北斗三号系统PPP-B2b信号定位服务模型及性能分析

给出了PPP-B2b信号定位的观测模型和随机模型,详细阐述了PPP-B2b增强改正模型和参数估计模型,并进行了静态和动态定位实验。结果表明：对于单系统,在30min的收敛时间内,北斗三号定位精度可以达到水平0.118m(静态)、0.176m(动态),高程0.208m(静态)、0.423m(动态)以内,GPS定位精度可以达到水平0.113m(静态)、0.163m(动态),高程0.206m(静态)、0.377m(动态)以内;对于北斗三号/GPS双系统,在20min的收敛时间内,定位精度可以达到水平0.092m(静态)、0.122m(动态),高程0.158m(静态)、0.312m(动态)以内。无论是收敛性还是定位精度,均能满足北斗三号精密单点定位服务指标的要求。     

低雷诺数条件下涡轮性能的计算研究

基于求解欧拉方程的方法,发展了能将多种不同损失模型耦合起来的涡轮S2流面准三维计算程序.并在不同雷诺数条件下对三台发动机涡轮部件性能进行了计算.计算结果表明,三套涡轮的效率及流通能力随雷诺数减小的变化量低于俄罗斯经验关联曲线所给出的变化量,但总体趋势比较吻合,不同的模型计算结果差别较大.      

Naive Bayes邮件过滤模型的特征词选取方法研究

将文本分类中的各种特征词选取方法引入到Naive Bayes邮件过滤模型(NBF)中,包括文档频度、信息增益、互信息、期望交叉熵、文本证据权、几率比及x2统计量.分析比较了这些方法的特点.实验结果显示在NBF中采用x2统计量选取邮件特征词有最好的效果.     

Comparison of Landsat OLI,ASTER, and Sentinel 2A data in lithological mapping : A Case study of Rich area (Central High Atlas,Morocco)

The eastern part of the Rich area consists of the massive Paleozoic and Meso-Cenozoic cover formations that present the geodynamic development of the study area, where is characterized by various carbonate facies of Jurassic age. The geographical characteristic of the study area leaves the zone difficult to map by conventional methods. The objective of this work focuses on the mapping of the constituent lithological units of the study area using multispectral data of Landsat OLI, ASTER, and Sentinel 2A MSI. The processing of these data is based on a precise methodology that distinguishs and highlights the limits of the different lithological units that have an approximate similarity of spectral signature. Three techniques were used to enhance the image including Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Independent Component Analysis (ICA). Lithological mapping was performed using two types of supervised classification : Maximum likelihood classifier (MLC) and Support Vector Machine (SVM).The results of processing data show the effectiveness of Sentinel 2A data in mapping of lithological units than the ASTER and Landsat OLI data. The classification evaluation of two methods of the Sentinel 2A MSI image showed that the SVM method give a better classification with an overall accuracy of 93,93% and a Kappa coefficient of 0.93, while the MLC method present an overall accuracy of 82,86% and a Kappa coefficient of 0.80. The results of mapping obtained show a good correlation with the geological map of the study area as well as the efficiency of remote sensing in identification of different lithological units in the Central High Atlas.     

Evaluation of the improvement of IRI-2016 over IRI-2012 at the India low-latitude region during the ascending phase of cycle 24

This paper investigated the performance of the latest International Reference Ionosphere model (IRI-2016) over that of IRI-2012 in predicting total electron content (TEC) at three different stations in the Indian region. The data used were Global Positioning System (GPS) data collected during the ascending phase of solar cycle 24 over three low-latitude stations in India namely; Bangalore (13.02°N Geographic latitude, 77.57°E Geographic longitude), Hyderabad (17.25°N Geographic latitude, 78.30°E Geographic longitude) and Surat (21.16°N Geographic latitude, 72.78°E Geographic longitude). Monthly, the seasonal and annual variability of GPS-TEC have been compared with those derived from International Reference Ionosphere IRI-2016 and IRI-2012 with two different options of topside electron density: NeQuick and IRI01-corr. It is observed that both versions of IRI (i.e., IRI-2012 and IRI-2016) predict the GPS-TEC with some deviations, the latest version of IRI (IRI-2016) predicted the TEC similar to those predicted by IRI-2012 for all the seasons at all stations except for morning hours (0500 LT to 1000?LT). This shows that the effect of the updated version is seen only during morning hours and also that there is no change in TEC values by IRI-2016 from those predicted by IRI-2012 for the rest of the time of the day in the Indian low latitude region. The semiannual variations in the daytime maximum values of TEC are clearly observed from both GPS and model-derived TEC values with two peaks around March-April and September-October months of each year. Further, the Correlation of TEC derived by IRI-2016 and IRI-2012 with EUV and F10.7 shows similar results. This shows that the solar input to the IRI-2016 is similar to IRI 2012. There is no significant difference observed in TEC, bottom-side thickness (B0) and shape (B1) parameter predictions by both the versions of the IRI model. However, a clear improvement is visible in hmF2 and NmF2 predictions by IRI-2016 to that by IRI-2012. The SHU-2015 option of the IRI-2016 gives a better prediction of NmF2 for all the months at low latitude station Ahmedabad compare to AMTB 2013.     

A regional model for the prediction of M(3000)F2 over East Asia

Research on empirical or physical models of ionospheric parameters is one of the important topics in the field of space weather and communication support services. To improve the accuracy of predicting the monthly median ionospheric propagating factor at 3000 km of the F2 layer (identified as M(3000)F2) for high frequency radio wave propagation, a model based on modified orthogonal temporal–spatial functions is proposed. The proposed model has three new characteristics: (1) The solar activity parameters of sunspot number and the 10.7-cm solar radio flux are together introduced into temporal reconstruction. (2) Both the geomagnetic dip and its modified value are chosen as features of the geographical spatial variation for spatial reconstruction. (3) A series of harmonic functions are used to represent the M(3000)F2, which reflects seasonal and solar cycle variations. The proposed model is established by combining nonlinear regression for three characteristics with harmonic analysis by using vertical sounding data over East Asia. Statistical results reveal that M(3000)F2 calculated by the proposed model is consistent with the trend of the monthly median observations. The proposed model is better than the International Reference Ionosphere (IRI) model by comparison between predictions and observations of six station, which illustrates that the proposed model outperforms the IRI model over East Asia. The proposed method can be further expanded for potentially providing more accurate predictions for other ionospheric parameters on the global scale.     

Analysis of the brightness temperature features of the lunar surface using 37 GHz channel data from the Chang'E-2 microwave radiometer

Compared with other remote observations, brightness temperatures (T_B) derived from microwave emission measurements provide a unique means to characterize the physical properties of the lunar surface. Using Chang’E-2 microwave radiometer data, we produced 12 global T_B images of the lunar surface during a diurnal cycle with different local times separated by approximately 2?h. There are two types of remarkable T_B units on the lunar surface, the “hot regions” occurring during the lunar day in the lunar Maria regions and the “microwave cold spots” occurring during the nighttime typically related to young craters. Compared with their surroundings, the hot regions are much warmer during the lunar day and slightly colder at night, while the microwave cold spots are much colder during the lunar night and slightly warmer in the daytime. Moreover, the T_B heating and cooling rates of these two units are larger than others at the same average latitude where they are located during the lunar day, especially after sunrise and before sunset. The hot regions have a good agreement with the mare regions with high TiO₂ abundance. Besides, brightness temperatures in the lunar Maria correlate closely with their TiO₂ abundance. For most microwave cold spots, they agree with the young craters, and their brightness temperature distributions have a significant negative correlation with the lunar surface nighttime temperature and rock abundance.     

Estimation of differential code biases with Jason-2/3 onboard GPS observations

With the continuous deployment of Low Earth Orbit (LEO) satellites, the estimation of differential code biases (DCBs) based on GNSS observations from LEO has gained increasing attention. Previous studies on LEO-based DCB estimation are usually using the spherical symmetry ionosphere assumption (SSIA), in which a uniform electron density is assumed in a thick shell. In this study, we propose an approach (named the SHLEO method) to simultaneously estimate the satellite and LEO onboard receiver DCBs by modeling the distribution of the global plasmaspheric total electron content (PTEC) above the satellite orbit with a spherical harmonic (SH) function. Compared to the commonly used SSIA method, the SHLEO model improves the GPS satellite DCB estimation accuracy by 13.46% and the stability by 22.34%, respectively. Compared to the GPS satellite DCBs estimated based on the Jason-3-only observations, the accuracy and monthly stability of the satellite DCBs can be improved by 14.42% and 26.8% when both Jason-2 and Jason-3 onboard observations are jointly processed. Compared with the Jason-2 solutions, the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations have an improved consistency of better than 18.26% and 9.71% with the products provided by the Center for Orbit Determination in Europe (CODE) and Chinese Academy of Sciences (CAS). Taking the DCB products provided by the German Aerospace Center (DLR) as references, there is no improvement in accuracy of the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations than the Jason-2 solutions alone. A periodic variation is found in the time series of both the Jason-3 and Jason-2 onboard receiver DCB estimates. Preliminary analysis of the PTEC distribution based on the estimated SH coefficients are also presented.     

PM2.5/PM10 ratio characteristics over urban sites of India

The PM_2.5/PM₁₀ ratio (PM_2.5 and PM₁₀ are defined as mass concentration of particles having aerodynamic diameter less than 2.5 and 10 µm respectively) is one of the important parameters in understanding the severity of the fine mode surface particulate matter pollution. The present study characterises PM_2.5/PM₁₀ ratio estimates from eight Indian urban sites with varying levels of urbanization. Five years (2015–2019) of collocated PM_2.5, PM₁₀, and meteorological (ambient temperature, relative humidity (RH), and wind speed) measurements are used to understand the spatial and temporal variability in the PM_2.5/PM₁₀ ratio at different scales and to investigate its relationship with meteorological parameters. Over the study sites, the seasonal mean PM_2.5/PM₁₀ ratio varied between 0.31 ± 0.08 (mean ± standard deviation) and 0.65 ± 0.13. Seasonally, the highest PM_2.5/PM₁₀ ratio was observed during winter and post-monsoon seasons. Sites in the Indo-Gangetic Plain (IGP) exhibited higher PM levels (PM_2.5 and PM₁₀) and higher PM_2.5/PM₁₀ ratios than the corresponding values recorded at other sites. The seasonal mean PM_2.5/PM₁₀ ratio estimated (over the study sites) using MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) ranged between 0.25 ± 0.08 and 0.77 ± 0.16, and exhibited consistent overestimation (when compared to values derived from measurements) during winter and pre-monsoon seasons. Grossly, the PM_2.5/PM₁₀ ratio exhibited a weak association with meteorological parameters. Interestingly, despite variations in geography, population, anthropogenic activities and PM concentrations across seasons and sites, the PM_2.5/PM₁₀ ratio showed low variability.     

Preliminary gravity recovery from CryoSat-2 data in the Baffin Bay

A number of geophysical phenomenons in the open ocean are still unresolved by conventional altimetry, but could be resolved through the potential improvements offered by Synthetic Aperture Radar (SAR), also called Delay-Doppler, altimetry. The SAR altimeter offers the following benefits with respect to conventional satellite altimetry: factor of 20 improvements in the along-track resolution, the along-track footprint length which does not vary with wave height (sea state), and improved precision in sea surface height measurements or sea surface slope measurements.