Based On Real-time Imaging Of The Sub-aperture Airborne Sar Processing

Real-time imaging is an important component in airborne Synthetic Aperture Radar (SAR) system, through which the image of ground targets can be obtained with the movement of platform and thus real-time surveillance is achieved. Azimuth compression, as a crutial step in real-time imaging, causes large difficulty when the resolution or range is improved, because both of them increase the beam width and synthetic aperture.In this thesis, the real-time imaging algorithm applied to large synthetic aperture is studied, which is based on the current hardware conditions. Besides, the motion compensation according to the subaperture is researched. Both of them lead the imaging algorithm applicable to real-time imaging system with high resolution and large synthetic aperture. The main contents are as follows:1. Based on the introduction of SAR principle, the normal SAR real-time imaging algorithms—RD and CS—are detailedly analyzed.2. Aiming to azimuth compression of large aperture, the necessary hardware condition is analyzed, concluding that it is difficult to achieve real-time azimuth compression under current hardware conditions. Based on the study, two subaperture algorithms named time domain subaperture correlative algorithm and STEP transform. The problem of data order in STEP transform is improved. The azimuth subaperture real-time algorithm is detailedly analyzed. The simulation of point target proves its efficiency and the experiment results of real data indicate that it is efficient in high resolution real-time imaging.3. The motiont compensation is studied referring to the azimuth subaperture, which is focused on motion compensation based on data and minimum entropy autofocus algorithm. The former algorithm is combined with parameter estimation, directly getting phase error from echo. The later is amply analyzed, concluding that it is useful to eliminate high-order phase errors as well as second-order error. The experimental results prove their efficiency.The azimuth subaperture real-time algorithm reduces the requirement of hardware resource. Moreover, it integrates subaperture processing with motion compensation, and so it is applicable to real-time imaging in high resolution and large synthetic aperture.