FY-2卫星的空间环境数据接收及警报系统

介绍了FY-2卫星探测数据的流通过程及接收处理.首先在FY-2卫星及探测器系统中,环境探测数据被收集、调制并发射,再由地基数据接收及解调系统将数据信号放大、解调还原并发送,最后由数据处理及警报系统将数据接收处理、保存显示,并对太阳质子事件、X耀斑进行自动电话报警.该系统是保障航天器安全和提高抗辐照水平的重要手段.     

地磁扰动期间日本Kokubunji站电离层的扰动特征分析

利用日本Kokubunji站(139.5°E,35.5°N)1959年1月到2004年12月共46年的F2层临界频率foF2参数,统计分析了Kokubunji站电离层F2层峰值电子浓度NmF2随地磁活动、太阳活动、季节和地方时变化的形态特征.结果表明,总体来看,磁暴期间Kokubunji站电离层响应以正暴为主,其中在太阳高年夏季为负暴,冬季为正暴,春秋季以负暴为主但幅度较小;在太阳低年夏季以正暴为主,冬季为正暴,春秋季以正暴为主.NmF2扰动与ap指数在夏季太阳高年负相关,在冬季无论太阳高年低年均为正相关,春秋季中4月和9月在太阳高年类似夏季,3月和10月在太阳低年类似冬季.电离层最大负相扰动对最大地磁活动的延迟时间约为12～15 h;正相扰动的延迟时间则分别为3 h和10 h.地磁活跃期间地方时黄昏后到午夜前倾向于正相扰动,清晨倾向于负相扰动.     

在轨地球同步卫星轨道控制参数计算及工程实现

在轨地球同步卫星轨道控制包括东西、南北控制和位置漂移三个部分.分别针对这三种情况,从工程实用角度出发,给出了选择目标参数方法、控制参数计算公式和具体实施策略.以自旋卫星为例,分析了控制效率,提出了一种新的东西控制参数计算方法,在给定控制精度下,大大简化了算法的复杂性.以1904年9月FY-2B星一系列控制为例,详细介绍了它们在经度漂移、南北控制、刹车控制和定点捕获等方面的具体应用和实现效果,理想的控制效果表明了上述算法和实施策略的正确性.     

地磁场与电离层异常现象及其与地震的关系

利用中国地磁台网与电离层台站资料,总结了大地震前出现的地磁低点位移、地磁日变异常及电离层f0F2(F2层临界频率)异常现象.对比研究了1997年11月8日玛尼7.5级与2001年11月14日昆仑山口西8.1级地震前磁场与电离层异常分布及特征.结果显示,两次巨大地震前磁场与电离层短临异常时空分布特征有较好的一致性,震中周围出现日变异常、拉萨台出现电离层f0F2明显异常;震前约1个月出现地磁低点位移,其突变分界线通过震中地区.     

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.     

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.     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.