Research On Frequency Diversity ISAR Translational Compensation Technology

Inverse Synthetic Aperture Radar(ISAR)can work all-weather and all-weather to complete high-resolution imaging for non-cooperative targets.It is one of the important radar systems.Frequency diversity ISAR,as a new type of inverse synthetic aperture radar,can obtain target scattering information by transmitting single-frequency signals with different frequency offsets at each observation time,which can overcome the complex problems of traditional ISAR broadband transceivers.Since frequency-diversity ISAR transmits singlefrequency signals in each observation time,it cannot form an effective range profile.Compared with traditional ISAR,translational compensation has become a new problem that must be solved in frequency-diversity ISAR imaging.In response to this problem,it is necessary to conduct a more in-depth study on the imaging and translational compensation methods of frequency diversity ISAR,and provide technical support for frequency diversity ISAR to quickly obtain target information and high-resolution imaging.Therefore,this dissertation studies the following aspects:Firstly,the basic principles of ISAR imaging are introduced,and the calculation method of the distance between the target and the radar in ISAR imaging,the generation principle of Doppler frequency shift,the parameter setting method of radar imaging system and the evaluation index of imaging performance are analyzed.Finally,the translation compensation model,common ISAR translation compensation algorithms,and the principle of ISAR turntable are introduced,and simulation experiments are carried out.Secondly,in order to solve the problem that the range profile of the target cannot be obtained by transmitting a single-frequency signal at each observation time of the frequency diversity ISAR,a method based on the observation subset to form a range profile is proposed.This method can divide the echo signals obtained at different moments into multiple observation sets in a certain unit,and synthesize the echo range profile.Aiming at the problem of frequency diversity ISAR translation compensation,a joint autofocus translation compensation algorithm based on cross-correlation and minimum entropy back projection is proposed.First,synthesize the range profile of the frequency diversity ISAR singlefrequency signal echo,and use the cross-correlation algorithm to roughly estimate the target's motion parameters according to the correlation between the range profiles.Then,the search range of the minimum entropy back-projection autofocus algorithm is determined according to the estimated motion parameters,and the precise motion parameters of the target are obtained through iterative search.Finally,use the estimated motion parameters to find the phase that needs to be compensated to complete the translational compensation.At the same time,this compensation method can be used for traditional ISAR translation compensation.Simulation experiments show that the cross-correlation and minimum entropy back-projection combined self-focusing algorithm can solve the problem of frequency diversity ISAR translational compensation.Thirdly,in view of the fact that the cross-correlation and minimum entropy back projection joint autofocus algorithm proposed in this paper needs to emit a large number of single-frequency signals,and the minimum entropy back projection autofocus algorithm has the problem of large search range and long execution period,a problem is proposed.A frequency diversity ISAR translation compensation method based on fast minimum entropy sparse reconstruction self-focusing.The algorithm is based on the feature that compressed sensing can use a small amount of signal to accurately reconstruct,and takes the minimum imaging entropy value as the objective function,and finally makes the image entropy after compensation reach the minimum value.The algorithm has the characteristics of high imaging quality and few iterations.This method firstly assigns the initial value to the phase error to perform phase compensation.Then the compressed sensing sparse reconstruction algorithm is used to image the compensated echo and calculate the entropy value.According to the entropy value,the fast minimum entropy algorithm is used to calculate the compensation value for the next iteration.Finally,calculate whether the difference between the entropy value of the image of this iteration and the previous iteration meets the error requirements,exit the iteration if it meets the requirements,and continue the iteration if it does not meet the requirements.Finally,the simulation results show that the algorithm can meet the translational compensation requirements of frequency diversity ISAR.