Based On High Resolution Sar Imaging Compression Perception Of Wide Domain Research

Synthetic Aperture Radar can obtain high resolution images of illuminated sceneunder all weather circumstances，so it becomes an important imaging and detecting toolin military field, including topographic mapping, target identification, and flightnavigation etc. However, the development of high resolution radar system is restrictedby the Nyquist sampling theory. According to the Nyquist sampling theory, a largeamount of samples will be collected in high resolution SAR system which leads to theburden of the system.CS offers many advantages that could be amazing to be used into radar signalprocessing, for instance, the possibility of hardware simplification, reduction of dataacquisition times, ability of achieving high resolution, and data compression, etc.Therefore, we introduce the theory of compressed sensing into the imaging of the SARprocessing. The main works of this dissertation are summarized as follow:1. First, aiming at the advantage of compressed sensing theory using in the signalprocessing field, the imaging model of radar based on compressed sensing is studied.Then, a novel high resolution SAR2D imaging algorithm is proposed based oncompressed sensing. Simulated result of sparse real target indicates the effective of theproposed method.2. To analysis the DPCMB SAR imaging technology, we established the signalmodel of Single Transmitter Multiple Azimuth Beams and Multiple TransmitterMultiple Azimuth Beams imaging. Then, this dissertation put forward a new DPCMBhigh resolution SAR imaging algorithm which is based on compressed sensing theory. Itis outstanding for sampling the raw data with lower A/D sampling rate than the requiredNyquist sampling rate, then operating at range and azimuth dimension using CStechnique. Simulated result of sparse real target also verifies validate of the proposedalgorithm.3. In the study of distribute SAR, we analyze the echo signal model of thedistribute SAR. Then a space-time frequency imaging method has been studied and thesimulated results indicate the effective of the algorithm. With the consideration the advantage of CS offers that could be amazing to be used into radar imaging, weintroduce the CS theory into the distribute SAR imaging field. The validity has beenproved by the simulation results.