Research On ISAR Imaging Algorithm For Complex Moving Targets

Since the inverse synthetic aperture radar(ISAR)imaging utilizes the Doppler information of the target,the motion state of the target as a whole,and the motion state of each component on the target will affect the imaging result.The research in this paper is mainly about how to obtain clear imaging results when the target's motion is more complicated.Starting from the most classical uniform turret model,the most commonly used distance-Doppler(RD)method for inverse synthetic aperture radar imaging is given.For maneuvering targets,the Doppler frequency of each scattering point is timevarying.This paper introduces the distance-instantaneous Doppler algorithm for imaging moving targets,using time-frequency analysis and decomposing multicomponent chirp signals..Instant imaging of maneuvering targets can be obtained.When the motion of the target of the ISAR imaging has greater maneuverability,the accumulation time will be less.This paper introduces a nonparametric spectrum estimation method,the Iterative Adaptive Approach(IAA),which is applied to the ISAR super-resolution field and uses a small number of echoes to obtain a clear image.Then,it was applied to the field of ISAR imaging with missing data,and a clear image of the missing data of the echo was obtained.Next,a sparse spectrum estimation method,covariance sparse iterative spectrum estimation method(SPICE),is studied.Thereby the resolution of the ISAR super-resolution imaging is further improved.A fast implementation method of SPICE based on Gohberg-Semencul(G-S)decomposition is given.For targets containing high-speed rotating components,the band spread is due to the micro-Doppler effect of the fretting target.We use the micro-Doppler effect of the micro-motion component as interference cancellation.In this paper,an ISAR imaging model with rotating component targets is established,and the micro-Doppler effect of high-speed rotating components is analyzed.Then a short-time Fourier transform(STFT)based de-micro Doppler imaging method is introduced,and a time recursive iterative adaptive approach(TRIAA)based de-micro Doppler imaging method is proposed in combination with IAA algorithm..Because the signal in the radar distance unit is sparse,this paper combines the compressed sensing signal reconstruction method with TRIAA to propose a new de-micro Doppler imaging method.Three methods were applied to the measured data with micro-Doppler effect interference,and the experimental results were analyzed and compared.Sometimes the rotating part of the target contains a lot of information about the target.In this paper,the complex empirical mode decomposition(CEMD)is applied to the separation of radar echo rigid body components and high-speed rotating component signals.The high-speed rotating scattering point echo is successfully extracted.A two-dimensional imaging model of a high-speed rotating target is also established.According to this model,a high-speed rotating target imaging method based on real-number inverse Radon transform is introduced.The signal separation method based on CEMD and the imaging method based on real-number inverse Radon transform are combined to obtain clear imaging of the propellers on both sides of the simulated aircraft..