罗兰C和卫星导航的组合应用

论述了目前罗兰C和卫星导航组合应用的几种方式,对罗兰C和卫星导航伪距组合定位以及罗兰C和卫星导航定位数据融合的原理和方法进行了论证,通过罗兰C和卫星导航的组合应用,可以克服单一导航系统的弱点,提高组合导航的性能,拓展了罗兰C的应用领域,延长了罗兰C的使用周期。     

NOAA卫星监测船舶溢油

ＮＯＡＡ气象卫星主要任务是探测全球大气，通过波段筛选和各种处理，也可以监测海洋原油、重柴油污染，这必将成为我国一种新的海洋环境监测手段。     

引入轨道特征的北斗列车定位方法研究

列车定位是轨道交通众多应用的基础条件,北斗卫星导航用于列车定位能够有效提升我国轨道交通装备的自主性.针对列车北斗定位性能对运行条件的适应性需求,本文提出一种引入轨道特征的北斗列车定位方法,该方法从轨道电子地图中提取轨道特征参数,在列车状态预测的系统模型中增加轨道约束,并利用一维地图位置预测拓展北斗导航卫星的伪距测量.利用现场实测数据构建场景进行仿真.所得结果表明,本文提出的方法能够提高列车定位解算对卫星可视条件的鲁棒性,有效拓展北斗列车定位在恶劣观测条件下的可用水平,具有较高的实际应用价值.     

Optimal interpolation of sea surface temperature for the North Sea and Baltic Sea

Sea surface temperature fields of the North Sea and Baltic Sea have been constructed for the year 2001 using a multiplatform Optimal Interpolation scheme. The analyzed fields are constructed every 12 h on a 10 km spatial grid. The product is based upon observations from the three NOAA satellites 12, 14 and 16 together with a large amount of in situ observations. Space dependent covariance functions are estimated from the satellite observations and account for spatial and temporal lags. Several independent methods have been used to assess the error on the sea surface temperature product. Compared against independent in situ observations, the mean RMS difference for the year 2001 is 0.78 °C. The spatial distribution of the errors reveals that the Baltic Sea in general show higher errors than the North Sea. The error statistics throughout the year show a temporal variation of the errors with maximum during summer and winter. Tests with a varying number of satellite observations show that the accuracy of the satellite observations is the most important parameter in terms of reducing the errors on the interpolated sea surface temperature product.     

舰载GPS航姿测量中卫星位置的计算与最优星座的选取

该文给出了在GPS航姿测量算法研究中的卫星位置计算的整个过程,数据处理采用RINEX标准输入格式,所得结果形象直观,便于分析。在此基础上提出了一种选择最优星座的方法。作为试验算例,最后给出了以广播星历参数为基础的GPS航姿测量中最优星座的选取结果。     

卫星罗经的原理及其应用

罗经是为船舶提供航向的航海仪器,在比较了陀螺罗经和磁罗经不同特点的基础上,介绍了一种新的指向仪器—基于GPS接收机的卫星罗经的系统组成、工作原理及其应用。     

基于北斗导航的列车定位技术研究

北斗卫星已逐步具备应用于列车定位的能力,为北斗卫星导航在铁路系统中的应用发展提供重要契机。将北斗卫星导航系统应用到列车定位系统,不仅能提高定位精度,而且能降低成本,也是列车运行控制系统安全性与可靠性的有力保障,对于列车定位系统的研究具有深远意义。与四大卫星导航系统进行比较,根据列车定位技术的分类,归纳各自特点和研究方向,最后指出基于北斗导航的列车定位技术下一步的重点工作。     

基于TBC4.1软件的高速铁路CP0框架控制网基线解算与网平差精度分析

针对天宝公司研发的新版本TBC4.1软件在高速铁路CP0框架控制网基线解算与网平差的可行性问题,以京沪高速铁路CP0框架控制网作为研究对象,将最新版TBC4.1软件与GAMIT10.7软件、旧版本TBC3.5软件的基线解算能力进行比较,并与Cosa GPS软件的网平差精度进行对比,用试验的方法讨论TBC4.1软件加载不同类型卫星星历对不同基线长度高速铁路CP0框架控制网的基线解算与网平差精度。结果表明:TBC4.1软件较旧版本TBC3.5软件在长基线解算能力上得到了很大的提高;在处理800 km范围内的高速铁路CP0框架网基线时,TBC4.1软件获得与GAMIT10.7软件相当的解算精度,且不受精密星历种类的限制;当CP0框架网的基线长度由800 km扩大至1 500 km时,TBC4.1软件加载最终星历的基线解算精度仍能与GAMIT10.7的解算精度保持一致;TBC4.1软件网平差模块的处理精度为毫米级,且不受精密星历种类解算的基线结果限制。     

Monitoring Crustal Deformations with Radar Interferometry： A Review

The crustal movements, probably motivating earthquakes, are considered as one of the main geodynamic sources. The quantitative measurements of ground surface deformations are vital for studying mechanisms of the buried faults or even estimating earthquake potential. A new space-geodetic technology, synthetic aperture radar interferometry (InSAR), can be applied to detect such large-area deformations, and has demonstrated some prominent advantages. This paper reviews the capacity and limitations of InSAR, and summarises the existing applications including some of our results in studying the earthquake-related crustal motions.Finally it gives the outlook for the future development of InSAR.     

Forecasting front displacements with a satellite based ocean forecasting (SOFT) system

Relatively long term time series of satellite data are nowadays available. These spatio–temporal time series of satellite observations can be employed to build empirical models, called satellite based ocean forecasting (SOFT) systems, to forecast certain aspects of future ocean states. The forecast skill of SOFT systems predicting the sea surface temperature (SST) at sub-basin spatial scale (from hundreds to thousand kilometres), has been extensively explored in previous works. Thus, these works were mostly focussed on predicting large scale patterns spatially stationary. At spatial scales smaller than sub-basin (from tens to hundred kilometres), spatio–temporal variability is more complex and propagating structures are frequently present. In this case, traditional SOFT systems based on Empirical Orthogonal Function (EOF) decompositions could not be optimal prediction systems. Instead, SOFT systems based on Complex Empirical Orthogonal Functions (CEOFs) are, a priori, better candidates to resolve these cases.In this work we study and compare the performance of an EOF and CEOF based SOFT systems forecasting the SST at weekly time scales of a propagating mesoscale structure. The SOFT system was implemented in an area of the Northern Balearic Sea (Western Mediterranean Sea) where a moving frontal structure is recurrently observed. Predictions from both SOFT systems are compared with observations and with the predictions obtained from persistence models. Results indicate that the implemented SOFT systems are superior in terms of predictability to persistence. No substantial differences have been found between the EOF and CEOF-SOFT systems.