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Ayodeji Ashidi Joseph Ojo Adekunle Adediji Oludare Ajewole 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2021,67(5):1612-1622
Existing amplitude scintillation prediction models often perform less satisfactorily when deployed outside the regions where they were formulated. This necessitates the need to evaluate the performance of scintillation models developed in one region using data data from other regions while documenting their relative errors. Due to its variation with elevation angle, frequency, other link parameters and meteorological factors, we employed three years (January 2016 to December 2018) of concurrently measured satellite radio beacons and tropospheric weather parameters to develop a location-based amplitude scintillation prediction model over the Earth-space path of Akure (7.17oN, 5.18oE), South-western Nigeria. The satellite beacon measurement used Tektronix Y400 NetTek Analyzer at 1 s integration time while meteorological parameters, namely; temperature, pressure and relative humidity were measured using Davis Vantage Vue weather station at 1 min integration time. Comparative study of the model’s performance with nine (9) existing scintillation prediction models indicates that the best and worst performing models, in terms of root mean square error (RMSE), are the Statistical Temperature and Refractivity (STN) and direct physical and statistical prediction (DPSP) models with values 11.48 and 51.03 respectively. Also, worst month analysis indicates that April, with respective enhancement and fade values of 0.88 and 0.90 dB for 0.01% exceedance, is the overall worst calendar month for amplitude scintillation. 相似文献
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用预测法量化防空导弹武器系统效能的研究 总被引:6,自引:0,他引:6
针对当前分析人员难于求解防空导弹武器系统总体效能值,提出了一套量化系统效能中的系统能力向量C的方法。对该方法作了详细的论述,并用该方法量度了一些防空导弹武器系统的总体系统效能。分析得到的结果是令人满意的,从而进一步解决了如何通过较理想的效能模型,全面地预测防空导弹武器系统在给定条件下完成规定任务的能力问题。 相似文献
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本文介绍了对测控站点内各测控设备的电磁干扰进行分析和预测的方法。系统采用干扰源与接收机逐对考虑的方式,极大简化了计算。并采用分阶段预测的方法,即分成:快速筛选、幅度筛选、频率筛选和详细预测四个阶段进行逐阶段分析和预测。 相似文献
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Han He Huaning Wang Zhanle Du Rong Li Yanmei Cui Liyun Zhang Yulin He 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2008,42(9):1450-1456
Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction. 相似文献
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从非金属材料老化机理与寿命预测模型、老化行为表征技术、贮存环境试验与寿命评估技术等方面,概述了国内外的技术发展和现状,介绍了航天产品用非金属材料及制品贮存寿命评估技术的发展及其应用进展。 相似文献
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