Research On New Methods For ISAR Motion Compensation And Imaging

Inverse synthetic aperture radar(ISAR) is a high resolution imaging system for the non-cooperative target. It has the capability of sensing non-cooperative target day and night in all weather from long range. The mutual complementation of radar imaging, visible light imaging and infrared imaging techniques can significantly improve the ability of target recognition. ISAR plays an extremely important role in the exploration of deep space, strategic defense, maritime rescue and other fields.With the development of ISAR application and the increasing demand of imaging quality, the key technology of ISAR imaging, such as motion compensation and imaging algorithms, still needs to be improved and developed in order to adapt to new challenges. Therefore, further discussion and study on the key technology of ISAR imaging is very necessary. An emphasis will be put on the research of ISAR motion compensation and imaging methods in this dissertation. The main work can be summarized as follows:Chapter 1 is the introduction. It reviews the development background of SAR and ISAR. The basic principle of ISAR imaging is summarized. Moreover, motion compensation and imaging algorithms are briefly introduced. Lastly, main contents of this dissertation are presented.The technique of two-dimensional ISAR imaging based on the compressed sensing theory is studied in chapter 2. This imaging technique consists of two parts: imaging algorithm and motion compensation. The redundancy of sparse scene is utilized to reconstruct the ISAR image, so the number of samples is much less than normal. In this chapter, a two-dimensional ISAR imaging algorithm based on the compressed sensing theory is proposed. While the result of processing the random pulse repetition interval(PRI) echo data by using the conventional motion compensation methods are not satisfactory. This chapter presents an effective motion compensation method to address the problem. This chapter also proposes a novel motion compensation method which based on the designing structured Gram matrices optimization theory. This motion compensation method takes full advantage of the correlation of all range profiles through constructing cross-correlation matrix to achieve multi-parameter estimation. Furthermore, this motion compensation method can be directly applied to the random PRI echo data, therefore it is a good candidate of ISAR motion compensation method for compressed sensing imaging.In chapter 3, the problem of ship target ISAR imaging is discussed deeply. Under the heavy sea state, the three-dimensional motion consists of roll, pitch and yaw, which caused by the ocean waves,is the main source of effeftive rotation. The time-varying of Doppler frequency is mainly caused by the change of effective rotation vector. The time-frequency distribution series(TFDS) is a kind of time-frequency analysis method, which has high resolution both in time and frequency domains.Moreover, it can be used to overcome the defocusing effect, caused by time-varying of Doppler frequency. However, the complexity of this algorithm is also high. To solve this problem, an improved TFDS algorithm is introduced in this chapter. The efficiency of the original algorithm has been significantly improved. When compared with time-frequency analysis method, range Doppler imaging algorithm has a better real-time performance. In order to reduce the influence of Doppler frequency time-varying on imaging and to improve the image quality of target, it is necessary to select the optimal imaging time. In this chapter, based on the concept of variance, an rms Doppler spread definition is proposed to choose the optimal imaging time for ISAR. This real-time algorithm can work automatically instead of artificial intervention. Better ISAR images can be obtained by using the data segments which are selected through the proposed algorithm.In chapter 4, the FMCW-ISAR imaging technique is studied. The FMCW-ISAR transmits a linear frequency modulated(LFM) signal in a relatively long time interval when compared with the pulse length of coherent pulse radar. During such an interval the assumption of stop and go is no longer valid, the target motion within the sweep should be taken into account. In this chapter, two problems are discussed on FMCW-ISAR imaging technique, i.e., the phase compensation and the point spread function(PSF) of the imaging system. By analyzing the model of echo signal, the phase error, which is related to the motion parameters, is derived. According to the characteristics of the phase error, an autofocus algorithm based on motion parameter estimation is introduced. And we get the exact form of PSF from the echo signal in wave-number domain.Chapter 5 concludes the whole dissertation and point out the issues to be further studied as well.