InSAR技术获取高山峡谷区DEM精度研究

通过对金沙江河段高山峡谷区L波段的Alos-Palasar和C波段的Radarsat-2雷达单视复数数据的干涉处理,获取此区域的数字高程模型(DEM)。利用SRTM 90m分辨率的DEM为参考数据,通过对比分析发现InSAR技术生成的DEM精度与相干系数、地形和波长有密切的关系。同时也验证了在相干性好,地形起伏不太剧烈的地区,用InSAR技术生成DEM是可行的。     

一种星载InSAR高精度快速DEM重建方法

面对全球干涉测量的海量实测数据,在保持精度的情况下,如何提高处理速度是星载干涉合成孔径雷达(interferometric synthetic aperture radar,InSAR)数据处理必须考虑的重要问题.数字高程模型(digital elevation model,DEM)重建是InSAR数据处理中较为耗时的一个关键环节.针对星载InSAR处理中DEM快速重建的难题,从DEM重建原理出发,分析揭示了干涉相位与目标点三维坐标映射关系的两个基本特性,一是目标点的三维坐标与干涉相位的关系可以分别用多项式来进行拟合,二是SAR图像上相近像素各自对应的多项式变化不大,并从理论上对特性的成立进行了论证.基于此,提出了一种快速DEM重建方法,给出了快速算法的详细步骤及关键参数的取值方法.最后,利用德国最先进的在轨雷达卫星TerraSAR-X获取的重复轨道干涉数据进行快速DEM重建,处理结果表明在重建精度损失较小的情况下,显著提高了重建速度,验证了该方法的高效性和正确性.     

基于外部DEM的InSAR图像配准方法研究

雷达图像的配准是进行雷达干涉测量(SAR Interferometry, InSAR)处理的关键,为了保证干涉相位图或形变相位图反映真实地面特性,需要雷达图像之间亚像元级精度的配准。首先综述了已有的基于外部DEM的InSAR图像配准方法的思路及其不足之处,并提出了一种全新的思路:以图像之间的相干性作为目标函数,利用搜索的方法实现了雷达成像方位向和距离向的最优时间常数的估计,从而实现雷达图像之间亚像元级配准;还进一步推导了数字高程模型(Digital Elevation Model, DEM)的误差对算法精度影响的一个更加严密的表示。结论表明,在利用精确轨道数据的情况下,美国航天飞机测地计划SRTM获得的地形数据的精度可以满足精确雷达图像配准的要求。结果表明,利用基于外部DEM算法配准雷达图像在山区和大的时间基线情况下要优于常规相干多项式配准方法,理论上可以达到百分之一个像素的配准精度。     

基于机载InSAR生成DEM技术研究试验

本文描述了机载双天线合成孔径雷达干涉测量数据生成数字高程模型(Digital Elevation Model,DEM)技术,针对机载双天线InSAR数据自动生成DEM的数据处理流程进行试验,主要包括:复图像配准、干涉条纹图滤波、相位解缠、相高转换。本文基于VC++开发了机载InSAR干涉处理原型系统,利用分辨率为2m×2m的机载双天线X波段InSAR数据进行了干涉处理实验,并将生成的DEM和实测的控制点数据进行了对比分析。试验结果证明基于机载双天线InSAR数据生成DEM技术可满足1:50000的精度要求。     

星载SAR干涉技术获取DEM及其精度分析

星载合成孔径雷达干涉(InSAR)技术是一种数据覆盖范围广、廉价、高效、方便的数字高程模型(DEM)获取方法,但在地面植被覆盖广、大气水汽含量高的地区其影像相干性随时间基线的增加迅速降低;同时,SAR卫星的轨道误差也影响DEM精度。利用ERS-1/2卫星串行模式SAR数据获取镇江地区DEM,分析了轨道误差对DEM精度的影响;根据干涉相位的统计特性,从理论上给出干涉相位噪声与相干系数和视数之间的关系。实验结果表明就干涉像对的卫星轨道误差和相位噪声而言,在小区域内DEM精度优于3.5m。     

SIR—C C波段和L波段雷达干涉数据生成DEM的比较

为了研究波长对干涉雷达生成DEM质量的影响，以黑龙江省加格达齐地区为实验区，通过对美国航天飞机SIR－C／X－SAR C波段和L波段雷达单视复型（SLC）数据的处理，分别得到了两个不同的DEM，这两个DEM存在着一定的差异，通过与干涉相关性、相位解缠等干涉处理中的关键因素相结合进行的分析，揭示了干涉SAR技术生成DEM的精度与干涉相关性、波长的关系；同时，从另一个侧面说明了用InSAR技术生成DEM的可行性和影响因素；最后，利用1：50000地形图对干涉SAR生成的DEM误差进行了分析，并分析了地形图控制点精度对干涉SAR生成DEM的影响。     

基于区域网平差的干涉合成孔径雷达数字高程模型校正

合成孔径雷达干涉测量（InSAR）是获取数字高程模型（DEM）的常规手段,而通过干涉技术获得DEM后,其精度会受到轨道定位、影像的配准、干涉图获取、相位解缠等精度的影响。已有的利用区域网平差提升DEM精度的研究忽略了DEM的初始平面定位误差的影响。引入DEM的平面高程一体化区域网平差,将区域网平差分解为平面定位六参数的优化和高程误差模型的平差求解两个独立的平差过程,同时利用激光测高数据作为高程控制。从哨兵干涉生成的20 m分辨率DEM实验结果看,平差后DEM的高程均方根误差（RMSE）从平差前的19.372 m提升到了3.459 m。DEM对应连接点的平面内符合精度RMSE从初始182.462 m提升至14.887 m。而传统的不考虑平面误差的DEM优化方法在平差后高程精度提升至7.865 m,远低于所提出的方法,验证了提出的考虑平面误差的区域网平差方法的有效性。     

利用星载InSAR技术提取镇江地区DEM及其精度分析

InSAR技术是目前获取高精度数字高程模型（DEM）的一种新方法。为了分析InSAR技术提取DEM的精度,首先介绍了美国航天飞机雷达SRTM DEM的精度和数据结构,然后以江苏镇江地区作为试验区,采用ERS1/2卫星影像来提取DEM,并对星载SAR提取的DEM与SRTM 3弧秒分辨率DEM的精度作了比较。 结果表明,利用星载SAR提取的DEM分辨率与SRTM 3弧秒分辨率的DEM相当,能很好地显示出地形起伏（如山脉、沟谷）的纹理特征。进一步的研究还表明,利用InSAR技术提取DEM的精度与SRTM 3 DEM之间存在5米左右的系统误差,并对产生这一系统误差的原因作了详细分析。     

InSAR干涉纹图噪声抑制算法的比较及改进

干涉纹图中的噪声影响着InSAR的图像质量,使得相位解缠无法进行或者使生成的DEM精度降低。为了获得高质量的InSAR纹图,必须对噪声进行有效抑制,同时保持空间分辨率。文中探讨了InSAR干涉纹图的噪声抑制方法,提出了一种新的干涉纹图的滤波方法。并采用了真实数据验证了方法的有效性。     

InSAR干涉纹图噪声抑制算法的比较及改进

干涉纹图中的噪声影响着InSAR的图像质量,使得相位解缠无法进行或者使生成的DEM精度降低.为了获得高质量的InSAR纹图,必须对噪声进行有效抑制,同时保持空间分辨率.文中探讨了InSAR干涉纹图的噪声抑制方法,提出了一种新的干涉纹图的滤波方法.并采用了真实数据验证了方法的有效性.     

NASA EOS Terra ASTER: Volcanic topographic mapping and capability

Up-to-date, accurate topographic data are a crucial resource for volcanic research and risk mitigation efforts, in particular, for modeling volcanic flow processes at a detailed spatial resolution. In this paper, we examine the utility of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument currently operating on the NASA Terra satellite, which provides near infrared (VNIR) stereo imaging from which topography can be derived. We wrote software to generate digital elevation models (DEMs) from the ASTER level 1A product, which employs an automated stereo matching technique to calculate the parallax offsets between the images acquired by the nadir- and aft-looking sensors. Comparison of ASTER DEMs with DEMs derived from other sources (digitized 1:50 K topographic maps and aerial interferometric radar) at Ruapehu volcano reveal an RMS error of about 10 m for the ASTER DEM, in the absence of significant atmospheric water vapor. A qualitative assessment of surface features showed that the ASTER DEM is superior to the interpolated 1:50 K map product but falls short of the detail provided by aerial interferometric radar, especially in terms of stream channel preservation. A second ASTER DEM was generated for Taranaki volcano, where previously only 1:50 K topographic map data were available. Although the 2000 Space Shuttle radar topography mission (SRTM) will largely remedy the previous global paucity of adequate topographic data at volcanoes, such as Taranaki, we anticipate the problem that at active volcanoes, the topography may change significantly following activity, rendering the SRTM data inaccurate. With the high temporal coverage of the dataset, ASTER not only provides a means to update significant (>10 m) topographic measurements at active volcanoes via a time-series of DEMs, but also provides a simultaneous means to map surface cover and localized land-use via the near infrared sensors. Thus we demonstrate the potential for up-to-date volcanic economic risk assessment using geographic information systems (GIS) analysis.     

快速区域互相关InSAR图像配准方法

在分析复图像干涉相位对快速互相关算法配准精度影响的基础上,提出了一种快速区域互相关InSAR图像配准方法。该方法对图像的幅度谱进行区域相关操作,获得干涉相位空间角频率的粗估计,并对主图像进行干涉相位补偿。该算法通过上述步骤消除干涉相位变化对算法的影响实现了高精度配准。在仿真实验和实测实验中,通过与传统的快速区域互相关算法及最大频谱法进行对比,验证了本文算法的稳健性与有效性。     

Joint interferometric calibration based on block adjustment for an airborne dual-antenna InSAR system

Mapping large areas using airborne dual-antenna interferometric synthetic aperture radar (InSAR) usually requires processing and mosaicking of different scenes from multiple strips. The overlapping areas of these multiple strips should have consistent elevation values. Due to the unstable attitude of the plane, the interferometric parameters usually vary for each scene during mapping. Therefore, interferometric calibration technology for high-precision height retrieval is required for the correction of the interferometric errors. The traditional interferometric calibration methods for a single scene usually use ground control points (GCPs) to estimate the interferometric parameters – this method cannot guarantee a consistent height in the area of overlap. Besides, GCPs are difficult to deploy over rough terrain, making it impossible to use traditional calibration methods. In this article, a joint interferometric calibration method based on the block adjustment theory used in photogrammetry is proposed for airborne dual-antenna InSAR. This method considers the accurate digital elevation model (DEM) height reconstruction model and can be applied with sparse GCPs. The principle of the proposed method is to make the best use of the GCPs within all the scenes and the tie points (TPs) between the adjacent scenes to establish an error relationship model. First, the weighting values of all GCPs and TPs based on their retrieval elevation error caused by the interferometric phase error and the position distribution difference are introduced in the proposed method. Next, the interferometric parameters are weighted to reduce the condition number of the normal equation. Then, an alternative approximation approach combined with the sparse matrix decomposition technique LDL^T is utilized to solve the normal equation, and the corrected interferometric parameters for each scene are obtained. High-precision joint interferometric calibration results for airborne InSAR systems are achieved by the proposed method and validated by experiment. Using the proposed method, the average mean error (AME) and root mean square error (RMSE) are below 0.6037 and 0.9176 m, respectively. Meanwhile, the maximum AME and RMSE of the reconstructed DEM height difference for the validation TPs in the overlapped area of the adjacent scenes are reduced from 1.2909 and 1.7245 m to 0.8864 and 1.2087 m, respectively.     

Improved Modeling of Elevation Error with Geostatistics

The elevations recorded within digital models are known to be fraught with errors of sampling, measurement and interpolation. Reporting of these errors according to spatial data standards makes several implicit and unacceptable assumptions about the error: it has no spatial distribution, and it is statistically stationary across a region, or even a nation. The approach explored in this paper employs actual elevations measured in ground and aerial survey at higher precision than the elevations in the DEM and recorded on standard paper maps. These high precision elevations are digitized and used to establish the real statistical and spatial distribution of the error. Direct measurements could also have been taken in the field by GPS or any other means of high precision data collection. These high precision elevations are subtracted from values stored in the DEM for approximately the same locations. The distribution of errors specific to the DEM can then be explored, and can be used in the geostatistical method of conditional stochastic simulation to derive alternative realizations of the error modeled and so of the DEM. Multiple versions of the derived products can also be determined. This paper compares the results of using different methods of error modeling. The best method, which gives widely implementable and defensible results, is that based on conditional stochastic simulation.     

Effects of residual motion compensation errors on the performance of airborne along-track interferometric SAR

Two approximations, center-beam approximation and reference digital elevation model (DEM) approximation, are used in synthetic aperture radar (SAR) motion compensation procedures. They usually introduce residual motion compensation errors for airborne single-antenna SAR imaging and SAR interferometry. In this paper, we investigate the effects of residual uncompensated motion errors, which are caused by the above two approximations, on the performance of airborne along-track interferometric SAR (ATI-SAR). The residual uncompensated errors caused by center-beam approximation in the absence and in the presence of elevation errors are derived, respectively. Airborne simulation parameters are used to verify the correctness of the analysis and to show the impacts of residual uncompensated errors on the interferometric phase errors for ATI-SAR. It is shown that the interferometric phase errors caused by the center-beam approximation with an accurate DEM could be neglected, while the interferometric phase errors caused by the center-beam approximation with an inaccurate DEM cannot be neglected when the elevation errors exceed a threshold. This research provides theoretical bases for the error source analysis and signal processing of airborne ATI-SAR.     

Filling voids of SRTM with Landsat sensor imagery in rugged terrain

The Shuttle Radar Topography Mission (SRTM) delivered a free digital elevation model (DEM) with a spatial resolution of 3″ at near global coverage. However, there are many data voids in the SRTM data that need to be filled before their application. In this Letter, a novel void‐filling method, which uses Landsat sensor imagery to provide detailed information on terrains for the filling procedure, is proposed. Valleys are extracted from Landsat sensor imagery first, then elevation values of SRTM voids along valleys are interpolated, and finally the remaining voids are patched with the global coarse resolution DEM. The test results show that the elevation values filled with the proposed method perform better than those filled with the traditional method and local geomorphological features can be maintained with the proposed method.     

Construction of a high-resolution DEM of an Arctic ice cap using shape-from-shading

Digital elevation models (DEMs) of ice sheets and ice caps are usually constructed from elevation data acquired from airborne or satellite-borne altimetric systems. Consequently, the DEMs have a spatial resolution of about 1km which limits their use for most glaciological and remote sensing studies. In this paper we investigated the possibility of using a shape-from-shading technique, applied to a Landsat MSS image, to create a high spatial resolution DEM of Austfonna, an ice cap in Svalbard. A high correlation (coefficient of determination = 0.85) was observed between Landsat pixel brightness values, acquired during winter, and the surface slope component parallel to the solar azimuth. This relationship was used to create a DEM by calculating surface elevation profiles across the ice cap, using low spatial resolution radio echo sounding data as tie points. The resulting DEM had an estimated rms error of about 14m, with the error occurring mostly at low spatial frequencies. Shape-from-shading produces less accurate DEMs than interferometric SAR (InSAR) techniques. Nevertheless, in scenarios for which InSAR cannot be used to construct a DEM, shape-from-shading provides an acceptable alternative.     

A detection method for near-ship wakes based on interferometric magnitude,phase and physical shape in ATI-SAR systems

Near-ship wakes approximately form a triangle region on the sea surface, and they differ from the background sea in a wave pattern, wave propagation direction and velocity, and fluid particle orbital motion. The differences are observed by along-track interferometric synthetic aperture radar (ATI-SAR) systems, and can be properly measured by the ATI techniques. In this paper, a detection method for near-ship wakes based on interferometric magnitude, phase and physical shape in ATI-SAR systems is proposed. The complex multi-look interferometric information for near-ship wakes is first utilized to detect potential pixels. Then, a cluster algorithm is designed based on the interferometric phase and spatial position characteristics of near-ship wakes. After clustering the detected pixels and performing image close operation, the near-ship wakes, which is the triangular region with a much larger physical area than those of common ships or other false alarms, can be identified. Finally, simulation results validate the effectiveness of the proposed method.     

Cross-validation as a means of investigating DEM interpolation error

Studies of the detailed characteristics of DEM error have been hampered by the difficulty in obtaining a large sample of error values for a DEM. The approach proposed in this paper is to resample a DEM to a lower resolution and then reinterpolate back to the original resolution which produces a large sample of error values well distributed across the DEM. This method is applied to a sample area from Scotland, which contains a variety of terrain types. The results show that the standard measure of error, the root mean square error (RMSE) of elevation, shows only moderate correlation with a visual assessment of the quality of DEMs produced by a range of interpolation methods. The frequency distribution and strength of spatial autocorrelation are shown to vary with the initial data density and interpolation method. When the source data density is low, the error has strong spatial autocorrelation and a distribution that is close to being Gaussian. However, as the data density increases, levels of spatial autocorrelation drop and the distribution becomes leptokurtic with values very strongly clustered around zero. At the level of the individual DEM point, elevation error is shown to be a poor predictor of error in slope derivatives which depend on the spatial pattern of elevation errors around the point and are also sensitive to differences in terrain. At the level of a whole DEM, however, RMSE of elevation is a good predictor of RMSE in gradient and aspect but not of curvature.