| Inverse synthetic aperture radar is used to obtain two-dimensional images of moving targets. ISAR imaging is an important approach for noncooperative moving target detection and identification, which is a study hotspot all over the world. With the development of radar technology, requirements for high-resolution images are increased. Because higher resolution images have, more information they can provide.ISAR imaging is based on rotation platform imaging. After motion compensation, the imaging of moving targets can be converted to ideal rotation platform imaging. Motion compensation includes range alignment and phase compensation. The methods of range alignment mainly include dominant scatterer method, envelope cross-correlation method, frequency domain method, Minimum entropy method and so on. As the precision of most traditional methods of range alignment is limited to one range cell, we proposed an algorithm of range alignment based on fractional delay. The precision of range alignment can be improved, so the focusing result of ISAR images can be improved. The simulation with practical measured data shows the effect of the method on ISAR imaging.High range resolution of ISAR can be obtained by transmitting wide bandwidth signal. A large rotation angle for the moving targets relative to the radar line of sight is required to obtain high azimuth resolution. When the rotation angle of the moving target is large, the migration-through-resolution cells (MTRCs) will obviously emerge thereby degrading image resolution. An ISAR imaging algorithm based on segment processing is described to solve this problem. In this algorithm, the large rotational motion is divided into several small segments. Low-resolution imaging can be handled easily with current ISAR imaging algorithms. After scaling and image registration, the MTRCs can then be compensated. Theoretical analysis and simulations show that the proposed algorithm can compensate the MTRCs of scatterers and obtain high-resolution images. |
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