GPS Ambiguity Resolution: Impact of Time Correlation,Cross-Correlation and Satellite Elevation Dependence

In this contribution we discuss the geometry-free GPS single baseline model and show how the least-squares ambiguities are affected by changes in the stochastic model. We particularly pay attention to the effect of time correlation, cross-correlation and satellite elevation dependence. We also differentiate between the impact on the location of the ambiguity search space and the impact on the size and shape of the search space. The analysis is carried out for both the model in which the ionospheric delays are assumed absent, and for the model in which they are assumed present. The former model is applicable to short baselines only.     

Seismic data compression based on integer wavelet transform

Introduction With the development of the seismological observation technique and deep-going of seismicdata application fields, especially the digitization of data in earthquake station networks, theimprovement of the precision, the data quantity increases as geometric order, which bringdifficulty to saving and transfering these data. To keep all information, seismic data, like medicalimages, should be compressed without error in many applications. In generally, traditionalcompression meth…     

A new approach of single epoch GPS posi- tioning for landslide monitoring

Introduction China is a country with many landslides and debris flows. These disasters bring out a large amount of losses of life and property. It is significant to predict landslide incident by monitoring the deformations of these landslides. At past, triangulation and trilateration are traditional tools, but it is very difficult for them to realize real-time monitoring, and it is more dangerous for obser- vation workers when the deformation becomes larger. Because of many advantages such as…     

北斗卫星导航系统双差动力法精密定轨及其精度分析

针对GEO卫星切向轨道分量与双差模糊度强相关的问题,对经典双差动力法进行了改进,提出联合使用载波相位和相位平滑伪距实现北斗系统精密定轨,并从理论上分析了以上处理策略的可行性及对模糊度固定的影响,然后结合北斗系统精密定轨特点,推导给出了利用QIF方法实现北斗卫星双差模糊度固定的基本原理,实测数据分析表明:联合载波相位和相位平滑伪距,既可降低相关性,又可兼顾精度,定轨效果优于经典双差动力法;利用QIF方法能够取得一定的模糊度固定效果,但受观测条件限制,北斗卫星双差模糊度固定成功率整体不高,双差模糊度固定之后对轨道的改进作用有限。     

基于载波相位的GPS周跳恢复方法研究

在GPS定位中,周跳的探测和修复是获得高精度定位结果的前提。针对载波相位周跳数据的探测和修复这一问题已经提出了很多方法,但都有各自的不足之处。文中针对恶劣环境下的载波相位定位问题,通过使用多个历元的数据构建方程,提出一种新的整周模糊度定义方法,并预期能够在仅有3颗可用卫星且周跳发生时实现快速、准确的定位。     

改进的距离约束最小二乘模糊度搜索算法

针对短基线最小二乘模糊度搜索算法搜索效率低的缺点,该文提出了一种改善模糊度搜索空间以提高模糊度搜索效率的方法。最小二乘搜索算法通过基线长度范围确定模糊度搜索空间,完成模糊度的搜索和确认。距离约束的短基线模糊度搜索空间是一个空心椭球,各模糊度之间具有相关性,影响模糊度搜索效率。该文通过最小二乘去相关调整方法降低模糊度之间的相关性,减少搜索次数。实验证明,该算法的搜索效率提高了25%以上,且随着基线长度的增加,搜索效率有更多的提升。     

大型GNSS观测网的并行计算

CGCS2000精化及其全球拓展需要采用最新的模型,处理长期积累的大型GNSS观测网数据,大型GNSS网联合、快速和协同解算是空间基准精化、维持与服务的重要技术方向.在大数据技术背景下,以并行计算、云计算为代表的高性能计算技术逐渐成为大规模数据处理的首选方法.针对海量、多源、异构GNSS数据在解算处理与平差分析等方面面...     

北斗卫星类型间偏差快速改正分析

针对北斗卫星类型间偏差（ISTB）导致载波相位差分高精度定位（RTK）的整周模糊度无法固定问题,本文提出了改进ISTB快速改正方法,在观测量层面仅利用1组不同卫星类型的载波相位差分观测量即可实现ISTB估计与改正,实际应用中较传统方法更具普适性与简易性。该方法的测试结果表明,ISTB值由NH码调制不同引起,不同频点的ISTB值具有不一致性;此外,有无改正ISTB的北斗RTK性能对比反映了ISTB会严重降低整周模糊度固定与RTK定位性能。由此可知,本文方法能够保障现阶段北斗接收机更新换代过程中北斗RTK的高精度与高可靠性能。     

长距离GPS/BDS参考站网多频载波相位整周模糊度解算方法

长距离网络RTK是实现GPS/BDS高精度实时定位的主要手段之一,其核心是长距离参考站网GPS/BDS整周模糊度的快速准确确定。本文提出了一种长距离GPS/BDS参考站网载波相位整周模糊度解算方法,首先利用GPS双频观测数据计算和确定宽巷整周模糊度,同时利用BDS的B2、B3频率观测值确定超宽巷整周模糊度。然后建立GPS载波相位整周模糊度和大气延迟误差的参数估计模型,附加双差宽巷整周模糊度的约束,解算双差载波相位整周模糊度,并建立参考站网大气延迟误差的空间相关模型。根据B2、B3频率的超宽巷整周模糊度建立包含大气误差参数的载波相位整周模糊度解算模型,利用大气延迟误差空间相关模型约束BDS双差载波相位整周模糊度的解算。克服了传统的使用无电离层组合值解算整周模糊度的不利影响。采用实测长距离CORS网GPS、BDS多频观测数据进行算法验证,试验结果证明该方法可实现长距离参考站网GPS/BDS载波相位整周模糊度的准确固定。     

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.