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...     

First spaceborne demonstration of BeiDou-3 signals for GNSS reflectometry from CYGNSS constellation

The full constellation of Chinese Global Navigation Satellite System (GNSS) BeiDou-3 has been deployed completely and started fully operational service. In addition to providing global Positioning, Navigation and Timing (PNT) services, the BeiDou-3 satellites transmissions can also be used as the sources of illumination for Earth Observation (EO) with a bistatic radar configuration. This innovative EO concept, known as GNSS reflectometry (GNSS-R), allows to measure the Earth surface characteristics at high resolution via the reflected L-band radar signals collected by a constellation of small, low cost and low Earth orbiting satellites. For the first time in orbit, earth reflected BeiDou-3 signal has been detected from the limited sets of raw data collected by the NASA’s Cyclone GNSS (CYGNSS) constellation. The feasibility of spaceborne BeiDou-3 reflections on two typical applications, including sea surface wind and flooding inundation detection, has been demonstrated. The methodology and results give new strength to the prospect of new spaceborne GNSS-R instruments and missions, which can make multi-GNSS reflectometry observations available to better capture rapidly changing weather systems at better spatio-temporal scales.     

Improved specular point prediction precision using gradient descent algorithm

Global Navigation Satellite Systems Reflectometry (GNSS-R) utilizes GNSS signals reflected off the Earth surface for remote sensing applications. Due to weak power of reflected signals, GNSS-R receiver needs to track reflected signals by open loop. The first step is to calculate the position of specular point. The specular point position error of the existing algorithm—Quasi-Spherical Earth (QSE) Approach—is about 3 km which may cause troubles in data post-processing. In this paper, gradient descent algorithm is applied to calculate position of specular point and the calculation is based on World Geodetic System 1984 (WGS 84) ellipsoid in geodetic coordinate. The benefit of this coordinate is that it is easy to investigate the effect of real surface’s altitude. Learning rate—the key parameter of the algorithm—is adaptively adjusted according to initial error, latitude and gradient descent rate. With self-adaptive learning rate strategy, the algorithm converges fast. Through simulation and test on Global Navigation Satellite System Occultation Sounder II (GNOS II), the performances of the algorithm are validated. The specular point position error of the proposed algorithm is about 10 m. The speed of the proposed algorithm is competitive compared with the existing algorithm. The test on GNOS II shows that the proposed algorithm has good real-time performance.     

低轨卫星的北斗反射信号海洋覆盖分析

北斗系统作为我国自行研制的导航系统，具有独特的混合星座特性，其反射事件在海洋上的空间分布和覆盖性能的研究成果较少。针对上述问题，模拟了北斗三号（Beidou System 3，BDS3）以及全球定位系统（Global Positioning System，GPS）空间星座，模拟不同性能参数的低轨接收卫星，在此仿真系统的基础上，计算反射事件在各仿真场景下的海洋覆盖率以及同时发生反射事件的卫星数量。结果表明：BDS3与GPS相比具有更大的反射事件海洋覆盖率，覆盖性能更优；仿真周期7天与1天相比,前者卫星产生的反射事件海洋覆盖率约为后者5倍；低轨道卫星（Low Earth Orbit,LEO）轨道高度越高，天线波束角度越大，反射事件海洋覆盖率越大；3颗LEO卫星下同时发生反射事件卫星数的平均值约为单颗LEO卫星的3倍。可通过设计多星组网来提高反射事件海洋覆盖率。研究结果对星载反射技术海洋遥感应用方面有一定的参考价值。     

一种星载GNSS-R海面风向反演方法

针对目前海面风场反演中风向反演困难，准确性低的问题，提出一种利用深度网络反演海面风向的新方法，该方法采用星载GNSS-R信号作为遥感源，根据海面反射信号特性与风向相关关系选择反演观测量，建立海面风向反演的深度网络模型。引入ReLU函数作为网络激活函数，并基于遗传算法(GA)优化了网络模型，对输入数据进行时空匹配与归一化处理，通过机器学习建立风向与输入变量的对应关系，利用深度网络模型反演得到海面风向，该方法反演结果的均方根误差εRMSE=18.14°，满足海面风向测量精度均方误差小于20°的一般测量要求，并通过两组对比试验验证了该方法的有效性和鲁棒性。     

GNSS-Reflectometry: Forest canopies polarization scattering properties and modeling

Nowadays, GNSS-Reflectometry (GNSS-R) can be a new promising remote sensing tool in the ocean, snow/ice and land surfaces, e.g., vegetation biomass monitoring. Although GNSS-R provides a potentially special L-band multi-angular and multi-polarization measurement, the theoretical vegetation scattering properties and mechanisms for GNSS-R are not understood clearly. In this paper, the GNSS-R vegetation polarization scattering properties are studied and modeled at different incidence angles (specular direction). The bistatic scattering model Bi-mimics is employed, which is the first-order radiative transfer equation. As a kind of forest stand, the Aspen’s crown layer is composed of entire leaves, and its parameters in Mimics handbook are used as model input. The specular circular polarizations (co-polarization RR and cross-polarization LR) are simulated. For cross-polarization, the received polarization is assumed as a linear (horizontal and vertical) polarizations and ±45° linear polarizations. Therefore, the HR VR, +45R and −45R polarizations are simulated here. Contributions from different scattering components at RR, LR and VR polarization are also presented. For co-polarization, it is large in the whole specular angles (10–80°). The scattering trends of the other cross polarization (HR, LR, +45R and −45R) are a little similar when compared to the RR and RV. Therefore, the RHCP and V polarizations are more favorable to collect the reflected signals. The trunk heights and crown depths do not affect the scattering trends of RR, RV and RL, while the trunk height has some effect on the scattering amplitude of different polarizations. The azimuth angle has more effects on RR, RL and RV scattering, especially in lower than 50°. The observation angles and polarization combinations are extremely important for GNSS-R remote sensing.     

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.     

SVRM辅助的北斗GEO卫星反射信号土壤湿度反演方法

提出了一种支持向量回归机(SVRM)辅助的北斗地球静止轨道(GEO)卫星反射信号土壤湿度反演方法。使用全球导航卫星系统反射信号(GNSS-R)右旋圆极化(RHCP)天线和左旋圆极化(LHCP)天线接收体制进行了地基实验,采集了北斗GEO卫星直射、反射信号原始数据,并从中提取直射、反射信号的相关功率,结合北斗GEO卫星的高度角与方位角信息作为输入,烘干称重法获取的土壤湿度作为输出对使用径向基(RBF)核函数的ε-SVRM进行了训练。独立测试集上的结果表明,SVRM辅助的北斗GEO卫星反射信号土壤湿度反演方法获取的土壤湿度结果与烘干称重法获取的土壤湿度参考值误差控制在3%以内,线性回归方程决定系数为0.897 9,均方根误差RMSE为1.492 6%,证明了该方法具有良好的泛化特性,实际应用中效果良好。