低波段天基雷达射频干扰机理及抑制方法

天基合成孔径雷达(SAR)是一种重要的主动遥感设备,在测绘、目标警戒、资源探测等方面具有独特的全天时、全天候优势。但由于低波段电磁频谱异常拥挤复杂,也容易受到其他无线电设备的非蓄意射频干扰(RFI)。本文针对工作于P、L波段的天基SAR系统,分析其常见的地面射频干扰源及其干扰机理,并构建典型的窄带与宽带干扰模型,比较分析了频域陷波、最小均方(LMS)算法、自适应线谱增强(ALE)、特征子空间分解与时频滤波等多种干扰抑制算法,并在卫星实测数据的基础上进行仿真验证抑制宽带干扰的有效性。仿真结果表明:时频滤波算法抑制宽带干扰效果最好,造成的信号损失最小,能够为后续天基合成孔径雷达的抗干扰算法设计提供决策依据。     

雷达图像幅值空间变迹算法

针对旁瓣抑制，给出了一种幅值空间变迹算法。该算法与一般空间变迹法不同，主要通过每一像素点幅值与相邻两个Nyquist采样点幅值之和做比较来判别该点处于主瓣还是旁瓣，来加以不同处理。在整数倍Nyquist采样的情况下，这种算法不仅压低旁瓣还使主瓣变窄，能得到比传统SVA更高的分辨率，在非整数倍Nyquist采样的情况下也比SVA具有更好的稳健性。对此进行了实验研究，结果证实了该算法的有效性。     

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.     

一种实用的弹-地通讯接口设计

为实现普通个人计算机和弹载计算机间的弹一地通讯,对某型弹载计算机专用的增强型通讯接口电路和通讯协议进行了分析,设计了与之匹配的适用于普通计算机的通讯接口硬件电路,并进行了基于VB6．0的通讯程序设计。实际测试及运行结果说明,设计的通讯接口可实现高速、远距离、高可靠性的弹一地数据通讯,误码率低。     

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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