| The passive radar imaging system exploits the opportunity illuminator as its transmitter.The system realized the detection of targets we are interested in by deploying multiple receivers around the target area.Comparing with the traditional radar imaging system,the passive radar imaging system has advantages of low cost,robustness against to deliberate directional inference and strong survivability.Since receivers of the passive radar imaging system can be deployed in a flexible way,the system also has advantage over traditional ones on the detection of the stealth target.Taking account of the various advantages above,wide attention has been attracted from many research organizations.Though the passive radar imaging system improves the detection ability of the traditional ones,some challenges exist in the realization of the system which remains to be solved.The challenges of the system mainly contain two aspects,1)usually,the opportunity illuminators are not designed for the application of radar detection.The transmitted signal received by receivers is continuous.Therefore,the Stop-Go model assumed in traditional synthetic aperture radar system is not hold in the system.What's worse,the signal transmitted by the opportunity illuminator is narrow bandwidth which makes the range resolution cell poor.2)though the flexible deployment of the receivers improves the detection performance of the system,it makes the imaging process complex.Aiming at solving the problems listed above,the manuscript expands correlative research on improving the system performance mainly from three aspects.Firstly,the model of the passive radar imaging system is built based on the principle of tomography.On this basis,the mathematical model of the echo signal is derived.The relationship of the among the spatial sampling spectral domain of the echo signal,the geometry of the system and the resolution ability is analyzed.Further,the optimized method for deploying the receivers are developed from the viewpoint of point spread function.Then,the research of high resolution imaging technique is developed.Taking account of the sparse distribution of the scatters of the target,a high-resolution imaging algorithm is developed based on the compressed sensing.Finally,the influence of the imperfect motion of the moving platform on the received signal is analyzed.The contaminated signal model is reformed.The corresponding compensation method is proposed for improving the performance of the imaging system by correcting phase errors.The detailed research work of the manuscript is arranged as follows.1.The basic geometry of the passive radar imaging system is built.On this basis,the model of the echo signal is derived in theory.The various of the distribution of the spatial sampling of the echo signal with the number of the illuminators is analyzed.From the viewpoint of the spatial sampling of the echo signal,the resolution ability of the system is studied.Further,the point spread function of the system is derived.Based on the relationship of the deployment of the receivers and the point spread function of the system,the method for optimizing the geometry of the system is studied.2.By analyzing the echo signal model from the viewpoint of tomography,the Fourier transformation between the echo signal and reflectivity function of the target scene is derived.When the number of illuminators is large,the spatial sampling of the echo distribute densely,and the target scene can be reconstructed with the method of direct Fourier transform(DFT)based on interpolate method.In the case of the illuminators is rare,the spatial sampling of the echo is sparsely distributed.It is hard to interpolate the spatial sampling spectrum with high accuracy.Therefore,the imaging algorithm is developed under the polar format coordinate.By designing the convolution kernel function which is matched with the spectrum of the spatial sampling of the echo,the polar format imaging algorithm can realize the reconstruction of the target.Since the imaging process do not require the interpolation operation,the polar format imaging algorithm performs well when illuminators are rare.3.In the real world,the received echo usually limited by the number and the distribution of the receivers.Therefore,the echo obtained may be gaped compared with the ideal ones.The performance of the traditional imaging algorithm will subject to degrade seriously.To improve the performance of the system,high resolution imaging algorithm is studied based on the compressed sensing.Further,the relation between the correlation of the dictionary matrix and the imaging algorithm is analyzed.By studying the relation between the geometry of the system and the correlation of the dictionary matrix,the positions of the receivers can be optimized by minimizing the correlation of the dictionary matrix based on the method of Simulated Annealing(SA).Simulations show that the quality of the reconstructed image is improved significantly after the optimization.4.The echo would be contaminated for kinds of reasons,such as imperfect motion of the moving platform,the propagation error caused by the ionosphere,and so on.This will degrade the quality of the reconstructed image seriously.For refocusing the reconstructed image,the compensation methods which can be used for correcting phase errors of the echo are studied.The model of the system is rebuilt to fit with the imaging process in real world.By analyzing the influence of phase errors of the echo on the imaging process,the phase errors are estimated and compensated based on the fixed-point iteration method.In addition,the compensation method is also studied in the sparse imaging process.By minimizing the relative error of the reconstructed image,phase errors of the echo are well estimated and compensated.The effectiveness of the algorithm is confirmed by simulations.The compensation methods introduced above do not assume the detail model of the phase errors during the estimation process,therefore they are nonparametric method and can be used for compensating phase errors of any form. |
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