基于立体补偿的遥感立体像对压缩方法

提出研究遥感立体像对的压缩问题。主要讨论了左右影像的视差补偿和辐射补偿。针对遥感立体像对视差分布不均以及左右影像存在辐射差的特点,提出了一种基于立体补偿的遥感立体像对压缩算法。该算法以左片为基准图像,采用自适应视差估计计算出右片的视差矢量,结合辐射校正和重叠块视差补偿技术得到平滑的右片的预测图像,以右片减去预测图像得到残差图像,然后采用小波压缩算法对残差图像进行压缩。实验结果表明,该算法能显著提高遥感立体像对的压缩性能。     

Integer aperture bootstrapping: a new GNSS ambiguity estimator with controllable fail-rate

In this contribution, we introduce a new bootstrap-based method for Global Navigation Satellite System (GNSS) carrier-phase ambiguity resolution. Integer bootstrapping is known to be one of the simplest methods for integer ambiguity estimation with close-to-optimal performance. Its outcome is easy to compute due to the absence of an integer search, and its performance is close to optimal if the decorrelating Z-transformation of the LAMBDA method is used. Moreover, the bootstrapped estimator is presently the only integer estimator for which an exact and easy-to-compute expression of its fail-rate can be given. A possible disadvantage is, however, that the user has only a limited control over the fail-rate. Once the underlying mathematical model is given, the user has no freedom left in changing the value of the fail-rate. Here, we present an ambiguity estimator for which the user is given additional freedom. For this purpose, use is made of the class of integer aperture estimators as introduced in Teunissen (2003). This class is larger than the class of integer estimators. Integer aperture estimators are of a hybrid nature and can have integer outcomes as well as non-integer outcomes. The new estimator is referred to as integer aperture bootstrapping. This new estimator has all the advantages known from integer bootstrapping with the additional advantage that its fail-rate can be controlled by the user. This is made possible by giving the user the freedom over the aperture of the pull-in region. We also give an exact and easy-to-compute expression for its controllable fail-rate.     

A new method for indentifying the model error of adjustment system

Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed formula, an effective approach of selecting the best model of adjustment system is given. Project supported by the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (No. 905276031-04-10).     

Investigating the propagation mechanism of unmodelled systematic errors on coordinate time series estimated using least squares

The propagation of unmodelled systematic errors into coordinate time series computed using least squares is investigated, to improve the understanding of unexplained signals and apparent noise in geodetic (especially GPS) coordinate time series. Such coordinate time series are invariably based on a functional model linearised using only zero and first-order terms of a (Taylor) series expansion about the approximate coordinates of the unknown point. The effect of such truncation errors is investigated through the derivation of a generalised systematic error model for the simple case of range observations from a single known reference point to a point which is assumed to be at rest by the least squares model but is in fact in motion. The systematic error function for a one pseudo-satellite two-dimensional case, designed to be as simple but as analogous to GPS positioning as possible, is quantified. It is shown that the combination of a moving reference point and unmodelled periodic displacement at the unknown point of interest, due to ocean tide loading, for example, results in an output coordinate time series containing many periodic terms when only zero and first-order expansion terms are used in the linearisation of the functional model. The amplitude, phase and period of these terms is dependent on the input amplitude, the locations of the unknown point and reference point, and the period of the reference point's motion. The dominant output signals that arise due to truncation errors match those found in coordinate time series obtained from both simulated data and real three-dimensional GPS data.     

短期集合降水概率预报试验

以MM5模式作为试验模式, 通过选取不同的物理过程参数化方案产生8个集合成员, 分别用平均法、相关法和Rank法对2001年11月至2002年5月期间的22个降水个例进行短期集合降水概率预报试验。试验结果显示对小雨—大暴雨6类降水的概率预报, Rank法的综合预报效果明显好于相关法和平均法, 相关法的综合预报效果与平均法基本相同; 无论从均方误差角度还是从命中率和假警报率的相对大小角度, 对小雨、中雨、大雨和暴雨各量级以上降水的概率预报, Rank法的平均预报效果是三种方法中最好的, 相关法的平均预报效果与平均法相同; Rank法好于平均法的平均幅度从均方误差角度较大, 从命中率和假警报率的相对大小角度则较小。平均而言, 三种方法对各量级以上降水的概率预报都是有技巧预报, 对量级小的降水的概率预报技巧高于对量级大的降水的概率预报技巧。     

淮河流域土壤湿度异常的时空分布特征及其与气候异常关系的初步研究

利用中国东部1990~2000年旬平均土壤湿度、降水和气温观测资料，通过对0~50 cm层次土壤湿度进行旋转主分量分析 (REOF)，重点分析了淮河流域土壤湿度的时空分布特征, 并初步研究了土壤湿度与前期、同期和后期不同时段降水与气温的关系。发现春季以30 cm为界，30 cm以上各层土壤湿度异常的第一旋转空间模态十分相似, 其大值中心主要位于淮河流域，而30 cm以下 (30~50 cm) 各层的第二旋转空间模态与之亦十分类似, 因此称该模态为“淮河型”，而夏季和秋季虽然该模态也很显著, 但特征不如春季突出。该模态在各层次土壤中具有明显的持续性特征，均存在40旬左右的显著周期；并与前期和同期降水（气温）呈显著正 (负) 相关关系，与约半年后的降水 (气温) 呈负 (正) 相关关系。     

K 近邻非参数回归概率预报技术及其应用

针对参数回归技术制作概率预报存在拟合好、但预报结果不稳定的现象, 提出了用K近邻非参数回归技术制作概率预报的新途径。K 近邻非参数回归技术包括历史样本数据库、近邻子集生成和优化以及预报量估计4 个主要部分。利用该技术进行了单要素概率预报(主要包括云量和降水)和多维联合概率预报(降水、总云量、风速和气温)试验, 并对试验结果进行了检验。实例研究结果表明:该文所给出的计算方案预报稳定性好, 准确率较高,具有良好的业务应用价值。     

我国松花江流域和辽河流域降水的长期变化规律和未来趋势分析

利用1881～2002年我国东北地区的月、季降水资料,采用历史曲线分析、功率谱分析、小波变换等方法,重点分析了松花江流域和辽河流域降水的长期变化规律。结果表明:松花江流域和辽河流域的降水都存在着明显的年代际变化,松花江流域降水以27～30年周期为主,辽河流域降水周期比松花江流域略长,大概为35～38年左右。根据降水自身演变规律及自回归方法预测的结果,估计未来5～10年,松花江流域仍将处于少雨期,辽河流域少雨期维持时间可能会稍长一些。     

东亚冬季风异常与广东前汛期旱涝关系的初步分析

利用500hPa北半球格点资料,参照历史平均东亚大槽位置,定义了东亚冬季风强度指数(I₅₀₀)。分析发现,近50年东亚冬季风强度有减弱趋势,特别是1987年以来冬季风明显减弱。根据广东48个站1954～2004年前汛期(4～6月)降水资料,用区域旱涝指数W对广东前汛期旱涝等级进行划分。51年内广东有9年前汛期出现大涝(或特涝),11年出现大旱(或特旱),旱涝发生频繁。冬季风异常对广东前汛期降水的影响比较大,强冬季风年后广东前汛期出现大旱的可能性较大,而出现大涝的可能性很小。     

西北地区不同类型云的时空分布及其与降水的关系

利用1983年7月～2001年9月国际卫星云气候计划ISCCP D2的月平均资料，对西北不同区域不同类型云的云量和云水路径的时空分布及其与降水的关系进行了研究。结果表明:高原气候区是各种云出现最多的地区，特别是积状云的云量明显高于其他两区，但这些云的云水路径值低；西北地区大多数云云量的高值区出现在天山山区、北疆地区、陕西东南部和青藏高原的部分地区。高云和部分中云云量空间分布特征与降水有着较好的一致性:沿着天山—昆仑山—祁连山一带以及陕南和／或陇南地区是高值区，低值区在塔里木盆地—内蒙古西部戈壁沙漠—黄土高原西北部一带；绝大多数云类春夏季节云量维持较高，秋冬季节云量较少。云水路径值较大的层状云类的云量多寡与降水多寡相一致；积状云类和层积云类云量多少与降水没有一定的关系，在降水偏少时，这类云的云量大多与降水正常时相近，有些云的云量甚至比降水偏多时还要多。