CFOSAT散射计几何定位验证与精度初步评估

采用STK软件对中法海洋卫星（CFOSAT）散射计几何定位算法进行了验证。针对CFOSAT散射计扇形波束扫描观测体制,分别就扇形波束扫描散射计几何定位原型算法、包含天线安装误差的完整几何定位算法利用STK进行了详细验证。结果表明了CFOSAT扇形波束散射计几何定位算法的准确性,与STK几何定位结果偏差在100 m以内。在此基础上,结合有源定标器实验数据,对CFOSAT实际观测数据几何定位参数进行了校正,给出了CFOSAT散射计几何定位精度的初步评估。     

基于星载宽刈幅散射计的海面舰船目标检测方法与识别

针对全球海面舰船目标检测的需求,结合宽刈幅与方位高分辨的需求,提出了一种基于星载宽刈幅散射计的海面舰船目标检测方法.该方法使用扇形波束旋转扫描散射计,发射宽带线性调频信号,对回波信号进行方位高分辨,海面目标二维检测,得到舰船的多次观测信息.使用方位角、多普勒频率、高分辨距离像等观测数据,计算船长、船速、与卫星运动方向夹...     

一种适用于WindSat的地理定位方法

星载全极化微波辐射计WindSat为海面风场的被动微波遥感提供了有效的手段。WindSat亮温需要经过地理定位才能形成包含目标位置信息的有效物理量。地理定位是辐射计数据预处理的重要环节。针对WindSat圆锥扫描方式,将Patt94定位算法进行修改,应用于WindSat地理定位中。详述了定位的计算过程,给出了定位结果,讨论了误差分析方法。通过模拟WindSat轨道,对可能的定位误差来源展开分析,着重分析了辐射计姿态误差、扫描方位误差对定位的影响。最后,就辐射计姿态校正进行了讨论。     

修正安装矩阵提高FY-3B/MERSI的地理定位精度

遥感数据的地理定位精度是影响其定量化应用的重要因素,为了提高FY-3B中分辨率光谱成像仪(MERSI)L1级数据的定位精度,分析了地理定位算法模型中安装矩阵与实际定位偏差之间的关系,通过修正风云三号卫星地面应用系统预处理模块中参数——安装矩阵,提高了地理定位精度。当仪器坐标系分别绕X轴、Y轴和Z轴旋转一个小角度后,遥感图像的定位结果会分别产生左右平移、前后平移和旋转变形。分析并建立旋转角度与变形之间的数量关系,根据海陆掩码与遥感图像的偏差程度估算安装矩阵的误差。修正安装矩阵后,计算出的定位结果准确性得到明显提高,精度达到1个像元左右。通过一段时间的业务系统测试,地理定位结果的质量稳定可靠。     

星载微波散射计的在轨定标技术现状及展望

星载微波散射计通过测量海面不同方位向的后向散射系数反演出海面的风速和风向,为了满足测量精度要求,必须对其进行在轨定标.本文总结了现有微波散射计的在轨定标技术,包括有源定标器法、陆地自然目标法、海洋目标法和星星交叉定标法;然后分析了每种定标方法的优缺点;最后,描述了现有定标方法适用扇形波束体制散射计和笔形波束圆锥扫描体制散射计的特性.     

中法海洋卫星散射计噪声分析及自适应估计

针对星载扇形波束扫描散射计数据预处理中噪声能量估计问题,对中法海洋卫星(China-France oceanography satellite,CFOSAT)微波散射计数据稳定性及其对噪声能量估计的影响进行了分析,基于内部噪声信号和内定标信号构建了噪声能量估计的二元多项式模型,实现了散射计噪声能量的自适应估计.微波散射...     

基于星载旋转扫描雷达的高分辨率实现

为了提高传统星载真实孔径雷达(微波散射计)空间分辨率、满足地球物理参数(雪水当量、冰雪冻融等)的观测需求,开展了扫描体制散射计的高分辨率分析和研究。基于距离向脉冲压缩处理和方位向多普勒处理技术,提出了一种旋转扫描体制下的分辨率提高方法。针对笔形波束圆锥扫描散射计的观测方位角在天线扫描过程中不断变化的特点,在正侧视和斜侧视时对模型分别进行了仿真验证。验证表明利用散射计旋转扫描多普勒信息能够建立与方位向分辨率的关系,可以有效提高微波散射计的空间分辨率。当正侧视时,方位向分辨率可以达到2km,斜前视或者斜后视时,方位向分辨率能够达到2~5km。针对雪水当量模型数据进行分析验证,设计的系统传递误差Kpc在5km分辨率下可以达到0.3,在2km分辨率下达到0.3~0.5。     

风云三号微波湿度计遥感图像地理定位方法

风云三号（FY-3）微波湿度计采用45°天线绕轴旋转形成垂直于卫星飞行轨迹的360°连续变速圆周扫描方式。依据这种扫描几何,给出了适用于风云三号微波湿度计遥感图像地理定位的方法,定义了完善的坐标系及坐标系转换关系,根据微波湿度计观测几何、卫星空间位置和姿态、仪器空间位置和指向建立了天线观测矢量与地面位置之间关系的模型。风云三号微波湿度计遥感图像地理定位方法在风云三号地面应用系统业务运行中,对微波湿度计遥感图像地理定位精度达到了像元级。     

一种北斗无高程RDSS定位模型及其误差分析

北斗卫星导航系统RDSS(Radio Determination Satellite Service)导航体制中的定位报告服务由于允许用户向外界通报自己的位置,在水利、海事、海洋渔业、森林防火、搜索救灾等领域得到了广泛应用。北斗RDSS定位需要高精度高程数据的支持,对于偏远地区或中国境外地区将难以获得高精度高程数据。设计一种无需高程库的RDSS定位模型,当用户观测RDSS卫星个数超过2个时,利用多余的观测卫星代替高程进行定位,并对该模型下的定位误差进行了分析。模拟实验表明,无高程RDSS定位的DOP值较大,定位误差较大;相同伪距误差下,定位误差随用户位置纬度增加而指数增加;定位结果中的经度误差远小于纬度和高程的误差。     

LEO卫星TDOA/DOA定位性能分析

随着以“星链”卫星为代表的低轨（LEO）互联网卫星系统的快速发展,星载相控阵列天线的应用数量飞速增长,未来LEO互联网卫星便于提供星载电磁波到达方向（DOA）检测能力。卫星覆盖区内的非法干扰进行定位排查,是未来互联网卫星系统正常运维的重要保障。目前常用的双星到达时差（TDOA）/到达频差（FDOA）定位体制存在定位误差显著增大的“定位盲区”造成盲区内的干扰源无法定位的问题,提出了一种基于加权最小二乘约束优化模型的TDOA/DOA双星干扰源定位技术体制。分析了几何稀释精度因子（GDOP）的定位误差,仿真实验表明该定位方法具有不存在“定位盲区”的优点,在经纬度张角为4°×4°的波束范围内定位误差小于0.2 km,定位误差的地理平均为0.112 km,满足非法干扰定位排查的应用需求。通过定位解算的根均方差（RMSE）的蒙特卡洛方法,验证了GDOP误差精度。该定位方法的定位误差地理稳定性优于目前常规的双星TDOA/FDOA定位算法。     

Fusion of sea surface wind vector data acquired by multi-source active and passive sensors in China sea

This work is the first to analyse the sea surface wind vector (SSWV) data acquisition capabilities of eight satellites carrying microwave scatterometer (scanning scatterometer carried by Haiyang satellite 2A, advanced scatterometer carried by Metop satellite A, advanced scatterometer carried by Metop satellite B and scanning scatterometer carried by Oceansat satellite 2) or radiometers (Special Sensor Microwave Imager carried by Meteorological Satellite Program satellites F15 and F17, advanced microwave scanning radiometer 2 carried by GCOM-W1 satellite, and windsat polarimetric radiometer carried by Coriolis satellite) and investigate a SSWV fusion algorithm for active and passive remote-sensing data. We found that combining observations of the eight satellites can provide an SSWV data product with spatial resolution of 25 km × 25 km and temporal resolution of 3 h. Sea surface wind speed and direction data were obtained from multi-source active and passive sensors using a spatiotemporally weighted fusion algorithm. An adaptive sliding window was introduced for calculating effective observation data within spatial/temporal radii, which can effectively improve calculation efficiency for wind field fusion. Comparing the fused and buoy observation results, the root-mean-square errors of the wind direction and speed were 20.6° and 1.2 m s^–1, respectively, indicating that the fusion results can meet most application requirements for wind vector. Meanwhile, the space coverage, accuracy of merged wind speed and wind direction can be improved comparing to a single sensor.     

A comparison of ship- and scatterometer-derived wind speed data in open ocean and coastal areas

Quality controlled wind speed observations from merchant ships have been compared with ERS-1 scatterometer data. The ship and satellite wind speed pairs were well correlated at 120 km separation in the open ocean, reducing to 40 km in the North Sea. The maximum allowed separation of ship and scatterometer wind speed pairs had to be further reduced to 20 km in the North Sea to avoid matching of coastal ship wind speed data with scatterometer data from more exposed regions. Spurious biases in the comparisons were caused by the error variability of the scatterometer data (0.5 m s-1) being significantly less than that for the ships (2.0 m s-1). The unbiased regression was: U10n(ship)=1.025 U10n(satellite)+0.255 No significant enhancement of the scatterometer wind speeds occurred in the coastal region.     

降雨影响散射计测风的初步研究

给出了降雨影响C、Ku波段微波散射计测量海面风速的初步结果。研究结果显示,海面风速为25～30 m/s时,雨速为15 mm/hr的降雨会使这两个波段的微波散射计测量的风速偏低10 m/s。
     

ERS-1 surface wind observations over a cyclone system in the Bay of Bengal during November 1992

The Bangladesh cyclone of 15–22 November 1992 was observed by the scatterometer onboard the ERS-1 satellite. The unique data set from this scatterometer (which is the first of its kind over an Indian Ocean cyclone) has been analysed in order to study various features of the cyclone. A new technique to estimate the centre of the cyclone objectively from the observed winds has been proposed. Based on the precise knowledge of the centre, the directional ambiguity of the wind data has been removed.     

The Study on Oceanic Vector Wind Field Retrieve Technique based on Neural Networks of Microwave Scatterometer

The neural networks are used to retrieve wind fields for microwave scatterometer data,especially for data gained by the scatterometer onboard HY\|2A satellite (HSCAT)under high wind speed conditions.The retrieval of wind speed is based on Back Propagation (BP)neural network,while multiple solutions of wind direction inversion is realized by Mixture Density Network (MDN)neural network.During the process,Gaussian kernel function is employed.The wind field used in network training is from corresponding European Centre for Medium\|range Weather Foresting (ECMWF).It is proved that wind fields retrieved in this paper could get results meeting the accuracy requirement for HSCAT by comparison with ECMWF wind fields.Results are also compared with the L2B wind field products distributed by the National Satellite Oceanic Application Service,it is shown that the method in this paper gave results with closer values than L2B products.     

TG-2多角度偏振成像仪遥感影像地理定位与误差订正

搭载多个遥感应用载荷的天宫二号空间实验室(TG-2)于2016年9月发射,其中多角度偏振成像仪共设置12个观测通道(565~910 nm),是国内首个应用于空间探测的多角度偏振仪器。该仪器的数据质量对气溶胶和云的光学、微物理特性参数的精确反演至关重要,而高精度的影像地理定位是观测数据得以定量应用的基础。根据多角度偏振成像仪光学几何设计参数和航天器的姿态信息,基于参数法建立了影像观测像元与地面空间位置之间的关系模型。首先分析地球自转和航天器姿态偏差对像移造成的影响,进行相应的偏流角和安装矩阵初步订正,接着采用海岸线拐点法探测初步订正结果在沿轨和交轨方向的误差,并使用焦点纠正法直接在焦平面坐标系中补偿了两个方向上的地理定位误差。最终的定位误差评估表明,沿轨和交轨方向的平均误差保持在一个像元以内。     

TG-2 Multi-angle Polarization Imager Remote Sensing Image Geolocation and Error Correction

The Tiangong-2 Space Laboratory(TG-2), equipped with multiple remote sensing application payloads, was launched in September 2016. The multi-angle polarization imager has 12 observation channels (565nm to 910 nm), which is the first multi-angle polarization instrument used in space exploration in China. The data quality of the instrument is crucial for the precise inversion of the optical and microphysical characteristic parameters of aerosol and cloud, and accurate image geolocation is the basis for the quantitative application of observational data. This paper is based on the multi-angle polarization design parameters of optical geometry, spacecraft attitude information, and the relation model between the image observation pixel and the ground space location is established by using parametric approaches. Firstly, the impact of both the earth's rotation and spacecraft attitude deviation on image motion is analyzed, and the preliminary correction of the corresponding drift angle and the mounting matrix is carried out, Then, the coastline inflection point method is used to detect the error of the initial correction result in the direction along-track and cross-track, and the focus correction method is used to directly compensate the geolocation error in two directions in the focal plane coordinate system. The final geolocation errors assessment shows that the mean error in both along and cross-track directions is within one pixel.