Research On ISAR Imaging Method Based On Compressed Sensing

Inverse Synthetic Aperture Radar(ISAR)has powerful ability to detect and recognize moving targets,and therefore widely applied in many fields.With the in-depth exploration on ISAR,the need for further obtaining high-quality imaging results has become more urgent.Methods such as increasing the bandwidth of transmitted signal can bring about highresolution imaging results,but they will put too much pressure on echo data processing,and sidelobe interference will occur during the matched filtering of the echo signal,which will eventually lead to blurred image and quality degradation.In order to solve the abovementioned problems,this paper studies the echo signal parameter estimation and sidelobe suppression algorithm in the ISAR imaging process based on the theory of Compressed Sensing(CS),and obtains high-quality imaging results.The main work of this paper can be summarized as follows:The principle of ISAR imaging and the Range Doppler(RD)algorithm are analyzed,and the corresponding motion compensation algorithm is used for the interference component caused by the target translation and rotation,and the rotation compensation algorithm is a double integration algorithm based on the projection slicing theory.Then the above motion compensation algorithm is applied to the ISAR imaging process,and it is verified by simulation experiment that compared with the direct RD algorithm imaging,the resolution of the imaging result is improved.The parameter estimation algorithm of ISAR echo processing is analyzed.First,the twodimensional search algorithm based on the Fractional Fourier Transform(Fr FT)domain is analyzed.This algorithm can effectively estimate the parameters,but the overall computational complexity is relatively high.In order to make up for the above-mentioned defect,considering that the CS theory breaks the limitation of the Nyquist sampling theory,an ISAR echo parameter estimation algorithm based on the CS theory is proposed.Then the algorithm is applied to the ISAR measured aircraft echo for imaging processing,which proves that the algorithm has the advantages of high computational efficiency and improved accuracy.The sidelobe interference phenomenon caused by matched filtering in the ISAR imaging process is studied.First of all,the traditional window function is used to suppress the sidelobe,but this algorithm will result in a lower resolution while reducing the effect of sidelobe.Based on the shortcomings of the window function,a Back Projection(BP)algorithm suitable for ISAR imaging is proposed,and simulates its effectiveness in improving the quality of ISAR images.However,the core interpolation process of the algorithm will lead to a significant increase in computational complexity.In order to further improve the computational efficiency and the quality of ISAR imaging,after analyzing reconstruction algorithm based on greedy matching in CS theory,it was innovatively applied to the echo data of the actual ISAR aircraft target to perform sidelobe suppression imaging processing.In comparison with traditional RD imaging algorithm,CS reconstruction imaging algorithms is more effective in the field of ISAR imaging and their final imaging quality improves significantly,verified by the concept of structural similarity and image contrast.