Study Of ISAR Imaging For Maneuvering Targets Based On New Methods Of Signal Processing

Synthetic aperture radar is a high resolution microwave imaging radar and has the characteristics of all-weather、day/night and long distance, widely used in the fields of national security and economy. Based on the operating mode, it can be divided into Synthetic Aperture Radar and Inverse Synthetic Aperture Radar. In the field of ISAR imaging of maneuvering targets, as to the smooth movement targets, the received signal could be represent by linear frequency modulated(LFM) signal mode, however as to the target with complex motion, the echo signal should be characterized as the model of multi-component polynomial phase signal(PPS) that is typical non-stationary signals. In the application, the quality of the radar images of targets depends on the signal processing technique, so the quality of the radar images can be improved greatly by the signal processing methods. This paper divides the echo of the maneuvering targets into four categories from the aspects of parameter estimation, time frequency analysis and signal decomposition, they are multi-component linear frequency modulated signal mode, multi-component polynomial phase signal mode, multi-component fourth-order polynomial phase signal and multi-component amplitude modulation and frequency modulation signal model respectively. For these four echo signal models, the corresponding signal processing method is presented to improve the quality of ISAR images of maneuvering targets. The main work of this paper is summarized as follows:1. Detailed analysis of the characteristics of the echo signal that from maneuvering targets and analysis of the effect of target motion on Doppler and radar images combine with simulated data. Finally analysis of the characteristics of ISAR imaging of maneuvering targets. The characteristics of the echo signal of the targets which have a maneuvering motion are summarized and analyzed in detail.2. For the linear frequency modulated(LFM) signal mode, the algorithm for estimating the parameters of LFM signal based on the Matched Fourier transform is analyzed in detail. This method has the advantage of high precision parameter estimation. Finally this method is applied to ISAR imaging of maneuvering targets, effective solve the problem of azimuth defocusing and improves the images quality greatly. Moreover, in case of the existence of a certain noise, this method is still valid.3. Due to the deficiency of MFT, a new algorithm for estimating the parameters of LFM signal based on the Quadratic Phase Function(QPF) is quoted. This algorithm can estimate the parameters of the LFM signal for each component with only one-dimensional maximization and the amount of calculation reduced greatly. QPF algorithm has the advantage of high precision parameter estimation. Finally, this method is applied to ISAR imaging of maneuvering targets and improved the images quality greatly. Moreover, in case of the existence of a certain noise, this method is still valid.4. For the cubic phase function, a new algorithm for estimating the parameters of CPF signal based on the Extension Form of Match Fourier Transform is proposed. Compared with the MFT algorithm, this method maintains a high estimation accuracy and does not increase calculation, the asymptotic statistical performance is analyzed by the first order perturbation analysis of maxima of random functions. The theoretical and simulated results demonstrate high precision of this algorithm. Finally this new algorithm is used in ISAR imaging of maneuvering ship targets and combine with the CLEAN technique to separate different signal components successfully, the radar images quality improved greatly.5. For the fourth-order polynomial phase signal, a novel method for estimating the parameters of multi-component polynomial phase signal based on the Product Time Phase Derivative Distribution(PTPDD). The PTPDD algorithm can effectively suppress the influence of cross-terms and can estimate the parameters of the PPS for each component with only one-dimensional maximization. Finally this new method is applied in the ISAR imaging of complex motion ship targets and combined with the Range-Instantaneous-Doppler(RID) technique, the high quality instantaneous ISAR images can be obtained, especially under the existence of a certain noise, this method is still valid6. The time frequency analysis of the high order polynomial phase signal are considered and the Modified S-Distribution(MSD) is presented in this dissertation. MSD algorithm is improved from SD, for linear frequency modulated(LFM) signal, the SD is only completely concentrated along the instantaneous frequency of it. Compared with SD, the MSD has better time frequency resolution in the analysis of cubic polynomial phase signal. As to the multi-component signals, the MSD can be cross-terms free based on the CLEAN technique. Finally the MSD is used in the ISAR imaging of maneuvering target, in the azimuth direction to replace the Fourier transform and the image quality is improved greatly.7. A new method of Shipborne Inverse Aperture Radar imaging for the maneuvering targets based on adaptive Chirplet decomposition is proposed. Due to complexity of the scatterer’s echoes from the target in S-ISAR imaging scenario this paper will describe it as multicomponent AM-FM signals and the signal decomposition technique based on the Chirplet basis function is adopted to deal with it. Signal decomposition is a common time-frequency analysis technique, by decomposing the signal into a linear combination of a series of basic functions, and then achieve the purpose of signal analysis and processing by analyzing the simple basic signal and their connection. Finally this method is used in the ship-borne ISAR imaging of ship target, the high quality instantaneous ISAR images can be obtained,, especially under the existence of a certain noise, this method is still valid.