一种新的SAR图像内波检测与参数估计方法

提出了一种SAR图像海洋内波检测与参数估计的新方法。通过对传统的Radon变换进行改进,将图像在椭圆区域内进行积分归一化,达到海洋背景下弱直线检测的目的。利用滑动窗口的思想结合椭圆域归一化Radon变换检测内波区域,通过对变换域的数据进行分析处理与计算,得到内波传播方向和内波波长参数。通过对实测SAR图像数据进行处理的结果可知,采用该方法对内波SAR图像进行处理不需要人工干预,能很好地定位内波位置,获得的内波参数与观测结果相符。     

An approach for refocusing of ground fast-moving target and high-order motion parameter estimation using Radon-high-order time-chirp rate transform

Long synthetic aperture time can improve the imaging quality of a ground moving target, whereas a moving target may be severely smeared in the cross-range image due to the range migration and the Doppler frequency migration. In this paper, the effects of the third-order Doppler broadening and Doppler ambiguity of a fast-moving target are considered. To address these issues, a novel motion parameter estimation method named high-order time-chirp rate transform (HTRT) is proposed, and then a new synthetic aperture radar (SAR) imaging method based on Radon-HTRT (RHTRT) for a ground moving target is developed. The major contributions are as follows: 1) The proposed SAR imaging method can eliminate the Doppler ambiguity effect. 2) The proposed method can realize longer time coherent integration than Radon–Fourier transform (RFT) and Radon–fractional Fourier transform (RFRFT) methods. 3) The proposed method is computationally efficient since HTRT can obtain the motion parameters of a moving target via performing the 2-dimensional (2-D) fast Fourier transform (FFT). Both the simulated and real data processing results show that the proposed method can finely image a ground moving target in a high signal-to-clutter and noise ratio (SCNR) environment.     

基于模糊函数估计和变分泛函数优化的含噪声模糊图像复原算法

针对摄影图像中常见的噪声和模糊同时退化图像的问题,提出一种Radon变换估计模糊函数结合变分泛函优化的图像复原算法。算法首先利用方向滤波器对图像去噪,然后利用Radon变换以去除方向滤波在模糊函数估计中引起的偏差,再利用模糊函数通过去卷积操作去除模糊,最后在去模糊的基础上利用 L0梯度范数的变换泛函的优化算法,去除剩余噪声从而对图像进行复原。实验表明,该算法可以有效地恢复摄影图像中的场景。     

高斯噪声下伪码-线性调频复合信号参数提取方法

针对目前雷达信号参数估计算法在某种环境中性能急剧下降,甚至失效的问题,提出一种基于多相滤波器组和高阶累积量联合处理的伪码-线性调频复合信号参数估计算法.该算法首先利用多相滤波器组实现信号在频域上快速均匀划分,然后对输出的每个子带信号进行三阶累积量对角切片的短时估计,有效抑制高斯噪声的干扰,并经过包络检波后得到复合信号完整的时频矩阵,最后通过时频图像的Radon变换和频率曲线的提取实现信号伪码数目、码元宽度、调频斜率、信号载频、带宽以及起止频率的提取.仿真结果表明,该方法在信噪比大于-11 dB时的估计精度较高.     

基于主导边界Radon变换的SAR目标方位角估计方法

针对仅利用主导边界估计带来的目标垂直与水平方位的模糊问题,提出一种基于主导边界Radon变换的合成孔径雷达(SAR)图像目标方位角估计方法。该方法基于分割图像中目标主导边界长度的判别准则进行解模糊,同时引入目标主导边界Radon变换的估计算法,解决了传统主导边界算法中长、短主导边界不易分离的问题。MSTAR实测数据的实验结果表明提出的算法具有良好的精确度和适应性。     

ISAR imaging of complex motion targets based on Radon transform cubic chirplet decomposition

For targets with complex motion, the echo of inverse synthetic aperture radar (ISAR) is a time-varying frequency signal in azimuth. Hence, the traditional range-Doppler (R-D) algorithm based on a constant frequency is invalid. In this letter, a novel ISAR imaging method for targets with complex motion is presented. The echo in azimuth is characterized as an amplitude-modulated (AM)-cubic phase signal, which is closer to the real ISAR scene, and Radon transform cubic chirplet decomposition (RTCCD) algorithm is proposed to process the signal. By introducing Radon transform and improved cubic chirplet function (CPF), the proposed algorithm estimates the chirp rate and the cubic chirp rate simultaneously to avoid error accumulation. Therefore, the parameter estimation precision is improved, and a high quality ISAR image can be obtained. Simulations and real data experiment validate the effectiveness of the proposed method.     

基于SVD和Radon变换的抗旋转攻击盲水印算法

为了提高传统基于奇异值变换（SVD）的数字水印抗几何攻击能力,提出一种在小波变换域将Radon变换和奇异值变换相结合的抗旋转攻击鲁棒性水印算法。将宿主图像进行小波变换,对变换后的低频子带进行奇异值分解,将经过仿射变换置乱后的二值水印图像嵌入到奇异值中。在水印嵌入操作上采用了奇偶量化嵌入算法从而实现了二值水印图像在水印检测时的盲提取;同时在水印检测之前,利用Radon变换检测算法对待检测图像进行几何校正,然后提取水印信息。实验结果表明,该算法对于噪声感染、滤波、JPEG压缩等常规信号处理的鲁棒性优于传统的基于SVD的数字水印算法,同时对于旋转几何变换具有很好的鲁棒性。     

A low complexity coherent integration method for maneuvering target detection

This paper considers the coherent integration problem for detecting a maneuvering target with complex motions, where the velocity, acceleration and jerk result in respectively the range migration (RM), linear Doppler frequency migration (LDFM) and quadratic Doppler frequency migration (QDFM) within the coherent pulse interval. A new coherent integration algorithm based on keystone transform (KT) and generalized dechirp process (GDP), i.e., KTGDP, is proposed. In this method, KT and fold factor searching are first employed to correct the RM, and then GDP is applied to estimate the target's radial acceleration and jerk. With the estimated motion parameters, LDFM and QDFM can be compensated and the coherent integration can be achieved via Fourier transform. In addition, at the cost of some performance loss, a fast coherent integration method combing KT and cubic phase function (CPF), i.e., KTCPF, is also introduced to further reduce the computational complexity. Compared with the generalized Radon–Fourier transform (GRFT) method, the proposed algorithms can avoid the blind speed side lobe (BSSL) effect and have much lower computational burden. Finally, we evaluate the performance via some numerical simulations.     

基于Radon变换的指纹图像滤波增强方法

基于Gabor滤波实现过干指纹图像的增强是一种较好的方法,如何估计Gabor滤波器的参数是解决问题的关键。本文采用Radon变换来估计Gabor滤波中的方向和频率,然后进行Gabor滤波增强。通过对FVC2000指纹库中的部分过干的指纹图像进行增强,结果表明,该方法增强效果明显,处理速度较快。     

Parameter estimation of moving targets in the SAR system with a low PRF sampling rate

In the synthetic aperture radar(SAR)system with low pulse repetition frequency(PRF)sampling,it is difficult for the motion parameters estimation of the moving targets,because of the Doppler spectrum ambiguity and Doppler centroid frequency ambiguity of the echo signals.Considering that moving targets are sparsely distributed in the observed scene,their positions and velocities can be reconstructed by using the compressed sensing(CS)technique.In this paper,the range-walk correction are implemented by the Keystone transform and the sparse range-walk correction(SRWC),then the CS technique is proposed to reconstruct motion parameters by processing the azimuth signals of the moving targets.Experiments using the simulated and real data are performed,and the results confirm the validity of the proposed method.     

一种新的多普勒中心频率实时估计算法

针对可编程器件实现合成孔径雷达多普勒中心频率实时估计问题,提出了复符号估计算法．新算法利用合成孔径雷达回波先验零均值圆对称复高斯分布统计特性,运用复反正弦定律非线性估计回波相关值,降低了多普勒中心频率估计复杂度,适合硬件实现．分析和仿真结果表明,与已有的符号多普勒中心频率估计算法相比,复符号多普勒中心频率估计算法不但大大降低了运算量和相应硬件的实现面积,提高了整个多普勒中心频率估计运算部件的运行效率,而且具有与其相当的估计性能．     

基于回波信号的环视SAR成像运动参数估计

环视合成孔径雷达(Circular-scanning SAR) 主要用于在 导弹精确末制导中进行景象匹配,而雷达的运动参数是实现精确制导的关键因素之一。运动 参数可以由GPS和IMU直接测得,也可以通过从实测数据中估计得出。由于环扫SAR雷达平台 具有运动速度快、非匀速运动和大斜视等特点,因此对多普勒参数估计精度要求比较高。而 由现有GPS和IMU测得的雷达运动参数由于具有较大误差一般很难满足成像精度要求,因此本 文将两者结合针对实际雷达和运动情况,对运动参数作了精确估计和运动补偿,以适应环扫S AR高分辨率成像和精确制导的要求。仿真数据处理的结果表明,该方法能准确地实现上述参 数估计,从而显著提高了环视SAR系统输出图像的质量。实测数据则证明了该方法具有很强 的实用性。     

基于FRFT的线性调频信号映射方法的快速算法

针对基于分数傅立叶变换(Fractional Fourier transform，FRFT)的线性调频信号(LFM)的参数估计方法，提出了基于Radon变换的判决准则，并建立了相应的快速算法。该映射方法将具有同样调频斜率、同样多普勒中心频率、不同初始相位的信号映射到同一个点。该快速算法的计算量等同于FRFT的计算量，计算结果的精确度取决于连续两次的FRFT运算。     

运动模糊图像PSF参数估计方法改进及图像复原

运动模糊图像复原的目的是改善运动图像质量,从而为图像处理任务提供高质量的清晰图像以保证算法能够准确获取图像信息,其中运动模糊图像的点扩散函数（PSF）求解是影响复原图像质量的关键步骤。针对现有运动模糊图像PSF参数估计方法中存在的估计误差大、有效估计范围有限等问题,在分析频谱图像特征的基础上,提出一种改进的PSF参数估计方法。通过图像增强处理和形态学变换去除频谱图像中的十字亮线和噪点干扰,获取形态合适的条纹图像以完成Radon变换检测。利用二值频谱图像的条纹特征自适应地控制形态学运算精度,从而保证算法的执行效率和鲁棒性。对条纹进行边缘测定,消除由条纹自身宽度导致的角度估计误差,以提高参数估计结果的精度。实验结果表明,该方法能够提高模糊参数估计的准确率和有效估计范围,由此构建的PSF能复原出更加清晰的重建图像,复原图像总体峰值信噪比不低于25 dB。     

利用四参数Chirplet分解方法估计SAR多普勒调频斜率

提出了基于一个距离门信号的四参数Chirplet分解方法，估计合成孔径雷达(SAR)回波的多普勒调频斜率。距离压缩后的回波数据，每个距离门的信号都是由一系列的Chirp分量组成的。利用四参数Chirplet分解方法，能够检测出这一信号中的一个或几个Chirp分量，估算出多普勒调频斜率，其结果被应用于合成孔径雷达成像的方位压缩处理。仿真及真实回波数据的计算表明，无论在精度还是运算时间上，其结果都优于目前已有的实时估计方法。     

The generalized Radon transform: Sampling, accuracy and memory considerations

The generalized Radon (or Hough) transform is a well-known tool for detecting parameterized shapes in an image. The Radon transform is a mapping between the image space and a parameter space. The coordinates of a point in the latter correspond to the parameters of a shape in the image. The amplitude at that point corresponds to the amount of evidence for that shape. In this paper we discuss three important aspects of the Radon transform. The first aspect is discretization. Using concepts from sampling theory we derive a set of sampling criteria for the generalized Radon transform. The second aspect is accuracy. For the specific case of the Radon transform for spheres, we examine how well the location of the maxima matches the true parameters. We derive a correction term to reduce the bias in the estimated radii. The third aspect concerns a projection-based algorithm to reduce memory requirements.     

Fast hyperbolic Radon transform using chirp-z transform

The hyperbolic Radon transform plays an important role in seismic data processing for its ability to focus seismic events in the transform domain. Traditional algorithms based on direct implementations, however, are inefficient with limited applications for processing large data sets. A new algorithm is presented for fast computation of the hyperbolic Radon transform and its sparse calculations. It uses interpolation procedures to stretch the data along time axis and efficiently computes the summation paths in the new coordinates via the chirp-z transform which is carried out by fast Fourier transform (FFT). The proposed fast algorithm is then used within the deconvolutive form of the Radon transform and iterative sparse algorithms for effective decomposition of CMP gathers with an improved temporal resolution, compared to the traditional Radon transforms. The effectiveness of the new algorithm are confirmed on sparse velocity-stack inversion, primary and multiple separation, high-quality stacking, and automatic velocity model building. The tests show that sparse velocity-stack inversion using the new algorithm is even more efficient than the traditional velocity scan, both in resolution and speed. Furthermore, numerical tests show the superiority of the proposed algorithm over the state-of-the-art fast algorithms, based on butterfly scheme and log-polar convolutions, demanding less computational complexity.     

复数Curvelet 变换域复数高斯尺度混合图像降噪

提出了一种基于复数Curvelet 变换域复数高斯尺度混合（CGSM）模型的图像去噪方法．指出Curvelet 变换重构图像存在“划痕”和“嵌入污点”的主要原因是Curvelet 变换域存在频谱混叠,为此,采用复数小波变换和 改进的Radon 变换分别代替原Curvelet 变换中的实小波变换和Radon 变换．构造了具有抗混叠性能的复数Curvelet 变换．本文同时把高斯尺度混合（GSM）模型扩展到复小波域,形成对复小波系数的幅值和相位信息具有有效捕捉 能力的复数GSM 模型,并在复数Curvelet 变换域,采用贝叶斯最小平方（BLS）估计器对CGSM 模型下含噪复系数 进行有效估计,从而实现降噪．实验结果表明,无论是用PSNR 指标评估,还是在视觉效果上,本文方法的去噪性能 均好于传统Curvelet 去噪、Curvelet 域HMT 去噪和小波域BLS-GSM 去噪．本文方法在有效去噪的同时,具有很好 的图像边缘和细节保护能力．     

Vibration target detection and vibration parameters estimation based on the DPCA technique in dual-channel SAR

This paper proposes a new method based on the displaced phase center antenna(DPCA) technique for the detection and parameters estimation of vibration target in dual-channel synthetic aperture radar(SAR).The echo model of vibration target is established in dual-channel SAR according to the equivalent phase center principle.By accumulating the DPCA signal amplitude in the azimuth direction,we realize the vibration target detection in clutter and noise background.Through the analysis of DPCA signal amplitude and phase characteristics of vibration target,we then convert the vibration parameters estimation to estimation of a signal with the form of absolute value of a sine function,and the converting conditions is also given.Accordingly,an algorithm combining the Fourier transform with least squares is proposed for estimation.The simulation results show that the algorithm can estimate each vibration parameter precisely at a low signal-to-noise ratio.     

基于GPU的星载SAR多普勒中心频率估计处理技术

针对星载SAR多普勒中心频率估计算法复杂及运算量大的特点,基于GPU技术手段开展实时数据处理技术研究。选用Tesla C1060构建GPU专用科学计算平台,针对雷达卫星数据进行了数据处理实验,完成了系统结构设计。完成了多普勒中心频率估计算法分析\,基于CUDA编程模型构建以及MLCC算法优化设计等关键技术。结果表明:在不考虑全局拟合数据处理的情况下,实现了多普勒中心频率估计的处理速度达到Radarsat\|1卫星下行速率的12倍以上。为进一步进行精确的多普勒中心估计及实时SAR成像处理系统的研制提供了依据。