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1.
提出了一种抑制InSAR干涉图噪声并保持干涉图条纹细节的算法,该算法改进了Goldstein滤波的参数α,将干涉图的相位标准偏差函数模型作为参数。相位标准偏差是相位噪声的体现,以干涉图的相位噪声强弱来决定滤波的强弱,噪声强的局部区域强滤波,噪声弱的局部区域弱滤波。实验结果表明,此方法改善了滤波效果,增强了滤波的局部自适应性和条纹细节的保真性。  相似文献   

2.
针对自适应卡尔曼滤波只适用于滤除高斯分布的白噪声,本文提出了融合小波变换和自适应卡尔曼滤波的算法。该算法利用小波变换的多尺度分解,将GPS高频的监测时间序列进行多层分解,重构出新的GPS监测时间序列,将其作为新的自适应卡尔曼滤波初始值,进行滤波处理。将融合算法的滤波结果与单一的自适应卡尔曼滤波结果进行对比分析,结果表明融合算法的滤波效果较为显著。同时,对融合算法滤除的噪声信息进行统计分析,结果表明融合算法滤除的噪声符合正态分布,进一步说明了该融合算法的有效性,为GPS的高频率、高精度的监测提供了技术支持。  相似文献   

3.
InSAR干涉图最优化方向融合滤波   总被引:1,自引:0,他引:1       下载免费PDF全文
尹宏杰  李志伟  丁晓利  蒋弥  孙倩  王平 《遥感学报》2009,13(6):1099-1113
在分析干涉条纹图噪声特征的基础上, 提出了一种能有效保持干涉图条纹的边缘和细节信息的InSAR干涉图滤波算法——基于最优化融合的自适应方向平滑算法。该算法首先对8个线性方向窗口进行统计分析, 然后根据干涉图的相干性选择合适的线性方向窗口, 按照最优化融合的方法, 以方差倒数为权重对各个方向窗口的均值进行加权平均。模拟和真实干涉图数据的实验结果表明新方法不仅能有效的抑制干涉图噪声, 而且能较好的保持干涉图的细节和边缘信息, 具有很好的信息保持能力。  相似文献   

4.
Speckle degrades the radiometric quality of a Synthetic Aperture Radar (SAR) image. Previous methods for speckle reduction have used a fixed-size window for filtering the entire image. This, however, may not be effective for the entire image, as land covers of different sizes require different filtering windows. In this paper, a novel method is proposed by which each pixel in the image is filtered with a window appropriate for the size of object within it. The real in-phase and the imaginary quadrature components of the SAR images determine the best window size and the pixels in the intensity image are filtered using their own optimal windows. The proposed method is presented for both single- and multi-polarized SAR images, and the results of several common filters that were modified are presented. This approach is applied to two RADARSAT-2 images: one over San Francisco, California, USA and the other over St. John’s, Newfoundland and Labrador, Canada, producing results that were similar to, or outperformed, comparable filters while retaining details and suppressing speckle effectively. While the method was successful for single-look intensity data, it offers great potential for multi-look and amplitude data as well.  相似文献   

5.
Kalman filter is the most frequently used algorithm in navigation applications. A conventional Kalman filter (CKF) assumes that the statistics of the system noise are given. As long as the noise characteristics are correctly known, the filter will produce optimal estimates for system states. However, the system noise characteristics are not always exactly known, leading to degradation in filter performance. Under some extreme conditions, incorrectly specified system noise characteristics may even cause instability and divergence. Many researchers have proposed to introduce a fading factor into the Kalman filtering to keep the filter stable. Accordingly various adaptive Kalman filters are developed to estimate the fading factor. However, the estimation of multiple fading factors is a very complicated, and yet still open problem. A new approach to adaptive estimation of multiple fading factors in the Kalman filter for navigation applications is presented in this paper. The proposed approach is based on the assumption that, under optimal estimation conditions, the residuals of the Kalman filter are Gaussian white noises with a zero mean. The fading factors are computed and then applied to the predicted covariance matrix, along with the statistical evaluation of the filter residuals using a Chi-square test. The approach is tested using both GPS standalone and integrated GPS/INS navigation systems. The results show that the proposed approach can significantly improve the filter performance and has the ability to restrain the filtering divergence even when system noise attributes are inaccurate.  相似文献   

6.
根据干涉图信号和噪声时频分布差异的特点,提出一种改进的基于经验模态分解EEMD的InSAR干涉相位滤波方法。该方法首先利用可有效降低模态混叠的EEMD算法,对干涉图的实部及虚部分别进行2维经验模态分解,获得具有不同时间尺度的模态分量;然后根据信号和噪声分量的时间尺度分布特性的差异,采用适用于非线性信号分析的KECA算法对噪声识别、分离;最后利用去除噪声后的模态分量重构干涉图。为了证明本文方法的有效性,分别利用模拟数据及真实InSAR差分干涉相位进行滤波试验。对比本文EEMD-KECA滤波方法、Goldstein滤波、圆周期—中值滤波、EMD分解、EMD-PCA方法的滤波效果,采用相干斑指数、均方差指数、边缘保持指数进行定量评价。结果表明,与经典InSAR干涉图滤波方法相比,本文联合EEMD-KECA算法的滤波方法能有效滤除干涉图噪声,且在条纹边缘等细节信息的保持上也具有较大优势。  相似文献   

7.
对GPS载波相位测量误差进行了理论分析和试验研究。根据噪声特征以及它们对载波相位测量结果的影响,提出了基于自适应噪声抵消与小波滤波相结合的GPS噪声抑止方法。对具有强相关特性的多路径误差采用自适应噪声抵消方法,而对于不相关的高频噪声则通过合理选择小波分解层数对信号进行分解,对作用闽值后的小波系数进行重构,得到最后的变形信号。实测数据分析表明,该方法能有效地削弱多路径效应及测量随机噪声,较用单一方法对GPS数据进行消噪处理有较大的优越性。  相似文献   

8.
Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63–84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10–30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.  相似文献   

9.
GRACE时变重力场滤波方法   总被引:1,自引:1,他引:0  
针对GRACE时变重力场模型高阶项误差较大导致的"南-北"条带噪声,该文利用模拟的GRACE数据分析了去相关滤波、Gaussian滤波、组合滤波和平滑先验信息滤波方法对噪声的滤除效果和对真实信号的衰减程度。实验表明:4种滤波算法均能有效降低条带噪声,但单独使用去相关滤波时效果较差,需与其他算法结合使用;Guass滤波和组合滤波在减小噪声条带的同时,也在一定程度上牺牲了空间分辨率;平滑先验信息滤波在移除噪声、保留有效信号方面比其他3种算法有较为明显的优势。  相似文献   

10.
GPS/INS组合导航系统抗差滤波器设计   总被引:5,自引:0,他引:5  
何秀凤  陈永奇 《测绘学报》1998,27(2):177-184
常规Kalman滤波器已经广泛用于GPS/INS组合导航系统,其中假设系统动态模型和噪声统计特性是精确已知的。事实上,这种假设是不符合实际情况的。在组合导航系统中,惯性测量器件的质量不稳定,GPS测量误差受外界环境的影响,因而对组合导航系统进行抗差设计是十分必要的。本文利用对策论设计了能使不确定噪声下性能最好的极小极大抗差滤波器,并将其应用到GPS/INS组合导航系统中。考虑一个IO状态的GPS/  相似文献   

11.
针对复小波双变量滤波模型仅考虑小波复系数实部,忽略了系数的虚部,导致信号相位噪声的增加而影响滤波效果的问题,提出基于复小波变换的复数域双变量模型干涉图滤波算法。该算法将双变量贝叶斯估计算法从实数域推广到了复数域,用噪声复系数概率密度函数刻画了小波复系数实部与虚部的相关性,根据小波分解复系数来估计噪声方差和信号方差,建立了复小波复数域双变量滤波模型,求得了干涉图复系数的贝叶斯估计。试验结果表明,本算法对干涉图噪声有较强的抑制能力,保留了干涉图的边缘及细节信息,滤波性能优于传统的实数域复小波双变量滤波、Goldstein滤波、单小波滤波和最优化融合滤波方法。  相似文献   

12.
多波束异常测深数据检测方法实践   总被引:4,自引:0,他引:4  
由于现有的交互式滤波和自动滤波不能满足大区域、高密度多波束测深数据滤波的需要,为此,本文给出了易于改善自动化滤波的趋势面法和基于抗差M估计的选权迭代加权平均法。前者适合于显著粗差的探测,对小粗差不敏感;后者由于对被检测点邻域内的观测点具有选择性,加之采用迭代实现推值,因而对于粗差具有较强的探测能力,检测和滤波结果较趋势面法更为合理。  相似文献   

13.
利用精密单点定位(Precise Point Positioning,PPP)获得的时间传递结果受到非模型化误差和观测噪声的影响,这些误差和噪声表现出随机噪声特性,因此,对时间传递数据进行平滑是一项非常重要的任务.将天文数据处理中广泛应用的Vondrak平滑方法应用于PPP时间传递的消噪中,采用观测误差法选取较为合理的平滑因子,并对实测数据进行平滑处理,结果表明:Vondrak平滑法可有效地滤除PPP数据的随机噪声,不仅可以提高时间传递的精确度,也能明显改善PPP时间传递所体现的频率稳定度.  相似文献   

14.
干涉图滤波是合成孔径雷达数据处理的关键,引入卷积神经网络(convolutional neural networks,CNN)进行干涉图去噪。首先,采用自编码器结构进行非监督学习,将干涉图去除局部地形坡度相位,所得残余噪声作为模型输入;然后将模型输出结果与去除的局部地形坡度相位相加,生成滤波结果。利用航天飞机成像雷达数据和哨兵一号A(Sentinel-1A)卫星数据,通过与Goldstein滤波器、均值滤波器、Lee滤波、Frost滤波、改进的去噪卷积神经网络(denoising convolutional neural network,DnCNN)进行对比实验,结果表明,该方法对干涉图相位质量有很大的改善,不仅能够较大程度地抑制噪声,而且能够更多地恢复出图像细节,保持干涉条纹边缘连续性。  相似文献   

15.
A Novel Technique for Noise Reduction in InSAR Images   总被引:3,自引:0,他引:3  
This letter proposes a new technique for noise reduction applied to synthetic aperture radar interferometry. This technique involves a nonlinear filter that separates the interferogram into two components: one containing the smooth (low frequency) part and the other containing the detail (high frequency) part. The smooth part is obtained using a combination of a median filter and a smoothing filter. The detail component is obtained by subtracting the smooth component from the original signal. This detail component is filtered to remove noise and then added to the smooth component to generate the final output. Both simulated and real data are used to evaluate the performance of the proposed technique under different conditions. The experimental results show that the proposed technique outperforms most commonly used interferometric phase filters  相似文献   

16.
InSAR干涉图的零中频矢量滤波算法   总被引:3,自引:2,他引:3  
提出一合成孔径雷达干涉测量干涉图的滤波方法。该方法引入无线电技术中的零中频技术,将干涉图由高的中心频率变为零中频信号,再将信号分解至矢量空间中的两路正交信号,得到正弦支路信号和余弦支路信号,并分别进行低通滤波处理,最后根据滤波后的两路正交信号计算出滤波后的零中频干涉图,并恢复干涉图的原始频率,得到原始干涉图的滤波结果。实验结果表明:该方法滤波效果较好,能够解决干涉图条纹密集时滤波处理困难、效果较差的问题。  相似文献   

17.
In this paper, we propose an adaptive filtering technique for Synthetic Aperture Radar (SAR) images. A new windowing technique is introduced where the total window is divided into five equal sized overlapping sub-windows. The pixel to be filtered is a part of each of these sub-windows. A weighted mean of all sub-windows is computed for the pixel under consideration. The weights are accounted from a measure of heterogeneity calculated for each sub-windows. The filter is able to adapt automatically and adjust the speckle suppression strength based on local statistics. This allows the filter to preserve edges while strongly suppressing speckle over homogeneous areas. The proposed filter was compared with some well known SAR filtering techniques in terms of speckle suppression and edge preservation ability. Several experiments were performed on datasets acquired from both air-borne and space-borne SAR platforms. Some well known indices were used for quantitative comparison with other filters. Among the filters compared, the proposed filter shows good speckle suppression ability while still exhibiting reasonable edge preservation ability.  相似文献   

18.
A novel noise reduction scheme for synthetic aperture radar (SAR) interferograms based on the wavelet packet transform (WPT) and the Wiener filter is introduced in this letter. First, by employing the WPT in the spatial frequency domain, the real and imaginary parts of the complex noisy interferogram are decomposed, respectively, and the wavelet coefficients are obtained. Then, for these coefficients, Wiener filtering is adopted to remove noise. This scheme can filter noise adaptively according to the local noise level, without requiring any a priori information. By using a simulated noisy interferogram and two ENVISAT Advanced Synthetic Aperture Radar C-band interferograms, the performance of this scheme, in terms of noise reduction and fringes preservation, is reported and compared with other filter algorithms. The experimental results demonstrate the effectiveness of the proposed scheme.   相似文献   

19.
基于可分解马尔科夫网的极端椒盐噪声图像滤波   总被引:4,自引:0,他引:4  
提出了一种基于可分解马尔科夫网(decomposableMarkovnetworks,DMN)的极端椒盐噪声的均值滤波方法,指出其网络节点的阈值衰减特性和网络节点的连接特性具有很好的对椒盐噪声污染图像的噪声定位的作用,并提出一种在该网络控制下,只对与噪声相关的像素进行均值计算以替代噪声像素的亚均值滤波算法,实现了图像的较强自适应滤波。实验表明,本文方法具有良好的滤波性能。  相似文献   

20.
For areas of the world that do not have access to lidar, fine-scale digital elevation models (DEMs) can be photogrammetrically created using globally available high-spatial resolution stereo satellite imagery. The resultant DEM is best termed a digital surface model (DSM) because it includes heights of surface features. In densely vegetated conditions, this inclusion can limit its usefulness in applications requiring a bare-earth DEM. This study explores the use of techniques designed for filtering lidar point clouds to mitigate the elevation artifacts caused by above ground features, within the context of a case study of Prince William Forest Park, Virginia, USA. The influences of land cover and leaf-on vs. leaf-off conditions are investigated, and the accuracy of the raw photogrammetric DSM extracted from leaf-on imagery was between that of a lidar bare-earth DEM and the Shuttle Radar Topography Mission DEM. Although the filtered leaf-on photogrammetric DEM retains some artifacts of the vegetation canopy and may not be useful for some applications, filtering procedures significantly improved the accuracy of the modeled terrain. The accuracy of the DSM extracted in leaf-off conditions was comparable in most areas to the lidar bare-earth DEM and filtering procedures resulted in accuracy comparable of that to the lidar DEM.  相似文献   

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