共查询到20条相似文献，搜索用时 718 毫秒
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为了有效提升干涉图相位解缠精度,提出粒子-平滑变结构滤波相位解缠算法：(1)把融入残差因子的平滑变结构滤波算法应用于干涉图相位解缠,结合局部相位梯度估计技术,构建粒子-平滑变结构滤波相位解缠程序;(2)把干涉图相位微分偏差图作为质量图,嵌入堆排序路径跟踪策略指导相位解缠路径;(3)利用归一化的干涉图相位微分偏差图把干涉图划分为3个不同质量层级的缠绕像元集,粒子-平滑变结构滤波相位解缠程序沿第1质量层级→第2质量层级→第3质量层级的顺序依次解缠干涉图缠绕像元,获得干涉图所有缠绕像元的解缠相位值。模拟和实测数据实验结果表明与一些代表性算法相比,上述方法能较好地执行干涉图相位解缠任务,显现了较好的鲁棒性,有效提升了干涉图相位解缠精度。 相似文献
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结合滤波算法的不敏卡尔曼滤波器相位解缠方法 总被引：2，自引：1，他引：1
提出结合预滤波算法的不敏卡尔曼滤波（UKF）相位解缠方法。该方法把UKF、传统路径跟踪策略、全方位的局部相位梯度估计技术以及小窗口干涉图预滤波算法有效结合起来,能在相位解缠的同时进行干涉相位噪声抑制,既不受相位残差点影响,又避免了传统方法在相位解缠之前须尽可能滤除干涉图中相位噪声的不足。模拟和实测数据实验结果验证了本文方法的有效性,且与扩展卡尔曼滤波相位解缠算法（EKFPU）以及传统方法相比具有较高的精度。 相似文献
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基于修正嵌入式容积卡尔曼滤波的相位展开算法 总被引：1，自引：1，他引：0
针对干涉图展开问题,将Levenberg-Marquardt方法修正后的嵌入式容积卡尔曼滤波器应用于缠绕相位图像的展开中,结合基于修正矩阵束模型的局部相位梯度估计算法以及量化跟踪策略,提出一种基于修正嵌入式容积卡尔曼滤波的相位展开算法。该算法不仅可以精确和快速地展开缠绕像元,还可以在展开缠绕像元的同时抑制相位噪声,降低前置预滤波器的难度与复杂度,甚至可以在处理受噪声污染不严重的干涉图时免去前置预滤波处理步骤。试验结果表明本文算法具有较高的效率和良好的稳键性。 相似文献
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为从含噪干涉相位数据中估计出解缠相位,本文提出相位解缠的CKF局部多项式系数递推估计法。利用基于修正矩阵束模型的局部相位梯度估计算法(AMPM)来获取多项式系数中的梯度信息,在此基础上获得局部多项式系数初始值(即状态变量初值),最后利用容积卡尔曼滤波(CKF)算法递推估计多项式系数状态估计值,从而获得解缠相位。可根据干涉图条纹密度以及相位噪声情况,分别采用逐行(或逐列)扫描方式或质量图引导策略引导容积卡尔曼滤波器解缠干涉图缠绕像元。模拟样例与实测数据试验结果表明,与其他同类方法相比,本文算法能从噪声干涉图中获得更高的解缠精度。 相似文献
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基于不规则网络下网络流算法的相位解缠方法 总被引：9，自引：0，他引：9
相位解缠作为SAR干涉测量数据处理中的一个关键步骤,受到越来越广泛的关注,出现了各种各样的算法。但现有的相位解缠算法仍无法解决高噪声问题,由此导致噪声区域的误差传递到其它区域,产生全程误差,从而影响相位解缠精度。针对这种情况,我们根据网络优化原理,提出了一种基于不规则网络下网络流算法的解缠方法,以干涉相干作为评价相位质量的标准,从含有大量噪声的干涉纹图中剔除低质量的相位,只对高质量相位进行处理,最终获取有用信息。该方法可以避免低质量区域的误差对高质量区域解缠的影响,保证高质量区域的相位解缠,从而获得较理想的解缠结果。 相似文献
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针对大块干涉相位图解缠效率低的问题,提出了一种共享内存环境下的大块干涉相位图解缠方法。利用质量引导和最小不连续优化策略设计了复合相位解缠算法,并在共享内存环境下对算法中的质量图计算、高低质量区域分割和低质量区域优化3个步骤进行了并行化。为充分利用多核计算资源,针对低质量区域的并行优化,设计了动态计算任务分配方法。对仿真和干涉合成孔径雷达相位图的解缠试验结果表明,所提算法在提高相位解缠精度的同时,也极大地优化了相位解缠效率。 相似文献
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针对多基线SAR干涉相位展开方法精度与效率之间难以兼顾的问题,文章提出一种高效稳健的相位展开方法:利用基于修正矩阵束模型的联合相位梯度估计技术快速和精确地从较短基线干涉图获取长基线干涉相位梯度,以增加算法的精度和效率;建立基于干涉图相干系数(或伪相干系数)以及相位微分偏差的相位质量图指导展开路径,以保证沿最优路径展开长基线干涉像元,有利于降低误差传递效应,提高相位展开精度;引入量化跟踪策略,减s少搜索最佳展开路径所消耗的时间,提高方法效率。仿真数据处理结果表明此方法具有精度及效率较高、稳健性较强的特点。 相似文献
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GPS Solutions - Autonomous Navigation (AutoNav) based on inter-satellite cross-link can substantially maintain BDS survivability in war and alleviate the need of the Operational Control Segment. It... 相似文献
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Real-time seismic signal enhancement utilizing a hybrid Rao-Blackwellized particle filter and hidden Markov model filter 总被引：3，自引：0，他引：3
This letter outlines a novel and robust algorithm for identifying seismic events within low signal-to-noise ratio (SNR) passive seismic data in real time. Since the event detection problem is a continuous, real-time process which has nonlinear mathematical representations, a Rao-Blackwellized particle filter (RBPF) is utilized. In this algorithm, a jump Markov linear Gaussian system (JMLGS) is defined where changes (i.e., jumps) in the state-space system and measurement equations are due to the occurrences and losses of events within the measurement noise. The RBPF obtains optimal estimates of the possible seismic events by individually weighting and subsequently summing a bank of Kalman filters (KFs). These KFs are specified and updated by samples drawn from a Markov chain distribution which defines the probability of the individual dynamical systems which compose the JMLGS. In addition, a hidden Markov model filter is utilized within the RBPF filter formulation so that real-time estimates of the phase of the seismic event can be obtained. The filter is demonstrated to provide up to an 80-fold improvement in the SNR when processing simulated seismic data with Gauss-Markov measurement noise. 相似文献
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The extraction of points on the bare earth from point clouds acquired by airborne laser scanning is one of the most important steps for the generation of digital terrain models (DTM). This process is called “filtering”. However, most of the current filters erode the bare earth in steep sloped landscapes and at discontinuities, and they retain low vegetation. Therefore, a new filtering method for extracting ground points based on a distance limit is proposed in this paper. The angle criterion is used to assure the robustness of the algorithm. The experimental results show that the proposed filtering method can effectively derive the ground points from point clouds in complex urban areas. 相似文献
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The extraction of points on the bare earth from point clouds acquired by airborne laser scanning is one of the most important
steps for the generation of digital terrain models (DTM). This process is called “filtering”. However, most of the current
filters erode the bare earth in steep sloped landscapes and at discontinuities, and they retain low vegetation. Therefore,
a new filtering method for extracting ground points based on a distance limit is proposed in this paper. The angle criterion
is used to assure the robustness of the algorithm. The experimental results show that the proposed filtering method can effectively
derive the ground points from point clouds in complex urban areas.
Supported by the Program for Changjiang Scholars and Innovative Research Team in University (No.0438), the National 863 Program
of China (No. 2006AA12Z151). 相似文献
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A separable filter for directional smoothing 总被引：1，自引：0，他引：1
Anisotropic and directional filters can smooth noisy images while preserving object boundaries. Data from remote sensing instruments often have missing pixels due to geometric or power limitations. In such cases, these nonisotropic filters are very inefficient, because transform methods cannot be used when there is missing data or when logical operations need to be performed. A directional filter is introduced in this letter that retains the ability to handle missing data and is separable, making it computationally efficient. We demonstrate the directional filter on weather radar data where it can be used to smooth along fronts. Since the filter introduced here can be parameterized for scale, orientation, and aspect ratio, this filter can be used in any directional filtering application where transform methods cannot be used, but computational efficiency is desired. 相似文献
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O. Remmer 《Journal of Geodesy》1969,43(2):99-122
A method for filtering of geodetic observationwhich leaves the final result normally distributed, is presented. Furthermore, it is shown that if you sacrifice100.a% of all the observations you may be (1−β).100% sure that a gross error of the size Δ is rejected.
Another and, may be intuitively, more appealing method is presented; the two methods are compared and it is shown why Method
1 should be preferred to Method 2 for geodetic purposes.
Finally the two methods are demonstrated in some numerical examples. 相似文献
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Reliability of the scattering model based polarimetric SAR (PolSAR) speckle filter depends upon the accurate decomposition and classification of the scattering mechanisms. This paper presents an improved scattering property based contextual speckle filter based upon an iterative classification of the scattering mechanisms. It applies a Cloude-Pottier eigenvalue-eigenvector decomposition and a fuzzy H/α classification to determine the scattering mechanisms on a pre-estimate of the coherency matrix. The H/α classification identifies pixels with homogeneous scattering properties. A coarse pixel selection rule groups pixels that are either single bounce, double bounce or volume scatterers. A fine pixel selection rule is applied to pixels within each canonical scattering mechanism. We filter the PolSAR data and depending on the type of image scene (urban or rural) use either the coarse or fine pixel selection rule. Iterative refinement of the Wishart H/α classification reduces the speckle in the PolSAR data. Effectiveness of this new filter is demonstrated by using both simulated and real PolSAR data. It is compared with the refined Lee filter, the scattering model based filter and the non-local means filter. The study concludes that the proposed filter compares favorably with other polarimetric speckle filters in preserving polarimetric information, point scatterers and subtle features in PolSAR data. 相似文献
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