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基于高阶累积量的最大似然估计方法及其应用 总被引:1,自引:0,他引:1
讨论了高距离分辨率制导雷达的近距角闪烁抑制问题,提出了利用超分辨谱估计算法对混叠在同一距离分辨单元内的两个或多个散射中心进行离析,然后采用最大似然估计方法分别估计各个散射中心谐波分量幅度与相位信息的新方法.实验结果表明,该方法能够有效克服目标多散射中心之间的干涉现象,为解决末制导过程中目标的稳定跟踪问题提供了一种有效途径. 相似文献
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目前将酉变换算法用于奇数阵元均匀圆阵时需要利用模式空间算法进行预处理,而模式空间算法需要阵元数过多,且与酉变换算法结合后只能针对特定俯仰角在方位向上进行一维搜索.针对问题提出利用高阶累积量算法对阵列接收数据进行预处理,为提高测向精度和估角性能,利用酉变换算法将预处理得到的高阶累积量矩阵实数化.与模式空间算法相比上述方法降低了对阵元个数的需要,并且能够直接进行二维谱峰搜索.与经典多重信号分类算法(MUSIC)相比,在不增加特征值分解及谱峰搜索计算量的情况下,提高了算法的分辨力.按照给出的算法原理,通过仿真试验验证了所得的结论的正确性. 相似文献
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为了高效估计出K分布的参数,提出了对数累积量参数估计方法。基于第二类统计量,先对K分布的概率密度函数进行Mellin变换,从而获得K分布的第二类第一特征函数;然后对第二类第一特征函数进行对数变换,由此获得K分布的第二类第二特征函数;最后对第二类第二特征函数求导数,进而获得K分布的前两阶对数累积量,由此可以估计K分布的参数。与传统的最大似然估计方法相比,K分布的对数累积量估计具有解析的表达式,易于计算。Monte Carlo仿真表明,基于第二类统计量的K分布对数累积量估计可获得较高的估计精度。 相似文献
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基于深度变化成像模型的图像估计 总被引:3,自引:1,他引:3
该文提出了一种基于EM算法的最大似然图像复原算法,此算法是基于三维显微光学切片中成像随深度变化的模型实现的。实际成像中,由于样本中物质是变化的,故样本不同位置的折射率不一样,并且会导致其点扩展函数也不同。虽然大多数显微镜具有像差补偿功能,但由于样本的折射率和物镜的折射率不匹配,导致不同深度其点扩展函数也不一样。该文对二维图像和三维图像序列进行实验,结果表明通过此算法能够补偿由于深度变化所带来的模糊,从而将模糊图像复原。 相似文献
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针对利用灰度共生矩阵作为纹理特征的传统方法不能够有效表征图像的边缘高频信息的问题,结合小波的多分辨率分析,提出了一种基于小波变换域统计特性的合成孔径雷达(SAR)图像分割算法。图像经过小波变换后,其统计特性服从广义高斯分布(GGD),利用最大似然(ML)估计,推导出GGD的两个参数[α]、[β],提出了利用Newton-Raphson法对[β]进行快速迭代求解。并将[α]、[β]作为SAR图像的纹理特征,利用K-Means对其进行分割。通过对典型的SAR图像结果分析,表明了该算法的有效性。 相似文献
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为了解决正交频分复用(OFDM)宽带信号处理的问题,研究了基于宽带聚焦矩阵和高阶累积量的波达方向(DOA)估计方法。前者是通过傅里叶变换将宽带阵列数据分解为若干窄带信号,再利用一种聚焦矩阵将不同频带下的方向矩阵变换到同一参考频率下,然后用多重信号分类(MUSIC)算法来估计DOA;高阶累积量算法是通过聚焦操作,把各个窄带频率处的阵列输出矢量变换到聚焦频率处,然后求其累积量矩阵。对各个累积量矩阵进行加权平均并特征值分解,再应用MUSIC算法估计DOA。理论分析和仿真结果表明,两种方法都能够精确地估计OFDM信号的DOA,四阶累积量方法的空间分辨率比聚焦矩阵方法有所提高。四阶累积量算法扩展了阵列孔径,信噪比(SNR)较低的时候也有很好的适应性。 相似文献
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With the improvements in modern radar resolution,the Gaussian-fluctuation model based on the central limit theorem does not accurately describe the scattering echo from targets.In contrast,the heavytailed Rayleigh distribution,based on the generalized central limit theorem,performs well in modeling the synthetic aperture radar(SAR) images,whereas its application to multi-look image processing is difficult.We describe successful modeling of multilook polarimetric SAR images with the heavy-tailed Rayleigh distribution and present novel parameter estimators based on matrix log-cumulants for the heavy-tailed Rayleigh distribution including the equivalent number of looks(ENL).First,a compound variable of heavy-tailed Rayleigh distribution is divided into a product of a positive alpha-stable variable and a complex Gaussian variable.The parameter estimations of the characteristic exponent and scale parameter based on log-cumulants in a single polarization channel are then derived.Second,the matrix log-cumulants(MLCs) for full polarization in multilook images are obtained,which can be applied to estimate model parameters.Therefore,a novel ENL estimator based on MLC is presented that describes the model more precisely.Extended to all other multivariable product models,this estimator performs better than existing methods.Finally,calculations on both simulated and real data are performed that give good fits with theoretical results.Multilook processing in one image with a fixed pixel number can improve parameter estimations over single-look processing.Our heavy-tailed Rayleigh model with its parameter estimation provides a new method to analyze the multilook polarimetric SAR images for target detection and classification. 相似文献
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Multi-look polarimetric SAR (synthetic aperture radar) data can be represented either in Mueller matrix form or in complex covariance matrix form. The latter has a complex Wishart distribution. A maximum likelihood classifier to segment polarimetric SAR data according to terrain types has been developed based on the Wishart distribution. This algorithm can also be applied to multifrequency multi-look polarimetric SAR data, as well as 10 SAR data containing only intensity information. A procedure is then developed for unsupervised classification. The classification error is assessed by using Monte Carlo simulation of multilook polarimetric SAR data, owing to the lack of ground truth for each pixel. Comparisons of classification errors using the training sets and single-look data are also made. Applications of this algorithm are demonstrated with NASA/JPL P-, L- and C-band polarimetric SAR data. 相似文献
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Y. Yu S. T. Acton Corresponding author 《International journal of remote sensing》2013,34(17):3423-3438
In this paper we present a new diffusion-based method for the delineation of coastlines from space-borne polarimetric SAR imagery of coastal urban areas. Both polarimetric filtering and speckle reducing anisotropic diffusion (SRAD) are exploited to generate a base image where speckle is reduced and edges are enhanced. The primary edge information is then derived from the base image using the instantaneous coefficient of variation edge detector. Next, the resulting edge image is parsed by a watershed transform, which partitions the image into disjoint segments where the division lines between segments are collocated with detected edges. The over-segmentation problem associated with the watershed transform is solved by a region merging technique that combines neighbouring segments with similar radar brightness. As a result, undesired boundary segments are eliminated and true coastlines are correctly delineated. The proposed algorithm has been applied to a space-borne polarimetric SAR dataset, demonstrating a good visual match between the detected coastline and the manually contoured coastline. The performance of the proposed algorithm is compared with those of two polarimetric SAR classification algorithms and two edge-based shoreline detection methods that are tailored to single polarization SAR images. Experimental results are shown using polarimetric SAR data from Hong Kong. 相似文献
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极化合成孔径雷达(SAR)图像包含目标丰富的散射信息,在边缘检测中具有重大的潜力。对极化SAR影像边缘检测问题进行了系统的研究,从单极化SAR出发,分析了极化SAR边缘检测问题,对已有的方法进行了分类总结,重点介绍了极化SAR边缘检测的最新进展,指出了当前存在的问题,对极化SAR边缘检测的发展趋势进行了展望。 相似文献
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In the presented paper a new method of identification of canonical coherent scatterers in the quad-polarimetric SAR data are presented. The proposed method is based on the analysis of polarimetric signatures. The observed signatures are compared with the polarimetric signatures of four canonical objects: trihedral, dihedral and helix – right and left which represent basic scattering mechanisms: single bounce, double bounce and helix scattering. The polarimetric matrices are treated as vectors in a unitary space with a scalar product that generates the norm. A recognized object is classified to one of the four coherent classes by a Kohonen network. It is not trained in an iteration process but its weights are adjusted according to the given patterns. The network classification is supported by rules. The obtained maps of pixels that represent canonical objects are compared with a map of coherent scatterers which was obtained by using the polarimetric entropy approach. The developed method of canonical coherent scatterers identification based on the polarimetric signatures analysis allows us not only to identify precisely the canonical coherent scatterers but also to determine the type of scattering mechanism characteristic for each of them. Since the proposed method works on a single-look (non-averaged) SAR data, it does not cause any spatial nor spectral decrease of amount of information because averaging is not conducted. Moreover, the proposed method will enable us the identification of a type of scattering mechanism in the canonical coherent pixels. This is an improvement in comparison to the existing methods. The obtained results should be more precise because the full polarimetric information about the scatterers is used in the identification procedure. 相似文献
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针对SAR图像地面车辆目标方位角估计精度不高的问题,尤其是0度和180度估计误差大的问题,提出了一种地面SAR图像目标方位角联合估计方法。首先,分析了地面车辆目标在不同角度的成像特点和典型目标方位角估计方法的优缺点,然后,通过判断当前目标成像所具有的特点,利用目标阴影特征与目标轮廓特征,并结合目标主轴提取方法和Hough变换方法对SAR图像目标方位角进行联合估计,最后利用MSTAR目标切片数据对该方法进行了验证实验,绝对误差在5º范围内的准确估计率都在89%以上,目标误差均值都在4º以内。实验结果表明该算法的方位角估计精度比较高,算法是有效性的和可行的。 相似文献
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Leonardo Torres Sidnei J.S. Sant'Anna Corina da Costa Freitas Alejandro C. Frery 《Pattern recognition》2014
This paper presents a technique for reducing speckle in Polarimetric Synthetic Aperture Radar (PolSAR) imagery using nonlocal means and a statistical test based on stochastic divergences. The main objective is to select homogeneous pixels in the filtering area through statistical tests between distributions. This proposal uses the complex Wishart model to describe PolSAR data, but the technique can be extended to other models. The weights of the location-variant linear filter are function of the p-values of tests which verify the hypothesis that two samples come from the same distribution and, therefore, can be used to compute a local mean. The test stems from the family of (h –?) divergences which originated in Information Theory. This novel technique was compared with the Boxcar, Refined Lee and IDAN filters. Image quality assessment methods on simulated and real data are employed to validate the performance of this approach. We show that the proposed filter also enhances the polarimetric entropy and preserves the scattering information of the targets. 相似文献
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针对利用Yamaguchi分解模型的四个散射分量直接进行类别归属判断精度不高并且所分类别有限的问题,结合模糊C均值的理论,提出了一种基于Yamaguchi分解模型的全极化SAR分类算法,把四个散射分量组成一组归一化的特征矢量,进行FCM聚类分析。并且用日本机载L波段PiSAR数据验证了该算法具有较高的分类精度和较好的视觉效果。 相似文献
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贝叶斯形式的非局部均值模型在极化SAR图像相干斑抑制中有良好的应用,在实现抑制相干斑的同时较好地保持了边缘细节和点目标.通过分析合成孔径雷达(SAR)图像多视数据的空间统计分布,结合贝叶斯形式的非局部均值模型,得出在该模型下多视与单视SAR图像中像素间相似性度量函数一致性的结论,并对该相似性度量函数进行了修正,使之满足对称性;最后针对算法全局使用一个固定滤波参数影响滤波效果的问题,提出一种根据像素间相似程度自适应选取滤波参数的方法.实验结果验证了本文算法的有效性. 相似文献