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1.
基于GPS新型L5信号的地表雪深反演研究   总被引:1,自引:0,他引:1  
利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明:与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。  相似文献   

2.
GPS信噪比用于雪深监测研究   总被引:2,自引:0,他引:2  
针对利用全球导航卫星系统反射信号研究测站地表环境参数已成为一个新兴的研究课题这一现状,该文基于全球定位系统信噪比与信号振幅的变化特征,给出了基于全球定位系统多路径信号的全球定位系统多径反射技术用于雪深探测的基本原理。为了验证算法的有效性,利用美国PBO网络中P360站离散20d的全球定位系统原始观测数据进行雪深探测的反演实验。实验结果表明:全球定位系统多径反射技术反演雪深值与实测雪深值吻合较好,误差均值为0.07m,相关系数大于0.99。因此,利用全球定位系统信噪比可以进行雪深探测,在未来的全球导航卫星系统观测站建立时,可以考虑它在环境监测方面表现出来的潜能。  相似文献   

3.
本文对全球定位系统干涉反射技术进行了研究。以美国板块边界天文台计划提供的P101测站的GPS监测数据为基础,利用GPS卫星高度角低于某一角度时多路径效应明显的特点,构建高斯过程回归(GPR)辅助的GPS干涉反射积雪深度估测模型,并监测了测站周围的积雪深度。结果表明,GPR辅助的GPS干涉反射积雪深度估测模型输出的雪深估测值的精度,相比传统单星反演结果有不同程度的提高,并且更贴近实测雪深的变化,为地表雪深反演提供了新思路。  相似文献   

4.
全球定位系统干涉反射测量GPS-IR(Global Positioning System Interferometric Reflectometry)是利用多路径信噪比反射分量参数幅度、相位、频率的变化监测地表环境的技术。针对多路径信号中同时包含卫星直射信号和反射信号,传统低阶多项式难以准确提取卫星反射信号有效参数的问题,本文利用小波分析对卫星直射、反射信号进行分离,准确获取卫星反射信号,利用熵值法多星融合模型反演土壤湿度。经理论和实验研究表明:该方法能够更为精确地反映测站周围土壤湿度的变化,有效改善了部分异常跳变现象。相关系数为0.914,相比单星反演模型至少提高18.4%。  相似文献   

5.
研究了GPS干涉反射技术GPS-IR(GPS-Interferometric Reflectometry);在利用GPS卫星SNR信号进行积雪深度探测的基础上构建了支持向量机SVM(Support Vector Machine)辅助的GPS SNR雪深时间序列反演模型;对积雪深度进行时间序列预报和与传统GPS-IR积雪探测模型进行精度对比分析。实验结果显示,相比传统GPS-IR雪深反演模型,SVM辅助的GPS SNR雪深时间序列反演模型的雪深预报结果的精度更高,也更符合实测雪深的变化趋势,可为地面积雪雪深反演提供新方法。  相似文献   

6.
利用GNSS-MR(Global Navigation Satellite System Multipath Reflectometry)技术反演积雪深度是近年来一种新兴的卫星遥感技术。目前大多数研究仅使用GPS(Global Position System)数据限制了该技术的发展,为了扩展GNSS-MR算法的应用,介绍了基于GNSS-MR算法的雪深反演模型。首先,通过多项式拟合分解GLONASS观测数据获取高精度的信噪比残差序列;然后,利用Lomb-Scargle谱分析法对其进行频谱分析可解算雪深值。选取IGS中心的YEL2站2015年11月到2016年6月共243天的GLONASS卫星L1波段反射信号的SNR数据进行实例分析,并以美国国家气象数据中心提供的加拿大Y-H (Yellowknife Henderson)气象站的实测雪深数据为真值,将反演雪深与实测雪深进行对比验证。所得实验结果如下:(1)与GPS卫星的反演值相比,基于GLONASS-MR(GLONASS Multipath Reflectometry)技术反演积雪深度的精度同样能达到厘米级,RMSE仅3.3 cm,反演值与实测值的空间分布趋势一致且相关性较强,其相关系数R2高达0.969;(2)不同的积雪深度对信噪比的振幅频率与垂直反射距离具有直接影响;(3)对同一卫星而言,信噪比的频谱振幅强度峰值与其对应的反演值存在线性相关;(4)在相同条件下,采用多颗GLONASS卫星数据比单颗GLONASS卫星数据反演雪深的效果明显更优。基于反演的高时间分辨率产品,分析该地区雪深日变化的情况,实验结果表明基于陆基CORS站的GLONASS-MR技术在用于实时、连续的雪深变化监测方面具有良好的潜力和可行性。  相似文献   

7.
基于GPS和北斗信噪比观测值的雪深反演及其误差分析   总被引:1,自引:0,他引:1  
利用GNSS反射信号反演雪深具有全天时、全天候、数据量大、成本低等突出优点。本文围绕基于信噪比观测值的雪深反演方法,利用参加中国北极科学考察的机会在黄河站设计了GNSS-R试验,采集了GPS和北斗的双频信噪比观测数据,详细讨论了高度角范围、弧段长度、卫星数量、方位角、时间尺度、星座结构、信号频率、信噪比强度等多种因素对雪深反演结果的影响。通过大样本、质量控制、误差分析等手段,雪深反演精度和可靠性得到有效提高。根据误差分析的结果,本文推荐的反演策略如下:选择高度角范围为5°~25°、信噪比强度较高的L1和B1I观测值,充分利用多颗卫星和4个方位角的大量观测数据,在一天的时间尺度上,可以实现5 cm的反演精度。另外,弧段长度、星座结构、信号频率等对反演结果的精度影响较小。  相似文献   

8.
GPS-R技术辅助的土壤水含量变化监测   总被引:1,自引:0,他引:1  
针对传统地表土壤含水量测量方法时空分辨率小等不足,研究一种基于GPS卫星信号的矿区地表土壤水含量反演算法。针对傅里叶变换难以处理非均匀时序数据,设计了一种Lomb Scargle算法分析GPS信噪比特性。直接分离其中的直射信号和反射信号,提取多路径反射信号并分析其时频特征。通过与实测数据对比,分析反演土壤含水率的可行性。结果表明:反射信号频谱特征与实际数据具有较强的相关性。该方法为高时空分辨率监测地表土壤含水率提供了一种新的思路。  相似文献   

9.
针对地表物体反射信号引起的多路径效应是影响GNSS定位精度的重要误差源的问题,该文采用GNSS静态观测数据中的信噪比反演水面高度的方法,对水面高度进行反演,从而实现对水面高度变化的实时监测。为了验证水位反演的精度,利用平静湖面及海面上的GNSS静态观测数据,提取卫星高度角0~30°区间的卫星信噪比。采用二阶多项式拟合的方法去除趋势项,并利用Lomb-Scargle方法进行频谱分析,获取反射信号频率,从而反演天线相位中心到水面的垂直距离,进而确定GNSS-R技术反演水面高的能力。实验结果表明:GNSS-R技术在平静水面上的反演精度为厘米级,在海面上为分米级。因此,利用GNSS反射信号中的信噪比可以实现对水面高度的实时监测。  相似文献   

10.
利用全球定位系统反射信号干涉测量(GPS-IR)反演雪深成为近年来研究的热点领域。在此基础上,针对卫星反射信号分离这一问题,该文提出一种基于小波分解重构的卫星反射信号提取模型。利用coif5小波变换分解6层信噪比数据重构低频分量获取卫星反射信号,并对其反演精度和稳定性进行判别分析。结果表明:该方法克服了低阶多项式拟合分离卫星反射信号存在的局限性;算法简单实用,具有较强的抗干扰能力,分解得到的卫星反射信号较好;均方根误差和平均绝对误差分别降低了34%和27%;单颗卫星线性回归模型平均相关系数达到0.737,相比传统方法提高40%。  相似文献   

11.
积雪是全球水循环中的重要组成部分,积雪深度与雪水当量的精确监测对全球气候变化研究极其重要。随着GNSS研究与应用的不断深入,基于多路径效应的GNSS-MR(GNSS multipath reflectometry)技术用于地表环境监测(植被、土壤湿度、雪深、海平面等)已成为一种新兴的遥感手段。分析了SNR(signal-to-noise ratio)信噪比值的变化特性,详细给出了基于SNR观测值的GNSS-MR技术探测雪深的基本原理及其计算流程图。为了验证算法的有效性,利用科罗拉多州17 d连续跟踪站NWOT的GPS数据反演了降雪厚度,其结果与实测的雪深记录数据吻合较好,误差均值为0.07 m。初步研究结果验证了GNSS-MR技术用于积雪深度探测的可行性,并为后续充分利用现有的全球密集GNSS跟踪站数据开展地表环境监测提供重要参考。  相似文献   

12.
Multipath in global positioning system (GPS) is the interference of the microwave signals directly from satellites and those reflected before reaching the antenna, typically by the ground. Because reflected signals cause positioning errors, GPS antennas are designed to reduce such interference. Recent studies show that multipath could be utilized to infer the properties of the ground around the antenna. Here, we report one such application, i.e. a fixed GPS station used as a snow depth meter. Because the satellite moves in the sky, the excess path length of reflected waves changes at rates dependent on the antenna height. This causes quasi-periodic variations of the amplitude and phase of the received signals. Accumulation of snow reduces effective antenna heights, and we can see it by analyzing multipath signatures. Signal-to-noise ratios (SNR) are often used to analyze multipath, but they are not always available in raw GPS data files. Here, we demonstrate that the geometry-free linear combination (L4), normally used to study the ionosphere, can also be used to analyze multipath signatures. We obtained snow depth time series at a GPS station in Hokkaido, Japan, from January to April in 2009 using L4 and SNR. Then, we compared their precisions. We also discuss mechanisms responsible for the possible underestimation of the snow depth by GPS. Finally, we investigate the possibility of inferring physical conditions of the snow surface using amplitudes of multipath signatures.  相似文献   

13.
GPS snow sensing: results from the EarthScope Plate Boundary Observatory   总被引:5,自引:2,他引:3  
Accurate measurements of snowpack are needed both by scientists to model climate and by water supply managers to predict/mitigate drought and flood conditions. Existing in situ snow sensors/networks lack the necessary spatial and temporal sensitivity. Satellite measurements currently assess snow cover rather than snow depth. Existing GPS networks are a potential source of new snow data for climate scientists and water managers which complements existing snow sensors. Geodetic-quality GPS networks often provide signal-to-noise ratio data that are sensitive to snow depth at scales of ~1,000 m2, a much larger area than for other in situ sensors. However, snow depth can only be estimated at GPS sites when the modulation frequency of multipath signals can be resolved. We use data from the EarthScope Plate Boundary Observatory to examine the potential for snow sensing in GPS networks. Examples are shown for successful and unsuccessful snow retrieval sites. In particular, GPS sites in forested regions typically cannot be used for snow sensing. Multiple-year time series of snow depth are estimated from GPS sites in the Rocky Mountains. Peak snow depths ranged from 0.4 to 1.2 m. Comparisons with independent sensors show strong correlations between the GPS snow depth estimates and the timing of snowstorms in the region.  相似文献   

14.
Multipath is detrimental for both GPS positioning and timing applications. However, the benefits of GPS multipath for reflectometry have become increasingly clear for soil moisture, snow depth, and vegetation growth monitoring. Most multipath forward models focus on the code modulation, adopting arbitrary values for the reflection power, phase, and delay, or they calculate the reflection delay based on a given geometry and keep reflection power empirically defined. Here, a fully polarimetric forward model is presented, accounting for right- and left-handed circularly polarized components of the GPS broadcast signal and of the antenna and surface responses as well. Starting from the fundamental direct and reflected voltages, we have defined the interferometric and error voltages, which are of more interest in reflectometry and positioning applications. We examined the effect of varying coherence on signal-to-noise ratio, carrier phase, and code pseudorange observables. The main features of the forward model are subsequently illustrated as they relate to the broadcast signal, reflector height, random surface roughness, surface material, antenna pattern, and antenna orientation. We demonstrated how the antenna orientation—upright, tipped, or upside-down—involves a number of trade-offs regarding the neglect of the antenna gain pattern, the minimization of CDMA self-interference, and the maximization of the number of satellites visible. The forward model was also used to understand the multipath signature in GPS positioning applications. For example, we have shown how geodetic GPS antennas offer little impediment for the intake of near-grazing reflections off natural surfaces, in contrast to off metal, because of the lack of diversity with respect to the direct signal—small interferometric delay and Doppler, same sense of polarization, and similar direction of arrival.  相似文献   

15.
An open source GPS multipath simulator in Matlab/Octave   总被引:2,自引:1,他引:1  
Multipath is detrimental for both GPS positioning and timing applications. However, the benefits of GPS multipath for reflectometry have become increasingly clear for monitoring soil moisture, snow depth, and vegetation growth. In positioning applications, a simulator can support multipath mitigation efforts in terms of, e.g., site selection, antenna design, receiver performance assessment, and in relating different observations to a common parameterization. For reflectometry, in order to convert observed multipath parameters into useable environmental products, it is important to be able to explicitly link the GPS observables to known characteristics of the GPS receiver/antenna and the reflecting environment. Existing GPS multipath software simulators are generally not readily available for the general scientific community to use and/or modify. Here, a simulator has been implemented in Matlab/Octave and is made available as open source code. It can produce signal-to-noise ratio, carrier phase, and code pseudorange observables, based on L1 and L2 carrier frequencies and C/A, P(Y), and L2C modulations. It couples different surface and antenna types with due consideration for polarization and coherence. In addition to offering predefined material types (water, concrete, soil, etc.), it allows certain dimensional properties to be varied, such as soil moisture and snow density.  相似文献   

16.
GPS信噪比观测值的土壤湿度变化趋势反演   总被引:1,自引:0,他引:1  
土壤湿度变化趋势是某一个位置或区域内水资源循环的重要指标.多路径误差作为一种在导航、定位中的重要测量误差,由于其较弱的空间相关性,难以采用全球甚至区域性模型或差分的方法予以消除.在讨论和研究了多路径误差反射模型的基础上,实现了利用 GPS信噪比 SNR(Signal - to - NoiseRatio)观测值中的多路径反射分量对土壤湿度变化趋势的模拟.结合实测 GPS数据和土壤湿度计观测数据的对比和分析表明,该方法能反映土壤湿度变化趋势.同时,在计算过程中如何选择合适卫星、对反演结果质量进行评价以及如何实现两种观测结果之间的同化等是进一步需要研究的问题.  相似文献   

17.
Due to a satellite internal reflection at the L5 test payload, the SVN49 (PRN1) GPS satellite exhibits a static multipath on the L1 and L2 signals, which results in elevation-dependent tracking errors for terrestrial receivers. Using a 30-m high-gain antenna, code and carrier phase measurements as well as raw in-phase and quadrature radio frequency samples have been collected during a series of zenith passes in mid-April 2010 to characterize the SVN49 multipath and its impact on common users. Following an analysis of the receiver tracking data and the IQ constellation provided in Part 1 of this study, the present Part 2 provides an in-depth investigation into chip shapes for the L1 and L2 signals. A single reflection model is found to be compatible with the observed chip shape distortions and key parameters for an elevation dependent multipath model are derived. A good agreement is found between multipath parameters derived independently from raw IQ-samples and measurements of a so-called Vision Correlator. The chip shapes and their observed variation with elevation can be used to predict the multipath response of different correlator types within a tracking receiver. The multipath model itself is suitable for implementation in a signal simulator and thus enables laboratory testing of actual receiver hardware.  相似文献   

18.
小波变换与滑动窗口相结合的GNSS-IR雪深估测模型   总被引:1,自引:0,他引:1  
边少锋  周威  刘立龙  李厚朴  刘备 《测绘学报》1957,49(9):1179-1188
GNSS干涉反射技术(GNSS interferometric reflectometry)是一种新型的地表雪深监测方式。针对当前信号分离不佳和随机估测偏差的问题,提出联合小波变换和滑动窗口构建一种多卫星融合的GNSS-IR雪深估测精化模型。该模型采用离散小波变换代替常用的多项式方法,获取高质量的信噪比序列。通过利用阈值约束下的滑动窗口筛选多卫星有效反射高度,并进行等权平均。以PBO H2O和SNOTEL的雪深数据为参考值,利用2016—2017年雪季的GNSS观测数据建立模型并验证精度。结果表明:①GNSS-IR精化模型估测结果与实测数据在整体趋势上保持高一致性;②与单颗卫星结果相比,多卫星融合估测结果在精度和稳定性方面明显改善,其均方根误差(RMSE)为10 cm,相较于PBO H2O减少了近50%。此外,考虑到地表粗糙度作为一种误差影响因素,采用新的反射高度基准修正的雪深估测相对RMSE误差约4 cm,同时估测值与实际值的相关系数达到0.98。  相似文献   

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