A global empirical orthogonal function model of plasmaspheric electron content

Based on the method for establishing a global plasmaspheric model using observations from COSMIC and MetOp-A orbit determination GNSS receivers, Chen et al. (2017) obtained a global plasmaspheric total electron content product with a spatial resolution of 2.5° × 5° and a time resolution of 4 h. In this paper, we use those global plasmaspheric electron content product in 2008, 2010, 2011, 2012, 2014 for 1446 days to establish a global plasmaspheric empirical model based on empirical orthogonal function (EOF). The model can well characterize the spatiotemporal variation of plasmaspheric electron content (PEC) and the influence of solar radiation on it. Only the first four orders of EOF sequences can characterize the 98.43% features of the original PEC dataset. The principal component coefficient Pk is decomposed twice during modeling, and the combination of trigonometric function and linear function is used to model Pk to characterize the solar cycle, annual cycle, semi-annual cycle and quarter-cycle variation. We compare the PEC model values with the actual observation data, the results show that the empirical PEC model values are highly correlated with the actual observations. The correlation between the two is above 0.96, and the RMS maximum of the difference between the PEC model values and the observed values are 0.70 TECU, and the average of the difference between the PEC model values and the observed values are −0.18 TECU, respectively. In addition, we validate the reliability of the global plasmaspheric model established by two empirical orthogonal function decomposition method using actual observation data, according to the global distribution of the differences between the PEC model values and the observed values in low solar activity and high solar activity, it can be seen that under low solar activity and high solar activity conditions, the model has good adaptability.     

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.     

漂浮基空间机器人捕获卫星过程动力学模拟及捕获后混合体运动的RBF神经网络控制

 讨论了漂浮基空间机器人在轨捕获目标卫星过程的碰撞动力学建模,以及捕获操作结束后空间机器人与卫星混合体的稳定控制问题。首先采用多刚体动力学建模方法并结合空间机器人捕获目标卫星过程中的碰撞动力学特性,建立了漂浮基空间机器人在轨捕获漂浮卫星过程的动力学模型,并在此基础上计算出完成捕获操作后空间机器人与目标卫星混合体关节的运动速度。然后针对卫星及空间机器人系统惯性参数均是未知的复杂情况,应用上述模型、神经网络控制理论和Lyapunov稳定性理论,设计了空间机器人与卫星混合体在捕获过程碰撞冲击影响下稳定运动的高斯径向基函数神经网络控制方案,以达到对捕获卫星的有效控制。此外,高斯径向基函数神经网络控制方案具有不需要测量和反馈载体位置、移动速度与加速度的显著优点。系统数值仿真证实了上述控制方案的有效性。     

0-1线性规划的连续化求解方法

针对0-1线性规划的优化问题,提出一种惩罚函数方法。考虑到0-1线性规划的最优值特征,通过在目标函数中加上惩罚函数,将0-1离散线性规划模型连续化成非线性规划模型,并使用Matlab的Fmincon函数进行求解。经对多个算例的计算,并和其他算法比较,结果表明惩罚函数法的可行性和有效性。将该方法应用于实际的飞机排班问题上,取得比较满意的结果。     

一种求解Euler方程的简化气体动理学模型

基于一种简化的平衡分布函数,提出一种新的动理学通量矢量分裂（KineticFluxVectorSplitting,KFVS）格式来求解Euler方程。算例证实,新的KFVS格式继承了原始KFVS格式中捕捉激波准确、无数值震荡的优点。与原始的KFVS格式相比,由于简化的平衡分布函数与Maxwellian平衡分布函数相比复杂程度大大降低,计算中不需要再计算误差函数,新的KFVS格式的计算效率得到了很大提高。在同样的计算精度下,新KFVS格式比原始KFVS格式计算效率提高了一倍以上,显示了新格式具有良好的数值模拟性能。     

基于 MTF的潜航体尾迹 SAR成像仿真

基于水动力学理论和波流弱相互作用理论,运用波作用量谱平衡方程研究了潜航体的尾流场与表面波作用后的表面尾迹,探讨了采用传递变换函数实现表面尾迹SAR成像的可行性。研究表明,波作用量谱平衡方程能够较准确地计算出潜航体尾流场与表面波之间的非线性相互作用;传递变换函数能够快速有效实现海面后向散射系数到SAR图像的转换,且保证了较高的精度。     

用于发动机涡轮盘叶片加工的夹具设计

介绍了用于加工发动机涡轮盘叶片夹具的设计准则,并给出了采用矢量三角函数和VC软件计算夹具极限偏差的公式及其判别依据,采用该准则设计的夹具用于涡轮盘叶片加工,产品满足设计要求,并通过了发动机热试车考核。     

用AM300型函数信号发生器建立相位测量标准装置

提出了一种建立相位测量标准装置的方法。该标准装置以AM300型函数信号发生器为主标准器,相位计、示波器、失真度测量仪、数字电压表为配套设备。对AM300型函数信号发生器的量值指标进行了测试和实验,包括：相位增量误差测试、相位绝对零度误差测试、60°幅相误差测试、测量的重复性实验和长期稳定性实验。结果表明：该标准装置测试结果准确,性能稳定可靠,具有造价低、实用性强的特点。     

Weibull分布更新函数的指数近似算法

针对Weibull分布的更新函数较难确定的问题,研究了在平均寿命相等情况下指数分布与Weibull分布之间的贴近性.在此基础上,提出利用指数分布的更新函数模型计算Weibull分布的更新函数,能够比较方便有效地得到近似解.通过实例计算,分别比较了指数方法(直接利用指数分布的更新函数)、线性加权模型以及几何加权模型等三种方法的精度.结果表明:当时间较短时,线性加权和几何加权模型比指数方法精确度有所提高;当时间较长时,几何加权模型的精度较高.利用该结论能够为工程应用提供方便.     

基于模糊优化方法蜗杆减速器传动的设计

目的将模糊优化设计方法运用于蜗杆传动的设计中;方法以圆柱蜗杆传动的蜗杆齿数、模数和直径系数作为设计变量,并以蜗轮有色金属齿圈体积最小作为设计目标函数,采用离散消元法进行求解;结果建立蜗杆传动模糊优化的数学模型,得到最优解;结论与常规设计方案相比,齿圈体积下降52.36%,在生产实际中,能够提高蜗杆传动的使用价值和社会经济效益。