A non-local vectorial total variational model for multichannel SAR image speckle suppression

This paper aims at the multichannel synthetic aperture radar(SAR)image speckle reduction.This paper proposes a novel energy minimized regularization model for multichannel image denoising,which is an extension of the non-local total variational model for gray-scale image.It contains two terms,namely the vectorial data fidelity term and the non-local vectorial total variation term.The latter is constructed by high-dimensional non-local gradient that contains the structure information of the multichannel image.The existence and the uniqueness of the solution of the model are proved.A fixed point iterative algorithm is designed to acquire the solution of this model.The convergence property of this algorithm is proved as well.This model is applied to the multipolarimetric and multi-temporal RADARSAT-2 images despeckling.The result shows that this model performs better than the original vectorial total variational model on texture preserving.     

星载SAR在轨成像实时处理算法研究

星载合成孔径雷达(SAR)分辨率和幅宽的不断提高,其产生的原始数据率越来越大,采用在轨实时成像处理形成图像,在图像域再进行传统的图像数据处理和传输,有助于降低星-地数据传输速率,为了提高星载SAR在轨成像处理的实时性,文章分析了星上特殊条件对星载SAR处理算法实时性所提出的约束,对RD、波束域、CS等经典的星载SAR成像处理算法的运算量进行了比较,以CS算法为例,研究了相位补偿因子对CS成像处理算法的实时性影响,提出了一种补偿因子区域不变的CS成像算法,它极大地减少了成像处理算法的运算量,并通过仿真实验结果验证了该算法的有效性。     

An extended chirp scaling algorithm for spaceborne sliding spotlight synthetic aperture radar imaging

A system impulse response with low sidelobes is critical in synthetic aperture radar（SAR） images because sidelobes contribute to noise and interfere with nearby scatterers. However,the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis（SPECAN） technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling（CS） algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations（FFTs） is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.     

Advanced fractal approach for unsupervised classification of SAR images

Unsupervised classification of Synthetic Aperture Radar (SAR) images is the alternative approach when no or minimum apriori information about the image is available. Therefore, an attempt has been made to develop an unsupervised classification scheme for SAR images based on textural information in present paper. For extraction of textural features two properties are used viz. fractal dimension D and Moran’s I. Using these indices an algorithm is proposed for contextual classification of SAR images. The novelty of the algorithm is that it implements the textural information available in SAR image with the help of two texture measures viz. D and I. For estimation of D, the Two Dimensional Variation Method (2DVM) has been revised and implemented whose performance is compared with another method, i.e., Triangular Prism Surface Area Method (TPSAM). It is also necessary to check the classification accuracy for various window sizes and optimize the window size for best classification. This exercise has been carried out to know the effect of window size on classification accuracy. The algorithm is applied on four SAR images of Hardwar region, India and classification accuracy has been computed. A comparison of the proposed algorithm using both fractal dimension estimation methods with the K-Means algorithm is discussed. The maximum overall classification accuracy with K-Means comes to be 53.26% whereas overall classification accuracy with proposed algorithm is 66.16% for TPSAM and 61.26% for 2DVM.     

Occurrence rate of SAR arcs during the 23rd solar activity cycle

The occurrence rate of SAR arcs during 1997–2007 has been analyzed based on the photometric observations at the Yakutsk meridian (Maimaga station, corrected geomagnetic coordinates: 57°N, 200°E). SAR arcs appeared in 114 cases (∼500 h) during ∼370 nights of observations (∼3170 h). The occurrence frequency of SAR arcs increases to 27% during the growth phase of solar activity and has a clearly defined maximum at a decline of cycle 23. The SAR arc registration probability corresponds to the variations in geomagnetic activity in this solar cycle. The dates, intervals of UT, and geomagnetic latitudes of SAR arc observations at the Yakutsk meridian are presented.     

SAR performance-based fault diagnosis for electro-hydraulic control system: A novel FDI framework for closed-loop system

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation (FDI) issues for control systems. However, the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems. To avoid these difficulties, a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed. Under this framework, a so-called performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability, accuracy, and rapidity (SAR) respectively. The criteria for quantification, normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given. FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space. A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.     

Denoising methods in interferometric SAR images processing

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星机双基地SAR的工作模式研究

由于卫星速度远快于飞机,传统的条带式已不适用于星机双基地SAR。有文献提出一种"双向滑动聚束式",但该模式存在成像场景长度短、成像算法复杂等缺点。利用星机双基地SAR接收机端信噪比高的特点,提出两种新的工作模式,分别是"卫星宽波束、飞机反向滑动聚束式"和"双宽波束式"。当仅展宽飞机波束时,"双宽波束式"演变为"宽波束接收式"。从理论上分析两种工作模式的可行性,并计算得出典型参数下的技术指标。相比于"双向滑动聚束式",在方位分辨率相等的条件下,这些新模式的场景长度都明显增加。但除"宽波束接收式"外,所提两种新模式将使返回卫星的单基地回波无法使用。文末分析了几种工作模式的适用场合。     

面向时序InSAR的卫星任务规划框架设计

随着国内自主雷达卫星和差分干涉合成孔径雷达技术(D-InSAR)及衍生的时序InSAR技术的发展,以时间序列上重复观测为主的长周期形变监测的应用与日俱增。对遥感卫星地面任务规划系统来说,规划和管理大量有时序关联的重复任务,从而最大限度地满足观测要求,是提升以形变监测为使命的雷达卫星运控效率的关键。在综合考虑雷达差分干涉任务序列性、一致性、周期性特征的基础上,设计了一种面向雷达卫星时序InSAR类型任务的规划框架,旨在规划序列任务时,考虑序列整体特性,进行序列任务组间的冲突检测。基于此方法,对现有的地面任务规划系统进行了优化升级,验证了框架的有效性。结果证明:该方法可快速、自动进行序列任务冲突消解,可为长周期序列任务的规划和管理提供设计参考。     

针对星载 SA R的散射式干扰应用研究

针对星载SAR的特点,简述了散射波干扰的干扰原理,并针对其工程实现中的几个关键问题进行了分析。最后针对典型星载SAR进行了干扰验证试验,给出了试验结果,证明了该样式的有效性。