A New Retracking Technique for Brown Peaky Altimetric Waveforms

A new Brown-Peaky (BP) retracker has been developed for peaky waveforms that usually appear within ～10 km to the coastline. The main feature of the BP is that it fits peaky waveforms using the Brown model without introducing a peak function. The retracking strategy first detects the peak location and width of a waveform using an adaptive peak detection method, and then estimates retracking parameters using a weighted least squares (WLS) estimator. The WLS assigns a downsized weight to corrupted waveform gates, but an equal weight to other normal waveform gates. The BP retracker has been applied to 4-year Jason-1 waveform (2002–2006) in two Australian coastal zones. The results retracked by BP, MLE4 and ALES retrackers have been validated against tide-gauge observations located at Burnie, Lorne and Broome. The comparison results show that three retrackers have similar performance over open oceans with the correlation coefficient (～0.7) and RMSE (～13 cm) between altimetric and tide-gauge sea levels for distance >7 km offshore. The main improvement of BP retracker occurs for distance ≤7 km to the coastline, where validation results indicate that data retracked by BP are more accurate (15–21 cm) than those by ALES (16–24 cm) and MLE4 (19–37 cm).     

A-FPN算法及其在遥感图像船舶检测中的应用

光学遥感图像船舶检测主要面临两个挑战:光学遥感图像背景复杂,船舶检测易受海浪、云雾及陆地建筑等多方面干扰;遥感图像分辨率低,船舶目标小,对于其分类与定位带来很大困难;针对上述问题,在FPN的基础上,提出一种融入显著性特征的卷积神经网络模型A-FPN (Attention-Based Feature Pyramid Networks)。首先,利用卷积提取图像特征金字塔;然后,利用顶层金字塔逐级构建显著特征层,抑制背景信息,通过金字塔顶层的细粒度特征提高浅层特征的表达能力,构建自上而下的多级显著特征映射结构;最后利用Softmax分类器进行多层级船舶检测。A-FPN模型利用显著性机制引导不同感受下的特征进行融合,提高了模型的分辨能力,对遥感图像处理领域具有重要应用价值。实验阶段,利用公开的遥感目标检测数据集NWPU VHR-10中的船舶样本进行测试,准确率为92.8%,表明A-FPN模型适用于遥感图像船舶检测。     

波段选择协同表达高光谱异常探测算法

高光谱遥感影像具有光谱分辨率极高的特点,承载了大量可区分不同类型地物的诊断性光谱信息以及区分亚类相似地物之间细微差别的光谱信息,在目标探测领域具有独特的优势。与此同时,高光谱遥感影像也带来了数据维数高、邻近波段之间存在大量冗余信息的问题,高维度的数据结构往往使得高光谱影像异常目标类和背景类之间的可分性降低。为了缓解上述问题,本文提出了一种基于波段选择的协同表达高光谱异常探测算法。首先,使用最优聚类框架对高光谱波段进行选择,获得一组波段子集来表示原有的全部波段,使得高光谱影像异常目标类与背景类之间的可分性增强。然后使用协同表达对影像上的像元进行重建,由于异常目标类和背景类之间的可分性增强,对异常目标像元进行协同表达时将会得到更大的残差,异常目标像元的输出值增大,可以更好地实现异常目标和背景类的分离。本文使用了3组高光谱影像数据进行异常目标探测实验,实验结果表明,该方法与其他现有高光谱异常目标探测算法对比,曲线下面积AUC(Area Under Curve)值更高,可以更好地实现异常目标与背景分离,能够更有效地对高光谱影像进行异常目标探测。     

大同—阳高Ms6.1地震前兆综合加权信息熵的变化

利用“地震预报计算机专家系统”的思想对大同 -阳高 Ms6 .1地震前每一前兆异常事件进行综合评估 ,以每一异常的最可能发震时间来计算发震概率 ,利用地震前兆综合加权信息熵研究了系统熵值与地震的关系。对华北地区的地震前兆综合加权信息熵研究表明 ,在大同 -阳高 Ms6 .1地震前 ,信息熵出现了明显的减熵有序变化     

An atlas of the optical spectrum of supernova 1987A in the large magellanic cloud

Photographic spectra of SN1987A in the LMC have been obtained from 1987 February 25 to 1988 June 30. Microdensitometer tracings of these have been reduced to intensity and corrections for instrumental response have been applied to the spectra. This paper presents these data in an atlas format, discusses the reduction procedures in detail, and presents radial velocity measurements of selected lines in the spectra     

昆仑山口大地震与地形变异常的讨论

针对昆仑山口大地震，总结了多种地形变（大地测量）手段所显示的异常变化及其时空分布，结果显示：8．1级大震前存在空间尺度大，时间尺度的地形变前兆异常，简要介绍了相关的异常图像，给出了初步解释，并对未来震情的发展进行了探讨，认为近期内强震活动向华北迁移的可能性不大。     

滇西北和邻区均衡重力异常特征及其壳内构造

本文以爱黎-海斯卡宁均衡补偿假设模式为基础,利用圆模板编制了滇西北及邻区均衡重力异常图。分析了异常的基本特征与壳内构造的关系,并初步探讨了均衡重力异常和强震活动的相关性。     

山东内生金矿矿床谱系及其致矿地质异常

矿床谱系是对成矿多样性的理论概括,而成矿多样性又是由不同级别、不同性质的致矿地质异常决定的.本文论述了山东省内生金矿矿床谱系及其致矿地质异常.     

TROS-Ⅰ型流动人卫激光测距仪光学系统设计

介绍了车载流动型人卫激光测距仪光学系统(包括激光发射系统、接收系统及微光电视监视系统)的设计思想和方法,着重叙述了光学系统的结构设计、关键部件几何尺寸的确定及重要元器件的选取。设计基于流动型仪器应满足的防振、体积小、调校方便、抗环境干扰能力强等特点。多年的实测证明,这种光学系统不仅能满足流动型人卫激光测距仪总体设计要求,而且经济实用。     

Optical and X-Ray Observations of the Symbiotic System Ag Draconis During Quiescence and Outburst

We review the main characteristics of the symbiotic system AG Draconis, with special emphasis on its optical and X-ray variations. We also discuss the X-ray to visual energy distribution during quiescence and outburst and describe our spectroscopic and X-ray observations during the 2003 outburst. Based on X-ray observations collected with the XMM–Newton Observatory, on INES data from the IUE satellite, and on optical spectra collected with the Asiago–Cima Ekar, Bologna–Loiano and La Palma–Galileo Italian telescopes.