Research On Multi-Channel SAR Ground Moving Target Detection And Parameter Estimations

Synthetic aperture radar (SAR) ground moving target, especially slowly moving target detection and parameter estimation is a hot topic in the area of SAR and has an important significance in both martial field and civilian field. Now many countries in the world are making great efforts to develop the technique of moving target detection and imaging, and research on all kinds of efficient methods for moving target detection, parameter estimation and imaging.The topic of multi-channel SAR moving target detection and parameter estimations was researched deeply in this paper, and main contents are listed as below,1. As the basic research, the principle of SAR is introduced, and the echo model of SAR moving target is built. Then, the effect of moving target Doppler center frequency and Doppler frequency rate on SAR image is discussed in common SAR imaging. Next, the range migration of moving target is analyzed here in detail, and the cross-correlation algorithm of envelope alignment, which is applied to ISAR imaging, is used for reference to revise the range migration of moving target. Furthermore, according to analysis of statistical characteristics of ground clutter, Constant False Alarm Rate (CFAR) processing, which is applied to SAR moving target detection, is discussed.2. In this paper, there is a deep research on three kinds of multi-channel moving target detection algorithms– DPCA technique, ATI technique and Space-time equivalence technique (STET), which have simple structure and less computation complexity. By time-delay and subtracting processing, DPCA can cancel clutter. Through the interferometric phase in image domain, ATI can estimate whether moving target exists. After projecting the 2-D series to the new 1-D series according to the space-time equivalence property, STET can cancel ground clutter by frequency domain filtering of the new series. Among the three algorithms, DPCA and STET is the detection method based on ground clutter suppression, while ATI is the method based on interference. The main performance parameters of these algorithms (such as maximum detectable velocity, minimum detectable velocity and improvement factor) are analyzed theoretically in detail, and plenty of simulation experiments validate the detection effect of them.3. Concerning the linear frequency-modulated characteristics of moving target signal, a kind of mathematics tool called fractional Fourier transform (FrFT), which can estimate the parameters of chirp signal well, is introduced here. Based on the deep analysis of DPCA technique and FrFT, DPCA-FrFT algorithm which can realize detection and parameter estimations of SAR slow moving target in condition of three channel system, is presented in the paper. Plenty of simulation experiments validate sufficiently that this method can not only detect the moving target, but also locate the target and estimate the velocity well.4. On the basis of the deep analysis of STET, combined with FrFT, STET-FrFT algorithm is presented here. This method can realize detection and parameter estimations of SAR slowly moving target in condition of three channel system, too. Plenty of simulation experiments validate that, STET-FrFT algorithm can realize moving target detection, localization and velocity estimations well in different signal-to-clutter ratio (SCR) and signal-to-noise ratio (SNR) conditions because of the good capability of STET for clutter cancellation and the nice attribute of FrFT for parameter estimations of chirp signal.5. Concerning the azimuth position drift and defocusing when the typical SAR imaging algorithm used to moving targets, on the basis of parameter estimations, a kind of hybrid SAR/ISAR imaging algorithm, which applied to moving target imaging, is presented in this paper. In new imaging algorithm, the matched filter technique of typical SAR imaging is adopted in range compression, while the dechirp processing of ISAR imaging is used for reference to azimuth process. Simulation experiments validate that there is no azimuth position drift and the image focus well when using the new algorithm to moving target imaging.