Study On Motion Compensation And Refocusing Of Moving Ships Over The Sea

Synthetic Aperture Radar(SAR)imaging has the advantages of working in all weather conditions and even in the night.It is of great value in both military and civilian applications.A clear high-resolution SAR image contains a wealth of target’s information,which can help to achieve the targets’ detection and identification better.Ship targets usually have two complex motion states:translation and rotation due to the influence of the wind and waves over the sea.It is difficult to obtain a high-resolution image of moving ships since the traditional SAR imaging algorithm are mainly designed to process the signal from the stationary targets or scenes.The complex motion states of ship targets will result in the mismatched of the imaging parameters when we processing the signal from ship targets,which will result in the smearing of the final results.The demand for obtaining clear highresolution SAR images of ship targets is growing in order to cope with the complex and everchanging international situation and enhance China’s capability of the sea observation and surveillance.In this dissertation,the shortcomings of the existing algorithms are analyzed.And after the depth study in the existing algorithms which are used to solve the practical problems in the refocusing of moving ships,the research on motion compensation and refocusing technology for ship targets is carried out.One of the main purposes of the dissertation is to solve the main problems of the parameter estimation and spectral winding in the process of motion compensation,the other is to obtain clear and high-resolution SAR images of ship targets.The main research contents of this dissertation are as follows:In Chapter 2,both the rotation model of ship targets and the geometric relationship and signal model of ship target imaging by SAR system are introduced.At the same time,the basic process of ship targets refocusing is introduced on the basis of existing algorithms.And the key problems and existing corresponding processing algorithms in the process of detection,extraction and separation of ship targets,motion compensation and azimuthal focusing are summarized and concluded respectively.The subsequent contents of this dissertation will discuss and study the algorithms of ship targets refocusing basing on the basic models and theories introduced in this chapter.In Chapter 3,an improved motion compensation algorithm for ship targets based on Doppler center estimation is proposed to solve the problems of motion compensation in the refocusing of ship targets,which break through the limitations and defects of the existing DPEA algorithm.The proposed algorithm firstly adopts the method of sliding window to divide the full-aperture data into sub-apertures.And then the Doppler center of each subaperture are estimated.Secondly,the method of least squares criterion is used to obtain the variation curve between the Doppler center and the azimuth slow time.The instantaneous range between the target and the radar is obtained through the integral inversion of the variation curve.Finally,the motion compensation of the ship target is completed by the fullaperture Deramp processing.Compared with the existing DPEA algorithm,the proposed algorithm reduces the dependence on the accuracy of the Doppler center through the least squares criterion method,which effectively improves the robustness of the algorithm.In addition,the proposed algorithm has the ability to acquire the higher terms of the instantaneous range which breaks the limitation of the existing DPEA algorithm,which makes it be adaptable to the situations of long synthetic aperture time or complicated target motion conditions.Finally,the effectiveness of the proposed algorithm is verified by the processing results of simulated data and airborne measured data.In Chapter 4,an algorithm based on minimum entropy principle is proposed for refocusing moving ships in BP image of side-looking SAR mounted on maneuvering platform.The algorithm proposes a concept of relative velocity between the target and the radar.For obtaining the phase error caused by the translation of the ship target,the two-dimensional wave-number domain expression of the BP image of the ship target is accurately derived through studying the basic principle of the BP algorithm for ship targets imaging.Then,a ship target refocusing algorithm based on the minimum entropy principle is proposed based on the accurately expression.Transforming the problem of minimum entropy into the problem of nonlinear quadratic optimization.And then,compensate the error phase iteratively by using the Gauss-Newton method.the focused ship target and the relative motion velocity of the ship target are obtained simultaneously when the entropy of the image is minimized.The algorithm utilizes the information of all scattering points of the target which can avoid selecting the special significant points in the image.It has high robustness and accuracy.Simulation experiments and the processing results of real data verify the effectiveness of the proposed algorithm.In Chapter 5,a ship target refocusing algorithm based on a method called "squint minimization" is proposed to solve the problems of 2-D wavenumber spectrum off-centering and squint in squint SAR image obtained by BP algorithm.The algorithm adopts a method to solve the problem which is based on the perspective of wave-number spectrum recovery by analyzing the mechanism of BP algorithm.Firstly,the wavenumber spectrum of the ship target in the squint SAR image obtained by BP algorithm is analyzed in detail.And then,the wave-number spectrum of the ship targets is orthogonalized by the squint minimization method which is based on the cascade of wave-number spectrum inclination correction and the alignment.Finally,the motion compensation of the ship target is completed through the proposed algorithm in Chapter 4.The computational efficiency of the proposed algorithm is significantly better than the existing related algorithms since it does not have any interpolation operation during the imaging process.And it is easy to implement in engineering.Finally,the proposed algorithm is validated by the simulation data and the real data from GF-3 satellite.