| Inverse Synthetic Aperture Radar(ISAR)is a high-resolution imaging radar that can depict the two-dimensional distribution of targets in space,and has important research significance in military and defense fields.However,due to the interference of noise and the non-cooperation of the target,the traditional imaging algorithm is not effective.The motion compensation in the distance dimension will be affected by the low signal-to-noise ratio,which makes the compensation result worse.The azimuth dimension processing causes the azimuth due to the change of the target’s speed.The form of the signal changes.Therefore,this article discusses the imaging process of variable-speed moving targets under low signal-to-noise ratio,and aims to find a suitable method to obtain ISAR images with good focusing effect.This article first analyzes the impact of low signal-to-noise ratio on ISAR imaging,and analyzes commonly used motion compensation algorithms based on envelope cross-correlation.By calculating the correlation between adjacent slow-time envelope amplitudes in high-resolution one-dimensional range profiles,The envelope is moved artificially,and the compensation effect of this method is better under high SNR conditions.However,under low SNR or because the target RCS is too low,the energy of the echo signal is too small,so that the echo signal is submerged in noise,or the correlation of the noise in a complex environment becomes stronger.The correlation between them is greatly weakened,which makes the effect of envelope alignment worse or even completely invalid.This article discusses the influence of different target noises on the motion compensation process.Aiming at the problem of poor compensation effect of the envelope cross-correlation algorithm under low signal-to-noise ratio,the translation compensation algorithm based on KT transform is introduced.Compare the imaging results.Subsequently,the motion compensation process of moving targets with variable speed under low signal-to-noise ratio is discussed.Although the KT transformation is not affected by noise,it will have a semi-blind speed effect at certain speeds,which will affect the results of motion compensation,and it is necessary to accurately estimate the target acceleration for variable-speed motion targets.In order to solve this problem,an improved algorithm is proposed on this basis.The improved idea is to combine the cross-correlation algorithm with the KT transformation method to obtain the moving distance of each slow-time echo.The blur number is estimated by radon transform,and HRRP is coarsely compensated by KT transform.The noise of the coarsely compensated HRRP is reduced by WNNM,and the echo moving distance is obtained through the cross-correlation algorithm,and then the original HRRP is compensated by the moving distance..The improved method has relatively loose requirements for KT transform,and at the same time avoids the problems of crosscorrelation method under low signal-to-noise ratio and KT transform under variable speed.Finally,the azimuth dimension processing of HRRP is analyzed from the perspective of azimuth dimension focusing.For uniformly rotating targets,the minimum entropy phase compensation method is used for processing,and for maneuvering targets,the FRFT transform method is used for processing.Considering that the calculation of FRFT transformation for each distance unit is relatively large,and the acceleration is too large,it will cause speed blur in the azimuth dimension.In this section,pre-processing is performed before the FRFT transformation to eliminate the effect of acceleration,and at the same time,the coarse FRFT is used to reduce the calculation amount of the algorithm,and finally the obtained imaging results are filtered and image gray-scale enhancement.The simulation experiment results show that FRFT has better focusing results in the azimuth dimension for the target of variable motion.At the end,the content of the full text is summarized and the points that still need improvement are proposed. |
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