtosis detection, so the strong components of the signal and the weak ones can be detected iteratively. The simulation results show that the method can effectively detect the weak components of the signal when the SNR of the strong components of the signal are 5dB and the weak one is -9dB. Finally, a new Chirp Scaling Algorithm based on the Fractional Fourier Transform is studied. The simulation results show that the algorithm can effectively imaging the point targets.