基于卫星遥感数据的全球表层流场反演重构

利用2000—2008年的卫星高度计资料和QuikSCAT风场资料,反演了全球的海表的地转流和Ekman流,将两者合成后生成了0.5°×0.5°的逐周全球表层流产品。在计算Ekman流的时候,引入了权重函数,改进了Lagerloef方法中Ekman流在25°S和25°N上的不连续问题。分析表明:卫星资料反演的流产品能够反映出海表流场的特征,将其分别与TAO观测和SCUD流产品进行定量化的比较显示,所得流产品具有较高的反演精度和可信度,说明改进的方法是有效的。     

利用卫星重力梯度恢复局部地球重力场的研究进展

简述了SGG数据恢复局部重力场的理论本质以及卫星重力梯度边值问题;详细介绍了当前国内外利用SGG进行局部重力场求解的研究进展,并将已有的求解方法总结归纳为三类：模型法、计算法和组合法,同时对各种方法的概念和研究现状作了详细介绍;最后总结了SGG数据求解局部重力场的发展前景和思考建议。     

The SARAL/AltiKa Altimetry Satellite Mission

The India-France SARAL/AltiKa mission is the first Ka-band altimetric mission dedi-cated to oceanography. The mission objectives are primarily the observation of the oceanic mesoscales but also include coastal oceanography, global and regional sea level monitoring, data assimilation, and operational oceanography. Secondary objectives include ice sheet and inland waters monitoring. One year after launch, the results widely confirm the nominal expectations in terms of accuracy, data quality and data availability in general.

Today's performances are compliant with specifications with an overall observed performance for the Sea Surface Height RMS of 3.4 cm to be compared to a 4 cm requirement. Some scientific examples are provided that illustrate some salient features of today's SARAL/AltiKa data with regard to standard altimetry: data availability, data accuracy at the mesoscales, data usefulness in costal area, over ice sheet, and for inland waters.     

一种地球静止轨道卫星的快速恢复定轨方法

地球静止轨道(GEO)卫星频繁的轨道机动对高精度、实时不间断的导航服务需求提出新的更高要求,如何在短弧跟踪条件下提高GEO卫星轨道快速恢复能力,是提升导航系统服务精度的关键因素。针对该问题,提出基于9参数星历拟合的GEO卫星短弧运动学定轨方法,详细推导定轨的数学模型与偏导模型,针对GEO卫星星历参数拟合中的奇异问题,提出相应的解决方法和措施。利用COMPASS GEO卫星实测自发自收数据进行短弧定轨试验与分析,结果表明:①10 min短弧运动学定轨的位置精度优于19 m,速度精度为4 mm/s,速度精度明显优于MEO卫星;②预报5 min的位置精度为17.760 m,预报10 min的位置精度为18.168 m;③解决GEO卫星频繁轨控所带来的轨道快速恢复问题,满足短弧跟踪条件下RDSS的服务需求。     

Seasonal Variation of Space/Time Statistics of Short-Term Sea Surface Temperature Variability in the Kuroshio Region

Spatial and temporal scales of sea surface temperature (SST) variations in the Kuroshio region have been investigated using a satellite-based one-year merged SST product. Targeting short-term variations with temporal scales of less than a year, decorrelation scales, which are defined as the e-folding scale of SST variability, have been derived as functions of regional positions and calendar months. We assumed that the autocorrelation function of SST has anisotropic Gaussian characteristics in the space-time domain. Resultant spatial and temporal decorrelation scales range from 1 to 3° and 2 to 3 days, respectively. They are strongly inhomogeneous, anisotropic and time-dependent. These characteristics are attributed to the oceanic and atmospheric disturbances. Spatial decorrelation scales are determined mainly by strong atmospheric forcing in the study region. In the area with dominant atmospheric forcing, the spatial scales are larger than those in the other regions. Those in the regions with dynamical oceanographic disturbances are as small as 1°. Signal-to-noise ratios are also large where the atmospheric forcing is strong, while they are small where the oceanic signals are active.     

嵊泗地区风浪分布及其时间变化分析

通过对嵊泗地区实测波浪资料的分析,探讨了嵊泗地区的风浪分布形式。并且依据1992年12月至2002年8月的TOPEX卫星高度计资料给出了本地区长期有效波高的时间变化,为该地区海洋减灾防灾和工程设计提供了科学依据。     

基于GPS的多站实时时间传递算法

提出了一种基于GPS的多站实时时间传递算法,该算法将卫星钟差作为未知参数进行实时估计,利用测站间的共视卫星建立起各测站误差方程之间的联系,同时解算站间时间传递结果和卫星钟差。摆脱了对外部事后精密卫星钟差产品的依赖,不受卫星精密钟差产品精度和实时性的限制,只要站间有足够的共视卫星,即可实现时间传递。实验结果表明:该算法时间传递精度可以达到亚纳秒量级,能够应用于高精度实时时间传递。     

Three-Dimensional Geographically Weighted Inverse Regression (3GWR) Model for Satellite Derived Bathymetry Using Sentinel-2 Observations

Current trends of development of satellite derived bathymetry (SDB) models rely on applying calibration techniques including analytical approaches, neuro-fuzzy systems, regression optimization and others. In most of the cases, the SDB models are calibrated and verified for test sites, that provide favorable conditions for the remote derivation of bathymetry such as high water clarity, homogenous bottom type, low amount of sediment in the water and other factors. In this paper, a novel 3-dimensional geographical weighted regression (3GWR) SDB technique is presented, it binds together methods already presented in other studies, the geographically weighted local regression (GWR) model, with depth dependent inverse optimization. The proposed SDB model was calibrated and verified on a relatively difficult test site of the South Baltic near-shore areas with the use of multispectral observations acquired by a recently launched Sentinel-2 satellite observation system. By conducted experiments, it was shown that the proposed SDB model is capable of obtaining satisfactory results of RMSE ranging from 0.88 to 1.23[m] depending on the observation and can derive bathymetry for depths up to 12m. It was also shown, that the proposed approach may be used operationally, for instance, in the continuous assessment of temporal bathymetry changes, for areas important in the context of ensuring local maritime safety.     

Pushbroom-Frame Imagery Co-Registration

More and more littoral surveys are conducted with aerial platform sensor suites that include a hyperspectral pushbroom sensor and a frame camera. However, in some cases, data from auxiliary sensors may contain errors or are not available. For many research groups, a high-accuracy registration of the multi-sensor data relative to each other is essential, while absolute geo-location of each individual measurement is not. A co-registration procedure was developed for pseudo ortho-rectification of the hyperspectral imagery and to remove spatial distortions caused by the aircraft's trajectory during the survey based on a flat-earth assumption. This image-processing approach utilizes the aerial frame imagery as a reference. Each hyperspectral scan line is co-registered into the frame imagery coordinate system. The performance of the procedure was evaluated using hyperspectral imagery collected over northern New Hampshire and southern Maine. The evaluation results showed that the procedure is robust enough to pseudo ortho-rectify hyperspectral imagery over coastal areas and to remove significant spatial distortions.     

GEO导航卫星定轨观测模型

根据GEO导航卫星的轨道特性,给出了严密的伪距观测和载波相位观测数学模型;讨论了其轨道和星钟差的解算条件,以及多星组差定轨的可行性。结果表明:在利用伪距时,如果测站钟差已知,需要4个以上站的数据才能进行定轨和星钟解算;如果站钟、星钟钟差已知,需要3个以上站的数据才能确定轨道。在利用站间组差伪距时,须有4个以上测站的钟差信息才能进行轨道和星钟解算;利用GEO卫星与MEO(IGSO)卫星组差定轨时,需要GEO卫星钟差已知且有3组星间组差数据。利用GEO卫星载波相位观测资料,不能单独解算轨道。