ICESat-2 ATL03数据预处理及校正方法

2018年9月15日,美国航空航天局成功发射了ICESat-2卫星,ICESat-2搭载了地形激光测高仪系统（ATLAS）,已经广泛应用于极地冰盖高程测量、海冰厚度估算、陆地高程测量、地表植被测量等多个研究领域。不同于GLAS/ICESat,ATLAS在信号探测系统中采用更为灵敏的单光子探测器,每秒发射10 000个脉冲（GLAS/ICESat系统每秒发射40个脉冲）,可以获取到重复频率更高、光斑更小的高密度光子计数回波数据,进而实现高精度全球观测。由于ATLAS采用的探测器光电倍增管（PMT）after-pulse的影响,在回波信号脉冲输出后常会出现小幅度脉冲干扰,不能准确反映原始信号波形,所以在实际应用过程中,必须对测量信号进行校正。首先基于ATL03产品,对光子计数回波数据进行预处理,获得了海冰、海洋、陆地和沙漠的廓线信息,结果显示在主信号回波之后均存在两个小的脉冲回波（约2.3 m和4.2 m处）,此外陆地和沙漠在10~45 m间存在一个更长时间延迟的脉冲回波,证实了不同反射表面均会受到PMT after-pulse影响。然后利用ICESat-2卫星过境撒哈拉沙漠地区的夜间观测数据,计算了不同波束下的脉冲响应函数,6个波束得到的脉冲响应函数整体形态相似,在主信号回波后出现三个不同幅度的脉冲回波（约2.3 m、4.2 m和6.5 m处）。最后利用6个波束的脉冲响应函数对同一海洋剖面进行校正,结果显示除ATLAS Beam2外,其余波束均可有效滤除主脉冲之后的小幅度脉冲,校正得到真实的水下回波信号。     

ICESat-2激光雷达海面信号提取和海浪要素计算

美国NASA于2018年发射的ICESat-2 (The Ice, Cloud, and land Elevation Satellite-2)卫星上搭载的ATLAS (Advanced Topographic Laser Altimeter System)是目前为止全球唯一一个对地观测的星载光子计数激光雷达,具有较高的轨向空间采样率,为用遥感的方法探测海浪要素提供了可能。光子计数激光雷达用于海浪探测的前提是能够准确地提取来自海面的信号光子,并确定瞬时的海面廓线。迄今为止,用星载光子计数激光雷达探测海面形态和海浪要素的研究鲜见报道,也缺少专门针对海面信号光子的提取方法。基于海面信号光子的分布特点,文中提出了一种新的信号提取算法：首先通过直方图统计及自适应的阈值选取完成对海面回波光子的粗去噪;然后基于激光雷达光斑尺寸和海面波动特点,选取合适的搜索邻域计算信号点和噪声点密度,根据两者点密度差异对信号光子和噪声光子分类;最后用高斯函数拟合的方法进一步去除密度较大的后向散射噪声光子,最终得到来自海面反射的信号光子。利用上述算法提取了太平洋7个不同海况区域的海面信号光子和瞬时海面廓线并进一步计算...     

ICESat-2星载光子计数激光雷达数据处理与应用研究进展

ICESat-2/ATLAS系统首次采用微脉冲多波束光子计数激光雷达技术,其在探测方式、数据处理方法、应用的广度和深度等方面与ICESat-1/GLAS存在明显差异。首先介绍了ICESat-2及ATLAS的性能指标、数据特点和产品信息,详细分析了光子点云去噪和分类两个关键技术,以及各算法的适应性及难点,总结了ICESat-2数据在冰盖和海冰高程测量及其变化监测、地面高程提取、森林高度提取和生物量估算、湖泊水位和蓄水量变化监测等方面的应用,最后展望了光子数据处理和应用的发展趋势和前景。     

基于Sentinel-1/2遥感数据的冬小麦覆盖地表土壤水分协同反演

冬小麦是我国重要粮食作物之一,对冬小麦覆盖地表土壤水分进行监测有助于解决因土壤供水导致的冬小麦歉收和农业用水浪费等问题.为了降低冬小麦覆盖地表土壤水分微波遥感反演过程中冬小麦对雷达后向散射系数的影响,该文基于Sentinel-1携带的合成孔径雷达(SAR)数据和Sentinel-2携带的多光谱成像仪(MSI)数据,结合水云模型,开展冬小麦覆盖地表土壤水分协同反演研究.首先,基于MSI数据,该文定义了一种新的植被指数,即融合植被指数(FVI),用于冬小麦含水量反演;然后,该文发展了一种基于主被动遥感数据的冬小麦覆盖地表土壤水分反演半经验模型,校正冬小麦在土壤水分反演过程中对雷达后向散射系数的影响;最后,以河南省某地冬小麦农田为研究区域,开展归一化水体指数(NDWI)和FVI两种指数与VV,VH,VV/VH 3种极化组合而成的6种反演方式下的土壤水分反演对比实验.结果表明:以FVI为植被指数,能够更好地去除冬小麦在土壤水分反演过程中对雷达后向散射系数的影响;6种反演方式中,FVI与VV/VH组合下的反演效果最优,其决定系数为0.7642,均方根误差为0.0209 cm3/cm3,平均绝对误差为0.0174 cm3/cm3,展示了该文所提土壤水分反演模型的研究价值和应用潜力.     

基于Sentinel-1/2遥感数据的冬小麦覆盖地表土壤水分协同反演

冬小麦是我国重要粮食作物之一,对冬小麦覆盖地表土壤水分进行监测有助于解决因土壤供水导致的冬小麦歉收和农业用水浪费等问题.为了降低冬小麦覆盖地表土壤水分微波遥感反演过程中冬小麦对雷达后向散射系数的影响,该文基于Sentinel-1携带的合成孔径雷达(SAR)数据和Sentinel-2携带的多光谱成像仪(MSI)数据,结合...     

基于随机森林的ICESat-2卫星数据地表覆盖分类

该研究将ICESat-2卫星激光测高数据作为地表覆盖分类的新数据源,提出了一种基于随机森林的ICESat-2卫星地表覆盖分类方法,探索了光子计数卫星激光测高在地表覆盖分类中的应用潜力。该方法采用光子数目、不同类型光子水平和垂直分布比例、信噪比、太阳条件、大气条件作为分类的输入,并在中国长三角地区开展了多类地表覆盖类型分类实验进行了验证。实验结果表明,ICESat-2卫星的强波束和弱波束的激光数据在水体、森林、低植被以及城市/裸地四类地表的总体分类精度均能达到优于85%;在水体、森林以及低植被/城市/裸地三类地表的总体分类精度能达到优于90%的水平。     

面向ICESat-2单光子激光雷达的陆地目标测距误差分析

单光子激光雷达所获取的光子事件存在随机分布的特点,使得其激光测距值出现不确定性,从而降低了单光子激光雷达的测距精度。在不减小采样分辨率的情况下,采用累积邻近多光斑的光子事件来构建光子累积直方图,并基于反算的目标响应函数的时间重心来确定激光测距值。针对ICESat-2单光子激光雷达,以测距均方根误差（RMSE）和平均绝对误差（MAE）为性能指标,构建出一种综合考虑陆地地形、累积光斑数目和回波光子数等多因素对其测距误差影响的评估方法。同时,选取ICESat-2过境美国犹他州西瓦利城的某观测条带的随机地形数据进行验证分析。结果表明,所提出的激光测距值解算方法能够使该条带的测距RMSE值由114.25 cm降低到63.84 cm,MAE值由70.97 cm降低到48.52 cm,均优于ICESat-2数据产品提供的137.96 cm RMSE值和97.24 cm MAE值,这对提升单光子激光雷达在陆地区域的测距精度具有一定的借鉴作用。     

Speaker verification under mismatched data conditions

This study presents investigations into the effectiveness of the state-of-the-art speaker verification techniques (i.e. GMM?UBM and GMM?SVM) in mismatched noise conditions. Based on experiments using white and real world noise, it is shown that the verification performance offered by these methods is severely affected when the level of degradation in the test material is different from that in the training utterances. To address this problem, a modified realisation of the parallel model combination (PMC) method is introduced and a new form of test normalisation (T-norm), termed condition adjusted T-norm, is proposed. It is experimentally demonstrated that the use of these techniques with GMM?UBM can significantly enhance the accuracy in mismatched noise conditions. Based on the experimental results, it is observed that the resultant relative improvement achieved for GMM?UBM (under the most severe mismatch condition considered) is in excess of 70%. Additionally, it is shown that the improvement in the verification accuracy achieved in this way is higher than that obtainable with the direct use of PMC with GMM?UBM. Moreover, it is found that while the accuracy performance of GMM?SVM can also considerably benefit from the use of these techniques, the extensive computational cost involved in this case severely limits the use of such a combined approach in practice.     

Adjusting software failure rates that are estimated from test data

Software test environments are often different from field environments. Using test data exclusively to estimate a field failure rate will not usually give a very accurate estimate. In this paper, we extend an empirical calibration methodology for adjusting the failure rate estimate obtained from analysing test data. In addition to scaling the estimated failure rate of a fault, we propose scaling the estimated number of residual faults as well. We also derive likelihood ratio tests to formally determine (from previous releases of the software) if test, and field environments are significantly different. We illustrate our new results with two telecommunications case studies. The combination of the likelihood ratio test, and the calibration methodology offers a practical way to extend the application of software reliability growth models to less formal test environments.     

Validation of temporal BRDFs of paddy fields estimated from MODIS reflectance data

The effect of the bidirectional reflectance distribution function (BRDF) is one of the most important factors in correcting and validating the reflectance obtained from remotely sensed data. While the importance of BRDF has become widely recognized, bidirectional reflectance factor (BRF) data measured for correction and validation are insufficient because of the technical difficulty of the measurement. The primary objective of the present research is to estimate BRDF effects from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Temporal ground-based BRDFs of rice paddy fields were estimated from ground measurements conducted in June and August 2002. MODIS-derived BRDFs obtained from MODIS reflectance data and ground-based BRDFs were estimated using the reciprocal form of the RossThick and LiSparse (RossThick-LiSparse-R) kernels, a semiempirical BRDF model adopted for the operational MODIS BRDF product. The MODIS-derived band 1 (620-680 nm) and band 2 (841-876 nm) BRDFs were compared with the ground-based BRDFs corresponding to the same waveband, respectively. The comparison results demonstrate that BRDFs of paddy fields change in accordance with paddy growth and that MODIS-derived BRDFs are closely related to ground-based BRDFs in most of the cases. It was also revealed that MODIS-derived BRDFs can be estimated to a high degree of accuracy when MODIS data necessary for the estimation are available.     

On the reconstruction of height functions and terrain maps from dense range data

This paper describes a method for combining multiple, dense range images to create surface reconstructions of height functions. Height functions are a special class of three-dimensional (3-D) surfaces, where one 3-D coordinate is a function of the other two. They are relevant for application domains such as terrain modeling or two-and-half dimensional surface reconstruction. Dense range maps are produced by either a range measuring device combined with a scanning mechanism or a triangulation scheme, such as active or passive stereo. The proposed method follows from a statistical formulation that characterizes the optimal surface estimate as the one that maximizes the posterior probability conditional on the input data and prior information about the application domain. Because the domain of the reconstruction is a two-dimensional (2-D) scalar function, the optimal surface can be expressed as an image, and the variational form of that optimization produces a 2-D partial differential equation (PDE). The PDE consists of two parts: a first-order data term and a second-order smoothing term. Thus optimal surface reconstruction is formulated as the solution to a second-order, nonlinear, PDE on an image, which is related to the family of PDE-based image processing algorithms in the literature. This paper presents the theory for reconstruction and some particular aspects of the numerical implementation. It also analyzes results on both synthetic and real data sets, which show a 75%-95% reduction of the RMS sensor error.     

Comparison of irregular terrain propagation models for use indigital terrain data based radiocommunication system planning tools

The availability of digital terrain models (DTM) or terrain data bases (TDB) has prompted the use of point-to-point prediction models to compute propagation losses due to terrain irregularity. Traditionally, area prediction models (like ITU-R Recommendation 370, Longley and Rice, etc) have been used for coverage computation. These models require very little information regarding terrain characteristics and provide poor accuracies. Here, an assessment of several point-to-point models using detailed terrain information and aimed to be used in radiocommunication planning tools based on TDBs is presented. Two main characteristics are considered for comparison, namely, accuracy and ease in terrain data handling     

TD-LTE信令数据准确性核查方法

随着TD-LTE网络的建设和大数据技术的逐渐成熟,基于TD-LTE信令数据进行网络质量分析已然成为当前趋势.通过采集海量XDR话单进行用户感知和网络性能分析,正在成为一种越来越重要的分析手段.数据源的完整性和准确性是分析的基石,文章分析数据采集的关键字段,制定核查算法,应用于当前信令分析系统.