Research On High-Resolution Airborne SAR Imaging Algorithms

Synthetic aperture radar (SAR) is a high resolution microwave imaging system with all weather,day and night capability. After the developments in the past decades, the monostatic SAR imagingtechnologies in general resolution case become mature gradually. However, there are still someproblems when utilizing the existing algorithms to focus the X band ultra-high resolution SAR data orbistatic SAR data.In ultra-high resolution case, the phase errors in the approximated frequency domain algorithms,such as chirp scaling algorithm (CSA), become larger, which degrade the focal quality of SAR imagesignificantly. To solve this problem, this dissertation investigates the modification of two frequencydomain algorithms in ultra-high resolution SAR imaging with the transmitted stepped frequencywaveform. With this modification, the phase errors in these algorithms are reduced so as to focus theX band ultra-high resolution SAR data with high precision.In bistatic SAR, the separation of transmitter and receiver results in a complicate form of theDoppler phase term of the received signal, and hence the derivation of bistatic algorithm with highprecision is complex. The bistatic polar format algorithm (PFA) and bistatic back projection algorithm(BPA), which are obtained by extending the corresponding monostatic algorithms, are analyzed andimproved in this dissertation. Then, the existing approximate bistatic spectrums are analyzed andcompared, and the bistatic range Doppler algorithm (RDA) is derived.Chapter I is the introduction, which introduces the background of this paper and describes thehistory and latest developments in monostatic and bistatic SAR. Then, the difficulties and maincontents in our research are outlined.Chapter II investigates the ultra-high resolution SAR imaging with the transmitted steppedfrequency waveform. This chapter first introduces the signal model of received stepped frequencywaveform and existing bandwidth combination methods. The new processing flows for the receivedchirp and dechirped stepped frequency signal are then proposed and discussed, respectively. The CSAand extended frequency scaling algorithm (EFSA) are applied to focus the sub pulses, respectively.After combining the focused sub pulses in the2-D frequency domain, the image can be obtained viaperforming2-D IFFT on the combined data. The phase error in the above processing flows and in theoriginal CSA/EFSA are analyzed and compared finally. Point target simulation and phase erroranalyses indicate that our proposed methodology can improve the focal quality of image effectively. In Chapter III, the implementation of bistatic PFA using the principle of chip scaling (PCS) isproposed. The bistatic spotlight mode SAR data collection geometry and bistatic PFA are introducedfirst. Then, the PCS and essence of range resampling in bistatic PFA are discussed. Finally, the scalingprocessing flows for the chirp and dechirped signal are described, respectively. Since the scalingmethodology is used to implement the range resampling, the efficiency of bistatic PFA is improvedeffectively.Chapter IV analyzes and corrects for the wavefront curvature error in bistatic PFA image. Theunrealistic planar wavefront assumption in bistatic PFA introduces phase error in the focused imageand results in space variant geometry distortion and defocusing effect. This chapter first derives theanalytical expression of wavefront curvature. Then, the space variant filter is designed and applied tocompensate for the defocusing effect in bistatic PFA image, and interpolation operation is used tocorrect for the geometry distortion. Analysis of the focused scene size after space-variant filteringvalidates this algorithm.Chapter V studies the bistatic filtered back projection (FBP) algorithm and the link betweenFBP and CSA. Based on the microwave model and Born approximation, the received baseband signalin SAR can be considered as the fourier integral transform of the reflectivity of the illuminated scene.The image can be obtained by applying a FBP-type inversion algorithm. This chapter completes theapplication of FBP algorithm in bistatic SAR imaging, where the essence of this methodology is alsodiscussed. Moreover, the link between FBP and CSA in monostatic case is derived. When ignoring therange variance of range modulation rate, the processing flow of FBP can be approximated as that ofCSA, which also indicates that the essence of FBP is a2dimensional space variant matched filter.In Chapter IV, bistatic point target response spectrum and bistatic RDA are analyzed. Threeexisting approximate spectrums are analyzed and compared first. The improved Loffeld's bistaticformula (ILBF) spectrum is proved to be comparably accurate with the spectrum derived using themethod of series reversion (MSR). Based on the expansion of the ILBF spectrum, a new bistatic RDAis developed to process the azimuth invariant and variant bistatic SAR data. Compared with theexisting bistatic frequency domain algorithm, the new algorithm has a simpler formulation, and is ableto cope with bistatic SAR data in azimuth invariant and variant configurations. Finally, point targetssimulations validate the new algorithm.