星载GNSS海洋反射信号建模与仿真

星载GNSS反射信号建模与仿真对GNSS反射信号正逆问题的研究及接收机算法和性能的评估非常重要。从几何、信号和信息的角度建立了星载GNSS反射信号分层建模方法。详细论述了星载GNSS反射信号的双基几何关系,建立了海风、涌浪和降雨驱动的线性组合海浪谱,并基于此计算了GNSS反射信号双基散射系数,基于各散射单元独立散射的假设推导了反射信号模型,通过仿真产生了星载GNSS反射信号及时延-多普勒相关功率,并与UK TDS-1卫星实测相关功率进行了对比分析。结果显示,通过先产生反射信号后处理得到的相关功率和直接端对端产生的相关功率与UK TDS-1卫星实测的相关功率的余弦相似度分别为0.97和0.94,所提架构和方法可正确对星载GNSS反射信号进行建模和仿真。同时,通过所建平台分析了涌浪和降雨形成的海浪谱对星载GNSS反射信号的影响。结果发现,涌浪主要影响低风速探测而对高风速无影响,降雨对星载GNSS反射信号无明显影响。      

基于TechDemoSat-1卫星的GPS反射信号海面高度反演

针对星载GPS反射信号（GPS-R）海面测高的误差问题，基于星载GPS-R实测数据进行星载海面测高模型和误差修正模型的研究，并验证其有效性。利用TechDemoSat-1（TDS-1）数据，使用时延多普勒图（DDM）海面高度反演技术，着重分析了星载GPS-R海面高度反演中的各类误差，并建立了相应的误差模型。对星载GPS-R海面高度反演模型进行优化，采用DTU15全球平均海面模型、DTU全球海潮模型验证反演精度。结果证明:优化后反演模型得到的全球海面高度反演结果的平均绝对误差（MAD）为6.05 m，精度提高了约29%，有效提高了海面高度反演的精度。研究成果对于推广星载GNSS反射信号（GNSS-R）的海面测高应用具有一定的意义。      

机载GNSS海洋反射信号的建模与仿真

由于全球导航卫星系统反射(GNSS-R)机载试验耗费大和重复性差,需研制GNSS-R信号模拟器,但没有相应的反射信号模型。提出了一种基于数据拟合的机载GNSS海洋反射信号建模方法。首先,对复杂的GNSS海面反射信号进行近似简化。然后利用ZV模型生成的时延相关功率曲线,通过最小二乘拟合和非线性拟合,建立了多条等时延间隔的海洋反射信号功率衰减模型,从而得到机载GNSS海洋反射信号的时延、功率、多普勒频率参数。最后,对多条反射信号的合路信号进行相关的仿真验证。验证的结果表明模拟的14条反射信号的相关功率曲线与ZV模型理论曲线的相关系数优于0.99,能够有效地用于GNSS海洋反射信号的生成。该方法可根据海面风场、浪高、波高等海面信息,模拟不同海况的海洋反射信号,为GNSS-R信号模拟器的研制奠定基础。     

基于双基雷达原理的GNSS海面反射信号建模方法

全球导航卫星系统反射(GNSS-R)技术应用过程中接收机的测试验证需要反射信号产生源,以降低成本。信号的模型是GNSS-R信号产生源中的核心。针对缺乏相应模型的问题,提出了一种根据双基雷达原理建立GNSS海面反射信号模型的方法。首先,在分析GNSS海面反射信号特征的基础上,选取了恰当的海面反射点。然后,计算了雷达方程中的散射系数和散射面积,从而得到相应反射点的反射信号功率。最后,对所求得的反射信号参数进行仿真验证。验证的结果表明,反射信号的相关功率曲线与ZV模型理论曲线的相关系数优于0.98,能够有效地用于GNSS海面反射信号的生成。因此,该方法可为GNSS-R信号产生源的研制提供一定的理论支撑。     

基于半无码的P(Y)码自相关GNSS-R海面测高方法

针对传统GPS C/A码延迟测高方法测高精度低和互相关测高方法时延波形信噪比低的问题,研究了基于半无码的P（Y）码自相关海面测高方法。首先,通过理论测高精度模型,对比分析了C/A码和P（Y）码的测高精度;然后,描述了L1、L2双频反射信号基于半无码的P（Y）码自相关处理架构,并论述了测高模型和L1、L2双频电离层时延误差修正方法;最后,利用模拟的L1、L2反射信号对比分析了基于半无码的P（Y）码自相关、C/A码自相关以及信号互相关方法的海面测高精度。结果表明:相比于C/A码自相关和信号互相关测高精度,基于半无码的P（Y）码自相关的测高精度分别提高了3.97倍和1.47倍。      

主动雷达导引头多路径效应的数字仿真

对于平整和起伏的地面或海面,分别给出了一种基于多反射点复杂目标的多路径回波的时域复包络波形数字仿真模型.采用随机分形插值算法利用地形实测数据对复杂的起伏地面和海面进行三维地形建模.对不同粗糙度地面上的低空目标的多路径回波进行了仿真计算,并使用主动雷达导引头数字仿真模型进行了多路径干扰环境下对低空目标的跟踪实验.仿真实验表明,多路径效应对雷达跟踪低空目标会产生较大的误差.     

基于树模型机器学习方法的GNSS-R海面风速反演

GNSS-R是基于GNSS卫星反射信号的一种新技术.GNSS-R技术可以运用到海面风场反演中，传统的GNSS-R技术反演海面风场主要有波形匹配和经验函数两种方法，风速反演精度约为2m·s-1.波形匹配方法耗时多，计算量大；经验函数方法通常只使用少量物理观测量，会造成信息浪费，损失一定的反演精度.为了提高海面风速的反演精度，引入机器学习领域常用的树模型算法决策树、随机森林、GBDT等对海面风速进行预测.利用GNSS-R与ECMWF数据构成训练集和验证集，训练集用于模型学习，验证集用于检验模型的反演效果.实验结果显示，决策树和随机森林预测误差约为0.6m·s-1，GBDT等算法的预测误差约为2m·s-1，满足风速反演要求.与GNSS-R传统反演方法相比，机器学习树模型算法效果更好，在验证集上表现稳定且误差较小.因此，可以将机器学习树模型算法运用到海面风速反演中.      

GNSS极化测量降雨正演模拟与实验对比

研究证明，全球导航卫星系统（GNSS）极化无线电掩星（PRO）技术可以用于探测降雨。利用GPM DPR降雨率数据与PAZ卫星极化相移观测数据匹配，筛选出代表性降雨事件。通过选用TB等7种雨滴形状和MP等5种雨滴谱模型，采用T矩阵法对各事件进行正演，并分析PAZ极化相移的线性校正值、天线相位校正值与正演模拟值之间的关系。对比分析得出线性校正值、相位校正值与模拟值的相关系数分别为0.9994和0.9933，均方根差分别为0.3429和1.2765。模拟值与实测值之间高度相关，且更接近线性校正值。进一步的研究表明，模拟降雨率在1 mm·h–1以下的事件时，雨滴谱采用MP或JD分布，雨滴形状采用SC或PB的模拟精度更高；降雨率在1 mm·h–1以上的事件，雨滴谱采用MP或 SS分布，雨滴形状采用TB的模拟结果最优。      

星载GNSS-R海面风场观测载荷关键技术设计与验证

目前海面风场观测手段有限,基于全球导航卫星系统反射信号处理(global navigation satellite system reflection,GNSS-R)的天基观测为全球风场信息获取提供了全新的手段.GNSS-R海面风速探测技术具有全天时、全天候、低功耗、宽覆盖、多信号源、低成本等特点,日益获得了广泛的关注...     

Deformation monitoring using GNSS-R technology

GNSS reflectometry (GNSS-R) has been widely studied in recent years for various applications, such as soil moisture monitoring, biomass analysis, and sea state monitoring. This paper presents the concept of a novel application of using GNSS-R technology for deformation monitoring. Instead of installing GNSS on the deformation body to sense the movement, GNSS-R deformation monitoring system estimates the deformation from receiving GNSS signal reflected by the deformation body remotely. A prototype of GNSS-R deformation monitoring system has been developed based on GNSS software receiver technology. A 3D geometrical model of GNSS signal reflection has been used to reveal the relationship between the change of carrier phase difference and deformation. After compensating the propagation path delay changes caused by satellite movement, the changes in the remaining carrier phase difference are linked to the deformation. Field tests have been carried using the GNSS-R system developed and the results show sub-centimeter level deformation can be observed with the new technology. Unlike other GNSS deformation monitoring methods, GNSS-R receivers are not installed on the slope which makes this new technology more attractive.     

The impact on tsunami detection from space using GNSS-reflectometry when combining GPS with GLONASS and Galileo

The devastating Sumatra tsunami in 2004 demonstrated the need for a tsunami early warning system in the Indian Ocean. Such a system has been installed within the German-Indonesian Tsunami Early Warning System (GITEWS) project. Tsunamis are a global phenomenon and for global observations satellites are predestined. Within the GITEWS project a feasibility study on a future tsunami detection system from space has therefore been carried out. The Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way of using GNSS signals for remote sensing. It uses ocean reflected GNSS signals for sea surface altimetry. With a dedicated Low Earth Orbit (LEO) constellation of satellites equipped with GNSS-R receivers, densely spaced sea surface height measurements could be established to detect tsunamis. Some general considerations on the geometry between LEO and GNSS are made in this simulation study. It exemplary analyzes the detection performance of a GNSS-R constellation at 900 km altitude and 60° inclination angle when applied to the Sumatra tsunami as it occurred in 2004. GPS is assumed as signal source and the combination with GLONASS and Galileo signals is investigated. It can be demonstrated, that the combination of GPS and Galileo is advantageous for constellations with few satellites while the combination with GLONASS is preferable for constellations with many satellites. If all three GNSS are combined, the best detection performance can be expected for all scenarios considered. In this case an 18 satellite constellation will detect the Sumatra tsunami within 17 min with certainty, while it takes 53 min if only GPS is considered.     

基于DDMR辅助的GNSS-R载波相位差测高方法

提出了一种基于时延-多普勒映射接收机（DDMR,Delay-Doppler Map Receiver）辅助的载波相位差提取方法,给出了系统结构及信号处理方法.该方法将DDMR中所观测到的码相位差作为直射信号与反射信号的码相位延时量,将完成跟踪的直射信号扩频码进行对应的延时用于完成对反射信号的开环码跟踪.该方法省去了码相位延时搜索的过程,且可以准确地对反射信号扩频码进行同步.为了验证系统的可行性及实际性能,进行了针对水面高度测量的岸基试验并给出了试验结果.岸基试验证明采用该方法的GNSS-R（Global Navigation Satellite System Reflection）接收机可以稳定地对反射信号进行跟踪并提取直射与反射信号的载波相位差,测高精度约为2.5 cm,经过0.5 s的数据平均后精度可达0.6 cm.      

GNSS-R open-loop difference phase altimetry: Results from a bridge experiment

The paper explores a method to obtain accurate lake surface heights using measurements of the Global Navigation Satellite System (GNSS) carrier phase reflected from the lake surface. The method is referred to as Global Navigation Satellite System-Reflection (GNSS-R) open-loop difference phase altimetry method. It consists of two key technologies: one is the open-loop tracking method to track the GNSS-R signals, where the direct GNSS signal’s frequency is used as a reference frequency to obtain the carrier phases of the GNSS-R signals; the other key technology is time difference phase altimetry method to invert the lake surface heights using two or more carrier phases of GNSS-R signals received simultaneously. A validation experiment is carried out on the SANYING bridge over GUANTING lake using a GNSS-R receiver developed by the Center for Space Science and Applied Research (CSSAR), processing the data with GNSS-R open-loop difference phase altimetry method. The lake surface height results are consistent with the height results of GPS dual-frequency differential positioning altimetry. The results show that we can achieve centimeter level height in one minute average, by using 11 minutes carrier phase data of three GNSS-R signals received simultaneously.