基于球谐函数模型的GPS电离层延迟改正分析

电离层延迟误差是影响GPS导航和定位的最主要因素,但由于电离层本身的不稳定性,以及目前对其物理特性还不甚了解,我们只能采用精度有限的经验模型和数学模型对其进行描述。本文介绍了利用球谐函数模型模拟电离层延迟的原理与方法,采用双频伪距精确获得电离层延迟,模拟了中国地区上空的电离层延迟,并对模拟结果进行了分析比较,得出了几点有益结论。     

基于球谐函数区域电离层模型建立

利用GPS双频观测数据建立高精度、准实时的区域电离层总电子含量(TEC)模型是电离层研究的一个重要手段。文中探讨IGS观测站数据结合4阶球谐函数建立区域电离层格网模型的方法,并对硬件延迟(DCB)和TEC建模结果的可靠性进行分析,结果表明,DCB解算精度在0.4ns以内,TEC内外精度优于1.4TECU(1TECU=1016电子数/m2)和1.5TECU,满足导航定位中电离层改正的需要。     

GTDM:一种获取全球对流层延迟的新模型

对流层延迟是GNSS定位的主要误差源.现有的各对流层延迟模型大多存在过度拟合的弊端,不能反映延迟在短时间内的细节变化.本文利用2011—2017年ECMWF气象资料分析了对流层延迟的变化特征,发现同一格网相邻年份之间全球对流层延迟偏差绝大多数在5 cm内.在此基础上,本文提出了一种非参数拟合的对流层延迟模型GTDM.经...     

一类球谐函数与三角函数乘积积分的计算

本文根据球谐函数的跨次递推公式和三角函数的性质,详细推导了在重力梯度调和分析中出现的一类球谐函数积分的跨次递推公式和递推初始值的计算公式。数值试验表明,球谐函数跨次递推算法具有快速、稳定的优点。该类积分的跨次递推实现,为卫星重力梯度调和分析奠定了算法基础。     

北斗系统全球电离层建模理论与方法研究

电离层延迟是卫星导航系统的主要误差源.北斗卫星导航系统(BDS )已由区域系统(北斗二号系统,BDS-2 )发展为全球系统(北斗三号系统,BDS-3 ) ,BDS-3星座具有全球覆盖、区域异构的特点,卫星播发了S和L频段多个导航信号,向下兼容 BDS-2的 B1I和 B3I信号,增加B1C、B2a(兼容 GPSL1/L...     

Far-zone effects for different topographic-compensation models based on a spherical harmonic expansion of the topography

The determination of the gravimetric geoid is based on the magnitude of gravity observed at the surface of the Earth or at airborne altitude. To apply the Stokes’s or Hotine’s formulae at the geoid, the potential outside the geoid must be harmonic and the observed gravity must be reduced to the geoid. For this reason, the topographic (and atmospheric) masses outside the geoid must be “condensed” or “shifted” inside the geoid so that the disturbing gravity potential T fulfills Laplace’s equation everywhere outside the geoid. The gravitational effects of the topographic-compensation masses can also be used to subtract these high-frequent gravity signals from the airborne observations and to simplify the downward continuation procedures. The effects of the topographic-compensation masses can be calculated by numerical integration based on a digital terrain model or by representing the topographic masses by a spherical harmonic expansion. To reduce the computation time in the former case, the integration over the Earth can be divided into two parts: a spherical cap around the computation point, called the near zone, and the rest of the world, called the far zone. The latter one can be also represented by a global spherical harmonic expansion. This can be performed by a Molodenskii-type spectral approach. This article extends the original approach derived in Novák et al. (J Geod 75(9–10):491–504, 2001), which is restricted to determine the far-zone effects for Helmert’s second method of condensation for ground gravimetry. Here formulae for the far-zone effects of the global topography on gravity and geoidal heights for Helmert’s first method of condensation as well as for the Airy-Heiskanen model are presented and some improvements given. Furthermore, this approach is generalized for determining the far-zone effects at aeroplane altitudes. Numerical results for a part of the Canadian Rocky Mountains are presented to illustrate the size and distributions of these effects.     

一种基于双频GPS接收机的精确快速相对定位方法

利用GPS载波相位测量可以精确确定两个载体间的相对距离，其核心问题是整周模糊度的快速求解，通过双频数据可以提高模糊度求解的速度。在推导模糊度组合的一般公式的基础上，研究了一种基于双频GPS接收机模糊度快速求解算法。实验证明该方法正确有效。     

A new method for generating a clear-sky Landsat composite for cropland from cloud-contaminated Landsat-7 and Landsat-8 images

A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data.     

顾及地物要素特征的电子地图POI分类抽稀方法

探讨影响POI分类抽稀结果的因素,提出顾及地物要素特征的POI数据分类抽稀方法。通过不同比例尺下POI分类抽稀试验分析,验证所提方法的可行性和有效性,提高电子地图中POI数据在不同比例尺下抽稀显示的合理性,从而满足用户专业需求。     

基于GT的钟差预测模型辅助GPS定位算法研究

为了解决在强干扰环境下由于GPS卫星信号被遮挡而无法定位的问题,从灰色理论(GT)的角度探讨了接收机的钟差序列,提出一种利用灰色理论的钟差预测模型辅助GPS定位的方法。对预测模型的基本思想和具体实现步骤作了详细的介绍,并且将钟差预测值引入到GPS接收机中,实现信号遮挡情况下GPS接收机的定位解算。通过对实测数据的验证分析表明,该钟差预测模型对钟差序列有很好的预测效果,能够在仅有3颗可观测卫星的情况下实现接收机的定位解算。     

Open source map matching with Markov decision processes: A new method and a detailed benchmark with existing approaches

Map matching is a widely used technology for mapping tracks to road networks. Typically, tracks are recorded using publicly available Global Navigation Satellite Systems, and road networks are derived from the publicly available OpenStreetMap project. The challenge lies in resolving the discrepancies between the spatial location of the tracks and the underlying road network of the map. Map matching is a combination of defined models, algorithms, and metrics for resolving these differences that result from measurement and map errors. The goal is to find routes within the road network that best represent the given tracks. These matches allow further analysis since they are freed from the noise of the original track, they accurately overlap with the road network, and they are corrected for impossible detours and gaps that were present in the original track. Given the ongoing need for map matching in mobility research, in this work, we present a novel map matching method based on Markov decision processes with Reinforcement Learning algorithms. We introduce the new Candidate Adoption feature, which allows our model to dynamically resolve outliers and noise clusters. We also incorporate an improved Trajectory Simplification preprocessing algorithm for further improving our performance. In addition, we introduce a new map matching metric that evaluates direction changes in the routes, which effectively reduces detours and round trips in the results. We provide our map matching implementation as Open Source Software (OSS) and compare our new approach with multiple existing OSS solutions on several public data sets. Our novel method is more robust to noise and outliers than existing methods and it outperforms them in terms of accuracy and computational speed.     

Defining a DORIS core network for Jason-1 precise orbit determination based on ITRF2000: methods and realization

In view of the future adoption of the new precise orbit determination (POD) standards for the TOPEX/Poseidon and Jason-1 satellites, we propose a method to evaluate terrestrial reference frames for POD. We applied this method to the ITRF2000 realization of the DORIS network using local geodetic ties, plate motion models, the recent DORIS IGN04D02 cumulative solution and DORIS weekly time-series of coordinates. We propose to adopt a selection of the ITRF2000 realization based on specific criteria that we define here, and to extend it with ground stations for which we propose new coordinates and velocities. Only 13 out of 131 stations were considered to be inappropriate for POD activities. The result is a robust and well-distributed DORIS core network of 118 stations (DPOD2000) suitable for POD during the 1993–2008 period considered here.     

WOFOST模型与遥感数据同化的土壤速效养分反演

土壤速效养分是作物生长的必要条件,合理控制土壤速效养分含量对粮食增产、农民增收以及环境保护都有重要意义。随着现代农业技术的发展,可以通过变量施肥将土壤速效养分含量控制在最佳状态,这也对土壤养分的获取精度提出了更高的要求。当前的主要土壤速效养分遥感监测方法在监测精度、稳定性、成本控制和可推广性依然存在一定不足,甚至限制对变量施肥的指导作用。本文针对传统土壤速效养分估算方法的不足,提出了利用作物模型与时间序列遥感数据相结合实现耕层土壤速效养分反演的新思路,该思路以养分缺失引起的作物长势参数的变化为切入点,在数据同化算法设计和养分模块优化改造的基础上,利用作物长势参数遥感监测结果与模型模拟结果的差异设计了土壤速效养分反演算法,实现速效养分含量信息的有效获取。设计地面观测实验并利用地面观测数据对反演精度进行评价,结果表明该方法可以对土壤中的速效养分进行实时、高精度的稳定反演,3种主要的速效养分速效氮、有效磷和速效钾的R2分别达到了0.68、0.74和0.52,平均相对误差分别为7.45%、6.17%和9.97%。     

基于光能利用效率的区域蒸散量反演模型——以玉米种植区为例

以内蒙古河套地区解放闸灌域为研究区域,以实测生物量与土壤含水量及其关系方程为研究基础,建立了基于光能利用效率(radiation use efficiency,RUE)的区域蒸散量反演模型;以陆面能量平衡(surface energy balance algorithm for land,SEBAL)模型为参考,对反演的同一时期的区域蒸散量进行对比分析.结果表明:RUE与SEBAL模型反演的区域蒸散量在空间分布和纹理特征方面具有相似性且相关性较高,决定系数高于农业技术推广支持系统(decision support system for agrotechnology transfer,DSSAT)与SEBAL的;基于RUE建立的区域蒸散量反演模型能够较好地反映区域蒸散量,在监测区植被(或作物)单一的前提下,是一种有效方法.     

Remote sensing of cirrus optical and microphysical properties from ground-based infrared radiometric Measurements-part I: a new retrieval method based on microwindow spectral signature

The surface radiance spectrum within the terrestrial infrared window (i.e., wavelengths between 8-12 /spl mu/m or wavenumbers between 833-1250 cm/sup -1/) is sensitive to the optical and microphysical properties of cirrus clouds. Numerous microwindows where atmospheric absorption is minimum exist in the spectral regions of 820-960 cm/sup -1/ and 1100-1240 cm/sup -1/. The minimum radiances at the microwindows in these two spectral regions can be fitted by using two linear lines. The slope of the fitting line for the spectral region of 820-960 cm/sup -1/ is sensitive to the effective size of ice crystals within cirrus clouds, whereas the intercept of the fitting line for the spectral region of 1100-1240 cm/sup -1/ is sensitive to the optical thickness of the clouds. Based on this spectral feature, a new retrieval method has been developed for simultaneously retrieving cirrus optical thickness and the effective particle size of ice crystals. Furthermore, the ice water path of cirrus clouds can be estimated from the retrieved values of cloud optical thickness and effective particle size.     

时序InSAR滑坡形变监测与预测的N-BEATS深度学习法——以新铺滑坡为例

滑坡通常发生突然,破坏力巨大,经常造成重大生命安全事故和财产损失。高可靠性、高精度及具有抗差性能的滑坡形变监测预测手段和方法对于国家防灾减灾需求具有切实意义。InSAR技术是一种能够全天时和全天候观测获取高空间分辨率和宽覆盖率影像,高灵敏性捕捉时空维动态变化的监测手段,然而目前应用InSAR时序影像对滑坡区进行滑坡预测的工作仅是凤毛麟角。基于时序InSAR观测结果,本文提出了一种能够有效解决中短期滑坡预测问题的深度学习滑坡预测方法。在三峡新铺滑坡区应用N-BEATS网络模型和Sentinel-1 SAR数据进行形变预测,以均方根误差1.1 mm的预测精度完成了滑坡预测工作,并对预测结果进行了数据结构影响的规律性分析、传统方法效果对比、抗差性评估及置信区间估计等多方位的剖析,结果显示出了其高精度、高可靠性及具有一定抗差能力的突出优势。     

机载LiDAR技术支持下的荒漠地区1:10 000地形图测绘与研究——以内蒙古阿拉善地区为例

尝试应用机载LiDAR技术测绘1：10 000比例尺地形图3D（DLG、DEM、DOM）产品,给出了机载LiDAR测绘3D产品的技术流程,并选择荒漠地区作为试验区,验证了此种技术方法在荒漠地区测绘3D产品的可行性,分析了成果精度。试验证明,该方法可以满足荒漠区域的1：10 000比例尺3D基础数据生产要求,且具有外业工作量小、自动化程度高、成图快、高程精度高、受外界环境影响小等优点,同时也总结了该方法中有待完善之处。该方法为荒漠地区3D基础测绘数据获取提供了有益借鉴。     

Preliminary analytical method for unsupervised remote sensing image classification based on visual perception and a force field

Abstract

The analysis of remote sensing (RS) images, which is often accomplished using unsupervised image classification techniques, requires an effective method to determine an appropriate number of classification clusters. This paper proposes a preliminary analytical method to evaluate the input parameters for unsupervised RS image classification. Our approach involves first analysing the colour spaces of RS images based on the human visual perception theory. This enables the initial number of clusters and their corresponding centres to be automatically established based on the interaction of different forces in our supposed force field. The proposed approach can automatically determine the appropriate initial number of clusters and their corresponding centres for unsupervised image classification. A comparison of the experimental results with those of existing methods showed that the proposed method can considerably facilitate unsupervised image classification for acquiring accurate results efficiently and effectively without any prior knowledge.