A simplified data assimilation method for reconstructing time-series MODIS NDVI data

The Normalized Difference Vegetation Index (NDVI) is an important vegetation index, widely applied in research on global environmental and climatic change. However, noise induced by cloud contamination and atmospheric variability impedes the analysis and application of NDVI data. In this work, a simplified data assimilation method is proposed to reconstruct high-quality time-series MODIS NDVI data. We extracted 16-Day L3 Global 1 km SIN Grid NDVI data sets for western China from MODIS vegetation index (VI) products (MOD13A2) for the period 2003–2006. NDVI data in the first three years (2003–2005) were used to generate the background field of NDVI based on a simple three-point smoothing technique, which captures annual features of vegetation change. NDVI data for 2006 were used to test our method. For every time step, the quality assurance (QA) flags of the MODIS VI products were adopted to empirically determine the weight between the background field and NDVI observations. Ultimately, more reliable NDVI data can be produced. The results indicate that the newly developed method is robust and effective in reconstructing high-quality MODIS NDVI time-series.     

Estimation of cloud top height and effective cloud cover from infrared satellite soundings

The paper deals with a new method for simultaneous determination of cloud top height and effective cloud cover, using infrared radiance data of satellite-borne instruments. These cloud properties derived from the Selective Chopper Radiometer on the Nimbus 5 satellite are compared with nearly simultaneous observations by radiosondes and with satellite images. Encouraging results for Central-Europe during January, April, July, August and October 1974, as well as numerical simulations indicate that the method proposed here, would be useful also for global application. Another advantage of the described procedure are the small amount of computing time, and that no other data are required than 3 of infrared channel values, for each sounded spot.     

基于对抗和迁移学习的灾害天气卫星云图分类

针对卫星云图中的灾害天气数据存在严重不平衡问题,提出一个结合生成对抗学习（GAN）和迁移学习（TL）的卷积神经网络（CNN）框架以解决上述问题进而提高基于卫星云图的灾害天气分类精度。该框架主要包含基于GAN的数据均衡化模块和基于迁移学习的CNN分类模块。上述2个模块分别从数据和算法层面解决数据的类间不平衡问题,分别得到一个相对均衡的数据集和一个可在不同类别数据上提取相对均衡特征的分类模型,最终实现对卫星云图的分类,提高其中灾害天气的卫星云图类别分类准确率。与此同时所提方法在自建的大规模卫星云图数据上进行了测试,消融性和综合实验结果证明了所提数据均衡方法和迁移学习方法是有效的,且所提框架模型对各个灾害天气类别的分类精度都有显著提升。      

基于DTW的HJ-1B卫星地表温度产品质量检验

HJ-1B卫星热红外数据应用广泛,但其地表温度反演产品的质量检验工作尚不完善。以黑河流域为研究区,利用普适性单通道算法得到HJ 1B地表温度,基于7个地面站点（下垫面为荒漠、沙漠、植被、农作物、雪地和湿地）同步观测资料和MODIS地表温度产品（MOD11A1）,引入动态时间规整方法（DTW）对站点处HJ 1B地表温度进行验证。试验结果表明：HJ 1B地表温度反演产品与地面观测值的偏差值在沙漠和荒漠站点为1K以内,均方根误差在05K左右;对于植被和农作物站点的偏差在2K以内,均方根误差为1~2K;基于DTW的验证对时序不匹配的数据评价结果与现有指标表现一致。HJ-1B地表温度反演产品与地面站点的相对偏差均低于其与MODIS地表温度反演产品的相对偏差。     

Discriminating satellite IR anomalies associated with the MS 7.1 Yushu earthquake in China

In the process of exploring pre-earthquake thermal anomalies using satellite infrared data, Blackett et al. (2011) found that the previously reported anomalies before the 2001 Mw 7.7 Gujarat earthquake, in India, were related to positive biases caused by data gaps due to cloud cover and mosaicing of neighboring orbits of MODIS satellite data. They supposed that such effects could also be responsible for other cases. We noted a strip-shaped TIR anomaly on March 17th, 2010, 28?days before the Ms. 7.1 Yushu earthquake (Qin et al., 2011). Here we again investigate multi-year infrared satellite data in different bands to discriminate whether the anomaly is associated with the earthquake, or is only bias caused by the data gaps. From the water vapor images, we find lots of clouds that have TIR anomalies. However, on the cloudiness background, there is an obvious strip-shaped gap matching the tectonic faults almost perfectly. In particular, the animation loops of hourly water vapor images show that the cloud kept moving from west to east, while they never covered the strip-shaped gap. We consider that the cloud with this special spatial pattern should have implied the abnormal signals associated with the seismogenic process. Based on current physical models, the satellite IR anomalies both on TIR and water vapor bands can qualitatively be explained using synthetic mechanisms.     

The attitude inversion method of geostationary satellites based on unscented particle filter

The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.     

基于起爆概率的无线电引信抗箔条干扰能力的量化表征方法

针对现有量化无线电引信抗箔条干扰方法的缺少,以防空导弹引信为例,结合箔条云运动轨迹模型和概率统计手段,提出基于起爆概率的无线电引信抗箔条干扰能力的量化表征方法。首先,在对单根箔条丝的螺旋下降运动进行分析的基础上,结合6-DOF非线性差分方程迭代计算得到箔条云的运动轨迹。其次,通过拟蒙特卡罗算法推导出箔条云的动态体密度函数,以箔条云的运动模型和动态体密度函数分别计算引信在箔条云近区干扰和远区干扰2种干扰作用下的不起爆概率。基于MATLAB构建箔条云轨迹模型,详细分析后得到箔条云动态的点分布模型,在此基础上利用拟蒙特卡罗方法得到箔条云的动态体密度函数,利用八叉树算法及最小二乘曲面法得到箔条云体积。最后,根据概率定义公式计算出箔条云干扰引信起爆概率。结果表明:所提方法客观、合理,为今后设计无线电引信抗箔条云干扰算法的启动条件提供了理论依据。      

Statistical approaches to cloud classification

For the determination of clouds from satellite data there exist in general more unknown parameters than independent observations. If the bispectral observations are used from the geostationary satellites in the solar (VIS-channel) and in the infrared (IR-channel) range to derive cloud parameters, information is needed whether a pixel radiance is from a cloud free or a cloudy scene. Statistical methods are applied to derive those informations. Various proposed statistical methods are discussed.The histogram analysis developed at the University of Cologne is described in detail: bispectral (two-dimensional) histograms are partitioned into clusters. Cloud cover results are shown. A comparison is given between the results of the histogram analysis, threshold methods (VIS- and IR threshold separately and both combined) and the spatial coherence method developed by Coakly and Bretherton. The cloud cover varies in this example by a factor of two depending on the definition of the threshold between cloud free and cloudy pixels. It is further shown that after a cluster analysis of a two-dimensional histogram the derived cloud cover is not as sensitive to the threshold as for a threshold method. The methods which are discussed here are those proposed for the International Satellite Cloud Climatology Project (ISCCP). The results are from the pilot study of the ISCCP.     

Dust optical properties: A comparison between cometary and interplanetary grains

A better understanding of cometary dust optical properties has been derived from extensive observations of comet Halley, complemented by other cometary observations at large phase angles and/or in the infrared. Also, further analysis of IRAS observations and improvements in inversion techniques for zodiacal light have led to some progress in our knowledge of interplanetary dust.

Synthetic curves for phase angle dependence of intensity and polarization are presented, together with typical albedo values. The results obtained for interplanetary dust are quite reminiscent of those found for comets. However, the heterogeneity of the interplanetary dust cloud is demonstrated by the radial dependence of its local polarization and albedo; these parameters are also found to vary with inclination of the dust grains' orbits with respect to the ecliptic. Such results suggest drastic alterations with temperature in the texture of cometary dust, and would favor an important asteroidal component in the zodiacal cloud.     

Estimation of vertically integrated water vapor in Hungary using MODIS imagery

Information about the amount and spatial structure of atmospheric water vapor is essential in understanding meteorology and the Earth environment. Space-borne remote sensing offers a relatively inexpensive method to estimate atmospheric water vapor in the form of integrated water vapor (IWV). The research activity reported in the present paper is based on the data acquired by the HRPT/MODIS (High Resolution Picture Transmission, MODerate resolution Imaging Spectroradiometer) receiving station established in Budapest (Hungary) by the Space Research Group of the Eötvös Loránd University. Integrated water vapor is estimated by the remotely sensed data of the MODIS instrument with different methods and also by the operational numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF). Radiosonde data are used to evaluate the accuracy of the different IWV fields though it has been pointed out that the in situ data also suffers from uncertainties. It was found that both the MODIS and the ECMWF based fields are of good accuracy. The satellite data represent finer scale spatial structures while the ECMWF data have a relatively poor spatial resolution. The high quality IWV fields have proved to be useful for radiative transfer studies such as the atmospheric correction of other satellite data from times different than the overpass times of satellites Terra/Aqua and the forecast times of the model data. For this purpose the temporal variability of IWV is scrutinized both using ECMWF and MODIS data. Taking advantage of Terra and Aqua overpasses, the mean rate of change of IWV estimated by the near infrared method was found to be 0.47 ± 0.45 kg m⁻² h⁻¹, while it was 0.13 ± 0.65 kg m⁻² h⁻¹ based on the infrared method. The numerical weather prediction model’s analysis data estimated −0.01 ± 0.13 kg m⁻² h⁻¹ for the mean growth rate, while using forecast data it was 0.24 ± 0.18 kg m⁻² h⁻¹. MODIS data should be used when available for the estimation of the IWV in other studies. If no satellite data are available, or available data are only from one overpass, ECMWF based IWV can be used. In this case the analysis fields (or the satellite field) should be used for temporal extrapolation but the rate of change should be calculated from the forecast data due to its higher temporal resolution.     

Generalised variational assimilation of cloud-affected brightness temperature using simulated hyper-spectral atmospheric infrared sounder data

Assimilated channel brightness temperature data from infrared sounders accounting for cloud effects have a positive effect on weather forecasting, especially in weather-sensitive areas. When cloud effects are included, the channel brightness temperature deviations follow a non-Gaussian distribution. However, classical variational data assimilation follows a Gaussian distribution. When processing the cloud-affected brightness temperature, useful data are lost through the cloud detection process, thus assimilating some channel brightness temperatures with weight function peaks above the cloud top. Furthermore, strict quality control of brightness temperature removes outliers. By adopting the generalised variational assimilation method, which assumes that errors follow a non-Gaussian distribution, this paper assimilates the cloud-affected brightness temperature using simulated data for the hyper-spectral atmospheric infrared sounder (AIRS). A channel set is formed by dynamically selecting AIRS channels. The experiments for retrieving temperature and humidity data demonstrate that the generalised variational assimilated cloud-affected brightness temperature method performs better than the classical method.     

一种参数区间交叉类型的目标识别方法

针对参数区间为交叉类型的目标识别问题,提出了基于直觉模糊集和云模型的逼近理想点（TOPSIS）识别方法。构建了包含个体类和交叉类的目标数据库模型,根据云模型的多步估计算法,得到未知目标相对已知目标类的确定度,提出了确定度向隶属度和非隶属度的转化方法,基于直觉模糊熵计算特征属性的动态权重,形成了去模糊距离测度的TOPSIS识别方法,应用于辐射源信号识别。仿真结果表明,所提方法对参数区间交叉类型的目标正确识别率较高,具有一定的实际应用价值。      

Research on the evaluation method of lunar soil disturbance based on the fitting of Gaussian surface

It is crucial to maintain the layer sequence information on in situ lunar soil during the lunar soil sampling. In this paper, a discrete element model for direct push sampling of the lunar weathering layer is established, and the relationship between the perturbation rate of the lunar soil layer sequence information and the sampling depth is obtained. A quantitative evaluation method of the perturbation rate of the structural information on the lunar soil layer sequence based on the Gaussian curvature is proposed by reconstructing the center-of-mass point cloud model of the marked layer lunar soil particles in MATLAB. The proposed method can accurately describe the perturbation rate of lunar soil layer sequence information and can analyze the degree of lunar soil disturbance according to the displacement of the sampling tube and mechanical parameters in real-time inversion during the sampling process. When the sampling depth is 40 mm, the minimum and maximum perturbation rates of sampling along the penetration direction of the machine are 5.261 % and 27.649 %, respectively. The perturbation rate shows a trend of first decreasing and then increasing. The method proposed in this study could effectively solve the problem that the disturbance of lunar soil bedding information was difficult to evaluate in the sampling process of lunar regolith.     

A surface reflectance correction model to improve the retrieval of MISR aerosol optical depth supported by MODIS data

Combined use of different satellite sensors are known to improve retrievals of aerosol optical depth (AOD). In this study, we propose a new method for retrieving Multi-angle Imaging SpectroRadiometer (MISR) AOD data supported by Moderate Resolution Imaging Spectroradiometer (MODIS) data in Jiangsu Province, China, over the period of 2016–2018 using MODIS L1B, bidirectional reflectance distribution function (BRDF), MISR 1B2T, and ground-measured AOD data. This method is based on the surface reflectance determined by the MODIS V5.2 algorithm. Through the observation angle and spectral conversion between different sensors, the MISR AOD can be obtained. The correlation coefficient (R) and root-mean-square error (RMSE) between the retrieved MISR and ground-measured AOD data varied between different seasons. The accuracy of the MISR AOD retrieval was notably improved after correcting the MISR surface reflectance. Therefore, the method proposed in this study is feasible for the retrieval of MISR AOD supported by MODIS data, and will be applicable to atmospheric environmental monitoring over large areas in the future.     

基于CLYC闪烁体的中子能谱测量及反演方法

空间中子是影响航天器和航天员安全的重要辐射要素之一。优化中子探测器,提高测量效率,提升反演精度是中子测量的难点。中国空间站将搭载一种基于新型中子探测材料Cs2LiYCl6:Ce（CLYC）闪烁体的中子探测器,该探测器具有同时测量热中子和快中子,以及探测效率高等特点。针对该新型探测器的中子能谱反演,分析了不同能量中子在该探测器中的响应特点,分析了中子反演常用的概率迭代法和非负最小二乘（NNLS）法的优缺点,考虑到这2种方法在CLYC探测器反演应用中的不足,提出了基于增广矩阵的非负最小二乘（AM-NNLS）法。数值实验结果表明:AM-NNLS法具有反演运算效率高和反演相对误差小的特点,验证了所提方法的有效性。      

基于多约束因子图优化的无人车定位与建图方法

针对目前在特定场景下应用的低速无人车定位系统极度依赖全球导航卫星系统（GNSS）,存在定位精度不高、漂移误差大、受环境影响严重等问题,提出一种低成本、高精度的无人车定位与建图方法。该方法基于三维激光定位与建图（SLAM）技术。首先,使用点云主成分分析（PCA）实现基于特征匹配的激光里程计;其次,将GNSS位置信息、点云分割聚类得到的地平面和点云聚类特征作为位姿约束分别加入图优化框架,消除激光里程计的累积误差;最后,得到最优位姿和大规模场景的点云地图,以实现无人车的自主定位导航。利用包含大型户外城市街道环境的KITTI数据集对所提出的SLAM算法进行了评估,结果表明:系统在3km运动距离情况下定位偏差可控制在1.5 m以下,在局部精度和全局一致性方面均优于其他里程计系统,为无人车的定位提供了新思路。      

基于GPS多星三频数据融合的GNSS-IR土壤湿度反演方法

土壤湿度的监测是全球卫星导航系统干涉测量法（GNSS-IR）的关键应用之一。传统的GNSS-IR土壤湿度反演方法一般只针对单颗卫星的单一频段，未充分利用不同轨道、不同频率卫星信号的差异性与互补性。针对此问题，提出了一种将GPS多星的L1、L2和L5频段数据加权融合进行联合反演的方法，该方法利用基于最小方差的自适应融合算法得到加权因子，并通过现场实验进行了方法验证。结果表明:在测试集上所提出的反演方法相比于传统的Larson方法，相关系数提高了24.69%，均方根误差下降了22.28%，与均值融合法相比，相关系数提高了26.77%，均方根误差下降了23.26%，证明了所提方法能有效提高反演精度。      

基于多点逆模型组的直升机慢切换姿态控制

针对传统直升机自适应模型逆姿态控制方法中单点逆模型的不足,提出基于多点逆模型组的慢切换控制方法.该方法构造多点逆模型组取代单点逆模型,将直升机姿态误差控制系统转化为切换系统;引入驻留时间的概念,构造慢切换逻辑,从理论上给出了系统的稳定条件.与传统方法进行了对比仿真,结果表明:该方法有效地减轻了自适应元件的补偿负担,显著提高了其控制性能;系统在切换过程中保持稳定,并具有较强的性能鲁棒性.     

Retrieval of aerosol optical characteristics from polarization measurements of reflected solar radiation above the oceans

The reflected near infrared solar radiation observed from space above the oceans is due mainly to the atmosphere scattering, as the ocean surface is nearly black. The molecular Rayleigh contribution is also minimized at infrared wavelengths and it can be evaluated. It is shown that the degree of polarization is much more sensitive to the aerosol properties than the radiance. Measurements of polarization at two wavelengths and with an angular scanning are simulated and an inversion algorithm is proposed. It aims at finding an “equivalent aerosol model,” which reproduces the optical thickness and the asymmetry factor of the actual aerosol at all wavelengths in the solar spectrum.     

PCB红外热像辐射率校准的非线性滤波方法

在印制电路板(PCB)的红外辐射诊断中,为了获得PCB表面温度的真实分布,须对PCB红外热像进行辐射率校准.将PCB表面温度的测量波形看作真实温度分布与辐射率分布的混合波形,提出一种非线性滤波方法,利用二者连续性的差异将其区分开来.讨论了作为该方法关键步骤的红外热像突变点检测的小波变换实现问题.实验结果表明该方法能够准确地估计PCB表面温度的真实分布波形.该方法还可以用于PCB红外热像的热源辨识以及对未知材料的辐射率估计中.