A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

利用监督分类快速提取分层设色图件中数据的方法

为了快速将分层设色图件中象元的颜色值转化为具有实际意义的属性标识或物理、化学参数值,从而提取分层设色图件中包含的数据,作者提出了根据不同颜色分量(RGB)构建颜色特征空间,基于最小距离监督分类方法快速提取分层设色图件中数据的方法。使用该方法对东半球海域海面水汽分布数据进行提取,取得了良好的效果。该方法可以广泛应用于物理海洋、环境科学、地质调查、地理信息系统建库等多个行业领域的数据提取工作中。     

国产抛弃式温度剖面仪(XBT)资料质量分析

国家海洋技术中心根据科研需求研发了抛弃式温度剖面仪(XBT)等一系列抛弃式产品.针对2014年8月份在西太平洋海域投放的XBT和XCTD所获取的温度数据进行对比分析,单剖面结果显示两者相关系数达到了0.95,在温跃层处出现温度差,断面标准差分析结果为200 m以上温跃层处较大而200m以下标准差较小,最大和最小标准差值分别为0.39和0.08.温度断面分析结果显示两者在同样的位置出现等值线的凹凸现象,对大洋水团特殊物理海洋现象描述基本一致.分析温跃层处两者温度存在偏差的原因有3个:不同传感器的不同响应时间引起的误差、深度测量公式的误差以及传感器本身的测量误差影响.国产XBT的数据质量较好,总体上性能能满足对环境复杂海域的快速走航观测,数据质量准确度和可靠性都较好.     

南海某导管架海洋平台倒塌分析

针对在役老龄导管架平台进行倒塌计算分析,确定极限承载力进而评估老龄导管架的安全裕度。采用非线性有限元方法,考虑平台的波流载荷及桩-土的非线性相互作用,利用SACS软件建立导管架整体三维有限元计算分析模型,并用逐步加载的方式,对南海某导管架平台进行了全过程非线性倒塌分析。计算分析表明,该导管架平台极限强度很高,具有较大的安全裕度;导管架倒塌过程呈逐步破坏形式,先是撑杆屈服,造成局部结构破坏,然后是钢桩发生屈服,降低结构承载力,最后节点逐步失效,造成结构倒塌。揭示了导管架平台结构失效倒塌的机理,给出了倒塌分析的可行方法和步骤。     

基于地理格网分级法提取的中国传统村落空间分布

中国传统村落真实地记录了建筑、民俗民风和较原始的民居空间形态,是千百年来人类与自然和谐共存的生活基础。随着城市化进程加快,传统村落的存续受到了很大的挑战,为了更好地保护利用传统村落,对其进行多视角的研究尤为重要,除了微观层面的具体保护措施外,还应加强宏观层面的空间分布研究。地理格网是表达复杂地理现象、综合分析自然与人文数据、模拟地理系统功能与行为的基本方法。本文从百度影像地图提取村落坐标,并截取遥感影像作为村落点数据的判断补充,在此基础上,运用地理格网的分级法,对国家公布的三批中国传统村落(2555个)数据进行空间格局分析,结果表明：这些村落主要分布在中国东南部,如落在一级格网Ⅰ18、Ⅰ19就分别有586、781个村落,占三批传统村落总数的96.6%。通过对二级和三级格网的村落分布离散性进行分析,使传统村落的空间分布数据结构更加系统和清晰有序,为合理构建其数据库提供了框架基础。     

粉末压片-X射线荧光光谱法测定盐湖样品中的主次元素

采用粉末样品压片制样,利用波长色散X射线荧光光谱仪对盐湖样品中K、Ca、Na、Mg、Cl、SO_4~(2-)等6个主次元素(组分)含量进行测定。使用化学定值得到的样品作为人工标样,其值作为标准样品参考值,建立了X射线荧光光谱法测定盐湖样品中主次元素的方法。经验证,该分析方法的准确度完全能够满足化学分析的要求,其相对标准偏差RSD7%,分析元素结果与化学法结果的相对误差均小于5%。     

Discussion on applying an analytical method to optimize the anti-freeze design parameters for underground water pipelines in seasonally frozen areas

Adopting the quasi-three-dimensional (Quasi-3D) numerical method to optimize the anti-freeze design parameters of an underground pipeline usually involves heavy numerical calculations. Here, the fitting formulae between the safe conveyance distance (SCD) of a water pipeline and six influencing factors are established based on the lowest water temperature (LWT) along the pipeline axis direction. With reference to the current widely used anti-freeze design approaches for underground pipelines in seasonally frozen areas, this paper first analyzes the feasibility of applying the maximum frozen penetration (MFP) instead of the mean annual ground surface temperature (MAGST) and soil water content (SWC) to calculate the SCD. The results show that the SCD depends on the buried depth if the MFP is fixed and the variation of the MAGST and SWC combination does not significantly change the SCD. A comprehensive formula for the SCD is established based on the relationships between the SCD and several primary influencing factors and the interaction among them. This formula involves five easy-to-access parameters: the MFP, buried depth, pipeline diameter, flow velocity, and inlet water temperature. A comparison between the analytical method and the numerical results based on the Quasi-3D method indicates that the two methods are in good agreement overall. The analytic method can be used to optimize the anti-freeze design parameters of underground water pipelines in seasonally frozen areas under the condition of a 1.5 safety coefficient.     

南极长城站验潮站数据处理和潮汐特点初步分析

继在南极中山站建成我国南极首个永久性验潮站后,2012年1月在南极长城站又建成了我国南极第二个永久性验潮站。通过对长城站验潮站相关数据进行分析处理,得到了验潮基准系统的水准网平差结果和验潮仪零点标定结果,以及长城站附近海域海洋潮汐170个分潮的调和常数,并据此进行了潮汐预报,同时分析了长城站潮汐余水位的变化特征,探讨了利用附近的Antarctic Base Prat验潮站的余水位改正长城站潮汐预报的可行性,结果表明使用Antarctic Base Prat验潮站余水位改正长城站潮汐预报,可以显著提高长城站验潮站潮汐预报的精度,余水位改正后2014时段的潮汐预报中误差为±3.42 cm,明显好于改正前的预报中误差±10.43 cm。     

Uncertainty analysis of space–time prisms based on the moment-design method

Space–time prism (STP) is an important concept for the modeling of object movements in space and time. An STP can be conceptualized as the result of the potential path of a moving object revolving around in the three-dimensional space. Though the concept has found applications in time geography, research on the analysis and propagation of uncertainty in STPs, particularly under high degree of nonlinearity, is scanty. Based on the efficiency and effectiveness of the moment-design (M-D) method, this paper proposes an approach to deal with nonlinear error propagation problems in the potential path areas (PPAs) of STPs and their intersections. Propagation of errors to the PPA and its boundary, and to the intersection of two PPAs is investigated. Performance of the proposed method is evaluated via a series of experimental studies. In comparison with the Monte Carlo method and the implicit function method, simulation results show the advantages of the M-D method in the analysis of error propagation in STPs.     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.