HY-2卫星DORIS厘米级精密定轨

"海洋二号"(HY-2)卫星搭载了新一代DORIS接收机,可提供双频相位和伪距测量数据。针对HY-2卫星的RINEX 3.0格式的相位测量数据,研究了一种区别于传统相位观测数据处理的历元间差分处理方法,将相位观测数据转换为距离变化率观测数据,并进行相关误差修正,建立了HY-2卫星的宏表面力和经验力等摄动模型,基于动力学定轨原理实现了基于DORIS相位观测数据的精密定轨。利用HY-2卫星的DORIS实测数据进行定轨,初步计算结果表明,径向轨道误差优于2cm、三维位置误差约10cm,满足HY-2卫星应用的厘米级轨道精度需求。     

基于J2ME-J2EE平台的移动电子商务系统的实现

为了解决移动电子商务开发中终端设备处理能力有限的问题,实现了基于J2ME-J2EE集成平台,将访问请求转发到服务端进行处理开发移动电子商务系统的方案。在该方案中,J2ME端的MIDP程序接收用户的访问请求,通过HTTP协议把请求转发到J2EE服务器端进行处理;J2EE端采用了流行的Web应用开发框架,分离了程序逻辑,简化了开发复杂度,提高了开发效率。     

台风影响电离层F2区的一种可能机制

在台风期间,特别是台风登陆前后,强烈的海气、陆气相互作用会增强低层大气中的湍流活动,并可能导致大气湍流层顶的抬升.这种抬升会改变高层大气结构,从而影响高层大气中的光化学过程,最终造成对电离层的影响.在台风活动抬升了湍流层顶的前提下,利用一个一维电离层物理模型,模拟了日本中纬地区(45°N,142°E)电离层F2区的响应.模拟结果很好地定性解释了如下观测事实,台风期间,电离层f0F2会下降,对给定频率电波的反射面会抬升;同时还表明以上过程会导致hmF2上升,这表明台风期间湍流层顶的抬升可能是台风影响电离层F2区的一种十分有效的机制.      

基于龙芯处理器的系统移植方法和应用可行性研究

提出了基于龙芯计算模块的嵌入式操作系统移植和实现方法,实现了龙芯计算模块的操作系统加载、启动和驱动开发,并介绍了龙芯处理器的性能测试方法和测试结果,为龙芯国产处理器在航空电子领域的部署和应用可行性提供了一定的依据.     

高超声速喷管非平衡黏性流动的数值研究

分别采用平衡气体模型、化学非平衡气体模型和热化学非平衡气体模型,通过求解轴对称Navier-Stokes方程组,数值模拟了法国Marseille高焓激波风洞锥型喷管(H₀=10.3MJ/kg),分析了热化学非平衡效应对喷管流动的影响,给出了平动温度、振动温度、马赫数和组分质量数在轴对称线上的分布与喷管出口附近的速度和温度沿径向分布等结果。计算结果表明:化学反应速度加快,会导致喷管出口温度增加,振动能的冻结会导致喷管出口温度降低。     

微纳卫星星座的Kuhn-Munkres匹配部署优化方法

针对将半长轴、升交点赤经、纬度辐角均不同的低轨微纳卫星群部署到同一轨道面不同目标相位的星座部署问题,提出一种基于Kuhn-Munkres (KM)匹配的星座部署优化方法.通过KM算法实现卫星和目标纬度辐角的优化匹配,充分利用J2摄动,使升交点赤经借助半长轴和纬度辐角的部署而得到同步修正,从而节约燃料.仿真结果表明,相比...     

Assessment of depth to magnetic sources using high resolution aeromagnetic data of some parts of the Lower Benue Trough and adjoining areas,Southeast Nigeria

High resolution airborne magnetic data acquired between 2005 and 2010 were used to determine depth to shallow and deep magnetic sources in some parts of Southeastern Nigeria. Various depth estimation methods such as standard Euler deconvolution (SED), source parameter imaging (SPI), spectral depth analysis (SDA) and two dimensional (2-D) forward modeling were applied. Results obtained from SED, SPI and models of profiles 1 and 2 indicate that the Abakaliki Anticlinorium (AA) and Ikom-Mamfe Rift (IMR) regions are dominated by short wavelength magnetic anomalies caused by extensive tectonic events. The SED map showed depth to shallow and deep magnetic sources ranging from ~ 16.6 to ~ 338.3 m and ~ 394.3 to ~ 5748.1 m respectively. Likewise, depth estimates from the SPI map varies from ~ 147.1 to ~ 554.2 m (shallow magnetic sources) and ~ 644.2 to ~ 6141.6 m (deep magnetic sources). The result obtained from SDA revealed depths to deep magnetic basement in the range of ~ 769 to ~ 6666 m with an average of ~ 3449 m. Also, it showed that depth to shallow magnetic sources vary between ~ 119 and ~ 434 m with mean of ~ 269 m. The 2-D forward modelling showed maximum depth values of ~ 4700, ~4600 and ~ 6500 m in the models of profiles 1, 2 and 3 within the Anambra Basin (AB), Afikpo Syncline (AS) and Calabar Flank (CF) respectively. Generally, from all the various methods applied the results indicate that AB, AS and CF are dominated by long wavelength anomalies. The 2-D models indicated that the basement framework is undulant. Also, depth estimates involving the various methods used in this study correlate strongly with each other in the AB, AS and CF geological regions.     

The longitudinal and hemispherical variation of the IRI’s foF2 estimates at ±40° dip angle around 95°E and 130°E sector under fluctuating solar flux conditions

The deviation of the IRI estimates of the monthly mean foF2 in the low mid latitude of 95°E–130°E longitude sector is investigated using simultaneous ground measurements at four stations during 2010–2014. The stations form two conjugate pairs of the same geo-magnetic latitude at two fixed longitudes enabling direct longitudinal and hemispheric comparison. The temporal, spatial, seasonal and solar activity variations of the deviations are discussed with reference to the longitudinal density variation in the transition region between low and midlatitudes. Cases of underestimation/overestimation as well as good estimate are noted. Underestimation (overestimation) in the daytime and overestimation (underestimation) in the nighttime of 95°E (130°E) are common. The longitudinal difference in the measurements suggests negative (positive) foF2 gradient from west to east in daytime (nighttime). In contrast, the IRI predicts flatter or increasing longitudinal profiles from 95°E to 130°E. The local time and longitudinal variation of the IRI deviations can be attributed to the combined role of the longitudinal EIA structure as well as midlatitude zonal wind-magnetic declination effect. The station/season independent deviations relate the role of solar activity representation in the IRI. These deviations may be attributed to the weak IRI response to rapid solar flux fluctuations.     

A prediction model of short-term ionospheric foF2 based on AdaBoost

In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.     

Threshold Selection Method Based on Reciprocal Gray Entropy and Artificial Bee Colony Optimization

Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional（2-D）histogram region oblique division and artificial bee colony（ABC）optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional（1-D）method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization（NCPSO）,the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.