Boost-Phase ballistic missile trajectory estimation with ground based radar

A conditional boost-phase trajectory estimation method based on ballistic missile （BM） information database and classification is developed to estimate and predict boos-phase BM trajectory. The main uncertain factors to describe BM dynamics equation are reduced to the control law of trajectory pitch angle in boost-phase. After the BM mass at the beginning of estimation, the BM attack angle and the modification of engine thrust denoting BM acceleration are modeled reasonably, the boost-phase BM trajectory estimation with ground based radar is well realized. The validity of this estimation method is testified by computer simulation with a typical example.

Extended state observer-based control with an adjustable parameter for a large ground-based telescope

The high-precision requirements will always be constrained due to the complicated operating conditions of the ground-based telescope. Owing to various internal and external disturbances, it is necessary to study a control method, which should have a good ability on disturbance rejection and a good adaptability on system parameter variation. The traditional proportional-integral(PI) controller has the advantage of simple and easy adjustment, but it cannot deal with the disturbances well in different situations. This paper proposes a simplified active disturbance rejection control law, whose debugging is as simple as the PI controller, and with better disturbance rejection ability and parameter adaptability. It adopts a simplified second-order extended state observer(ESO) with an adjustable parameter to accommodate the significant variation of the inertia during the different design stages of the telescope. The gain parameter of the ESO can be adjusted online with a recursive least square estimating method once the system parameter has changed significantly. Thus, the ESO can estimate the total disturbances timely and the controller will compensate them accordingly. With the adjustable parameter of the ESO, the controller can always achieve better performance in different applications of the telescope. The simulation and experimental verification of the control law was conducted on a 1.2-meter ground based telescope. The results verify the necessity of adjusting the parameter of the ESO, and demonstrate better disturbance rejection ability in a large range of speed variations during the design stages of the telescope.

Long-term gravity changes in Chinese mainland from GRACE and ground-based gravity measurements

A long-term （9 years） gravity change in Chinese mainland is obtained on the basis of observation of the ground-based national gravity network. The result shows several features that may be related to sore, large-scale groundwater pumping in North China, glacier-water flow and storage in Tianshan region, and pre seismic gravity changes of the 2008 MsS. 0 Wenchuan earthquake, which are spatially similar to co-seismi, changes but reversed in sign. These features are also shown in the result of the satellite-based GRACE obser vation, after a height effect is corrected with GPS data.

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

Trends in gravity changes from 2009 to 2013 derived from ground-based gravimetry and GRACE data in North China

North China is a key region for studying geophysical progress. In this study, ground-based and Gravity Recovery and Climate Experiment（GRACE） gravity data from 2009 to 2013 are used to calculate the gravity change rate（GCR） using the polynomial fitting method. In general, the study area was divided into the Shanxi rift, Jing-Jin-Ji（Beijing-Tianjin-Hebei Province）, and Bohai Bay Basin（BBB） regions. Results of the distribution of the GCR determined from ground-based gravimetry show that the GCR appears to be ＂negativepositive-negative＂ from west to east, which indicates that different geophysical mechanisms are involved in the tectonic activities of these regions. However, GRACE solutions are conducted over a larger spatial scale and are able to show a difference between southern and northern areas and a mass redistribution of land water storage.

A Differential Optical Absorption Spectroscopy Method for X_(CO_2) Retrieval from Ground-Based Fourier Transform Spectrometers Measurements of the Direct Solar Beam

A differential optical absorption spectroscopy （DOAS）-like algorithm is developed to retrieve the column-averaged dry- air mole fraction of carbon dioxide from ground-based hyper-spectral measurements of the direct solar beam. Different to the spectral fitting method, which minimizes the difference between the observed and simulated spectra, the ratios of multiple channel-pairs--one weak and one strong absorption channel--are used to retrieve Xc02 from measurements of the shortwave infrared （SWIR） band. Based on sensitivity tests, a super channel-pair is carefully selected to reduce the effects of solar lines, water vapor, air temperature, pressure, instrument noise, and frequency shift on retrieval errors. The new algorithm reduces computational cost and the retrievals are le^s sensitive to temperature and H20 uncertainty than the spectral fitting method. Multi-day Total Carbon Column Observing Network （TCCON） measurements under clear-sky conditions at two sites （Tsukuba and Bremen） are used to derive Xc02 for the algorithm evaluation and validation. The DOAS-like results agree very well with those of the TCCON algorithm after correction of an airmass-dependent bias.

Validation of total ozone data between satellite and ground-based measurements at Zhongshan and Syowa stations in Antarctica

We present validation between total ozone from satellite and ground-based observations of the Dobson and Brewer spectrometers and ozone radiosonde at Zhongshan and Syowa Antarctic research stations, for September 2004 to March 2009. Results show that mean bias error between Zhongshan （Syowa） and Ozone Monitor Instrument Total Ozone Mapping Spectrometer （OMI-TOMS） data are -0.06%＋3.32% （-0.44%：i：2.41%）; between it and OMI Multi Axis Differential Optical Absorption Spec- troscopy （OMI-DOAS） data, the error is -0.34%--4.99% （-0.22%~4.85%）. Mean absolute bias error values of OMI-TOMS data are less than those of OMI-DOAS. This means that total ozone of OMI-TOMS is closer to ground-based observation than that of OMI-DOAS. Comparison between direct observational total ozone of ground-based and integrated ozone from the ozone profile measured by ozone radiosonde shows that ozone amount calculated with the Solar Backscatter Ultraviolet （SBUV） method above balloon burst height is similar to corresponding Microwave Limb Sounder （MLS） data. Therefore, MLS data can be substituted with SBUV data to estimate ozone amount above that level. Mean bias error of the MLS ozone column is 2% compared with the ozonesonde column, with standard deviation within 9.5%. Comparison of different layers from ozone profiler and MLS data indi- cates that at the 215 hPa layer, the MLS ozone value is high, with relative deviation more than 20%. At the 100 hPa and 68 l^Pa layers, the MLS ozone value is also high. This deviation is mainly in spring, during Antarctic ozone hole appearance. In this period, at the height of severe ozone loss, relative deviation of MLS ozone values is especially large.

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

Primary Analysis of Sounding Data from a Multi-channel Parallel Ground-based Microwave Radiometer

The sounding data of a multi-channel parallel ground-based microwave radiometer （MWR） in Fuzhou station in July and August in 2016 were compared with the sounding data of a radiosonde in the same position in the same period. The results showed that the correlations between the two types of temperature or humidity detected by the microwave radiometer and the radiosonde were significant at 0.05 level, indicating that the overall changing trends of temperature or humidity detected by the two devices were similar. The temperature detected by the microwave radiometer and the radiosonde decreased with the increase of height. The difference between the changes in the height of the zero layer detected by the micro- wave radiometer and the radiosonde was not significant, and their trends were basically the same.

Ground-based remote sensing of atmospheric total column CO_2 and CH_4 by direct sunlight in Hefei

Fourier transform spectrometry has played an important role in the three-dimensional greenhouse gas monitoring as the focus of attention on global warming in the past few years. In this paper, a ground-based low-resolution remote sensing system measuring the total columns of CO2 and CH4 is developed, which tracks the sun automatically and records the spectra in real-time and has the advantages of portability and low cost. A spectral inversion algorithm based on nonlinear least squares spectral fitting procedure for determining the column concentrations of these species is described. Atmospheric transmittance spectra are computed line-by-line in the forward model and observed on-line by direct solar radiation. Also, the wavelength shifts are introduced and the influence of spectral resolution is discussed. Based on this system and algorithm, the vertical columns of O2, CO2, and CH4 are calculated from total atmospheric observation transmittance spectra in Hefei, and the results show that the column averaged dry-air mole fractions of CO2 and CH4 are measured with accuracies of 3.7% and 5%, respectively. Finally, the H2O columns are compared with the results observed by solar radiometer at the same site and the calculated correlation coefficient is 0.92, which proves that this system is suitable for field campaigns and used to monitor the local greenhouse gas sources under the condition of higher accuracy, indirectly.

Seismic Response of Base-Isolated Structures underMulti-component Ground Motion Excitation

An analysis of a base-isolated structure for multi-component random ground motion is presented. The mean square respond of the system is Obtained under different parametric variations. The effectiveness of main parameters and the torsional component during an earthquake is quantified with the help of the response ratio and the root mean square response with and without base isolation. It is observed that the base isolation has considerable influence on the response and the effect of the torsional component is not ignored.

Probabilistic analysis for the response of nonlinear base isolation system under the ground excitation induced by high dam flood discharge

According to theoretical analysis, a general characteristic of the ground vibration induced by high dam flood discharge is that the dominant frequency ranges over several narrow frequency bands, which is verified by observations from the Xiangjiaba Hydropower Station. Nonlinear base isolation is used to reduce the structure vibration under ground excitation and the advantage of the isolation application is that the low-frequency resonance problem does not need to be considered due to its excitation characteristics, which significantly facilitate the isolation design. In order to obtain the response probabilistic distribution of a nonlinear system, the state space split technique is modified. As only a few degrees of freedom are subjected to the random noise, the probabilistic distribution of the response without involving stochastic excitation is represented by the δ function. Then, the sampling property of the δ function is employed to reduce the dimension of the Fokker-Planck-Kolmogorov （FPK） equation and the low-dimensional FPK equation is solvable with existing methods. Numerical results indicate that the proposed approach is effective and accurate. Moreover, the response probabilistic distributions are more reasonable and scientific than the peak responses calculated by conventional time and frequency domain methods.

一种近实时全球电离层数据同化和预报系统的构建与实现

电离层天气变化正成为目前空间天气预报最重要的内容之一,建立一个可靠的、精确的电离层特征参量现报和预报系统对空间科学研究及军民用无线电信息系统保障均具有重要价值。基于国际GNSS服务组织(International GNSS Service,IGS)的地基GNSS和全球电离层无线电观测站(Global Ionospheric Radio Observatory,GIRO)数字测高仪的实时数据,以国际参考电离层(International Reference Ionosphere,IRI)模型为背景模型,采用高斯-马尔可夫-限带卡尔曼滤波同化技术,结合超大规模矩阵稀疏存储与处理方法,在云计算平台上构建完成了近实时全球电离层数据同化和预报系统(near-Real-Time Global Ionospheric Data AssiMilation and forecasting system,RT-GIDAM)。该系统具备了全球电离层TEC和电子密度的近实时(延时约5 min)、较高空间(5°×2.5°)和时间分辨率(15 min)的同化和预报功能,可为空间物理研究及相关无线电系统应用提供数据支撑。

塔里木盆地及其周边地区大气可降水量分布及其与降水关系的研究

利用2018年7月至2022年6月塔里木盆地及其周边地区17部地基GPS水汽探测仪遥感的大气可降水量(PWV)资料、 14个地面气象站逐时和逐日降水资料,分析了塔里木盆地西部(区域A)和东部(区域B)PWV分布特征及其与降水关系。结果表明:(1)研究区年平均PWV高值区主要集中于盆地北部和盆地西南部平原地区,海拔超过1300 m站点的PWV年平均值与海拔成反比,低于1300 m的低海拔地区PWV年平均值在10~12 mm。夏季测站PWV平均值是春、秋季节的2倍。(2)区域A和区域B PWV月变化呈单峰型分布,分别在8月和7月达到峰值。区域A有、无降水日PWV均在23:00(北京时,下同)达到日峰值。区域B有、无降水日PWV日峰值出现时间相差5 h,分别出现在11:00和17:00。(3)区域A和区域B多数测站ΔPWV(PWV与PWV月平均值差值)峰值分别在降水开始前0~1 h和降水开始时刻前后1 h出现。春季区域B降水前PWV跃变程度较区域A更剧烈,夏季各区域σPWV(PWV与PWV月平均值倍数)提前降水开始时刻1 h、 5~6 h达到1~1.8倍的天气过程较其余时次偏多。秋季和冬季区域BσPWV分别集中在1.4~2.0倍和1.6~2.4倍。(4)海拔高于1400 m测站的5-6月、 7-8月PWV值达到10~20 mm和15~25 mm,对应降水结束时刻。海拔低于1400 m测站5-8月降水结束时刻PWV值逐渐由15~25 mm增至25~35 mm。

地基深空探测雷达研究进展与展望

地基深空探测雷达通过主动发射电磁波,并接收反射信号,实现对深空目标的精确测量,是研究月球、近地小行星、类地行星等深空目标的重要手段。地基深空探测雷达可以高精度测量深空目标的轨道、自转、形貌等特征,具有全天时全天候观测、精确测距、高分辨率成像等优势,对近地小行星防御和行星科学研究具有重要意义。本文介绍了地基深空探测雷达的概念内涵,梳理了地基深空探测雷达系统的国内外发展现状,回顾了地基深空探测雷达过去数十年间取得的重要历史贡献,包括月球表面高分辨率成像与永久阴影区水冰探测、近地小行星精细形貌特征获取、近地小行星轨道与自转等物理特性精确测量、近地小行星撞击防御任务处置效果快速评估、类地行星表面高分辨率成像与地质结构研究等一系列重要研究成果。在此基础上,本文介绍了分布孔径深空探测雷达的创新机理,通过多部雷达单元协同观测,可突破传统集中式体制地基深空探测雷达的口径和发射功率物理极限,形象称之为“中国复眼”雷达。最后,本文介绍了分布孔径深空探测雷达系统研制与观测实验等最新研究进展,展示了分布孔径深空探测雷达对月球二维成像和三维成像的实验结果,并对地基深空探测雷达的未来发展趋势进行了展望。

Seismic Responses of Asymmetric Base-Isolated Structures under Near-Fault Ground Motion

An inter-story shear model of asymmetric base-isolated structures incorporating deformation of each isolation bearing was built, and a method to simultaneously simulate bi-directional near-fault and far-field ground motions was proposed. A comparative study on the dynamic responses of asymmetric base-isolated structures under near-fault and far-field ground motions were conducted to investigate the effects of eccentricity in the isolation system and in the superstructures, the ratio of the uncoupled torsional to lateral frequency of the superstructure and the pulse period of near-fault ground motions on the nonlinear seismic response of asymmetric base-isolated structures. Numerical results show that eccentricity in the isolation system makes asymmetric base-isolated structure more sensitive to near-fault ground motions, and the pulse period of near-fault ground motions plays an import role in governing the seismic responses of asymmetric base-isolated structures.

基于多模型神经网络的湿度廓线反演研究

为提升微波辐射计对大气廓线探测的精度,利用ARM大气观测站提供的地基微波辐射计、毫米波测云雷达以及探空数据,构建了两种添加不同云信息的反向传播神经网络(back propagation neural network,BPNN)模型(添加入云和出云高度的C-BPNN模型与添加雷达反射率因子的Z-BPNN模型)与一种未添加云信息的BPNN模型(记为BPNN0),并对反演结果进行了对比,结果表明:C-BPNN模型和Z-BPNN模型在任何天气下(有云或无云),得到的反演误差都小于BPNN0模型;C-BPNN相较于另外两种模型反演结果具有更高的稳定性。对3种模型各自反演结果最好的个例分析发现,C-BPNN与Z-BPNN模型主要的误差存在于高空无云但是相对湿度却出现跃变的情况,说明神经网络模型对初始权值与阈值较为敏感,因此通过遗传算法(genetic algorithms,GA)对BPNN模型进行优化。经GA优化后的反演结果表明:BPNN0模型与C-BPNN模型具有明显优化效果,而Z-BPNN模型优化效果则不明显。

基于极值理论的地基增强系统完好性评估方法

针对地基增强系统(Ground Based Augmentation System,GBAS)完好性风险事件的极端性而导致的无法通过风险事件发生频率评估系统性能的问题,提出一种基于极值理论的GBAS完好性评估方法。根据机载端(位置域)输出的位置误差和保护级计算安全系数,并利用区间极大值模型对安全系数进行建模描述以获得其分布模型;利用极大似然法估计安全系数模型参数,进而利用模型外推法计算GBAS完好性风险值。给出GBAS完好性评估流程,并利用GBAS系统进行了验证实验。研究结果表明:对于C类GBAS进近服务而言,基于全球定位系统(Global Position System,GPS)增强GBAS和基于北斗卫星导航系统(Beidou Navigation Satellite System,BDS)增强GBAS可用性均大于99.9999%;对于F类GBAS进近服务而言,BDS GBAS可用性能要优于GPS GBAS;根据7 d观测数据外推得到的GPS GBAS垂直和侧向完好性风险值分别为4.557×10^(-8)/进近和5.152×10^(-8)/进近,BDS GBAS垂直和侧向完好性风险值分别为1.612×10^(-7)/进近和1.823×10^(-7)/进近,满足航空器终端区I类进近与着陆导航性能需求。

结合气象监测与地基云图的地表太阳辐射预测

高精度的太阳辐照度预测是光伏输出功率预测的基础,而云的遮挡是导致太阳辐射波动的主要原因。针对现有技术由于对云图时变特征获取能力不足,导致在复杂天气条件下预测精度显著下降的问题,提出了利用3D卷积神经网络同时提取单张云图图像特征和云图序列时变特征,建立云图图像特征与云对地表太阳辐射衰减之间的关联,实现太阳辐射高精度预测的方法。实验验证结果表明,较现有方法,所提出的方法在复杂天气条件下的未来5 min功率预测精度提高8%以上,具有很高的推广应用价值。