Numerical orbit integration based on Lie series with use of parallel computing techniques

This article outlines necessary steps to perform numerical orbit integrations based on a Lie series approach. Its implementation requires an efficient evaluation of resulting series coefficients. As an example we treat the classical main problem in satellite orbit calculation (_J2$J_2$ only) and the case of a 4×4$4\times 4$-gravity field. All calculations were performed in very high precision with up to 100 significant digits. In comparison to independent third party computations this approach led to superior results referring to the verifiable constancy of various integrals of motion. To achieve a performance similar to classical numerical integrations in terms of acceptable computing time, at least for non-Keplerian motion problems, we exploited parallel computing capabilities. For our examples, run times were improved by several orders of magnitude, depending on the actual chosen precision level (up to a factor of 50,000 in case of double precision). Here we present the mathematical framework of the proposed orbital integration scheme as well as the work flow for its application in a multi-core, parallel computing environment.     

基于级数反演法的变速运动SAR回波二维频域模拟算法

针对变速运动平台,提出了一种基于级数反演法的SAR回波模拟二维频域的算法。建立了变速运动模式SAR的几何模型,利用级数反演法,得到了较为准确的信号2维频谱表达式,并对由变速运动引入的大场景空变性进行了分析,给出了空变性相位误差补偿因子,实现了回波信号的精确仿真。分析表明该算法能够在保证较高的相位精度情况下大大的提高SAR回波的仿真速度。仿真结果证明了该算法的有效性。     

基于SCSO-BP神经网络的卫星姿态控制系统故障预测

近年来,随着人工智能的迅速发展,基于人工神经网络的卫星姿态控制系统故障预测方法得到了越来越多的重视。在反向传播(Back Propagation ,BP)神经网络中,权重和偏置是重要的可调节参数,与神经网络的预测性能密切相关。BP神经网络的初始权重和偏置为随机生成,设置不当容易导致网络在训练过程中陷入局部极值,进而影响预测性能。为了提高BP神经网络的预测性能,提出了一种将沙猫群优化(Sand Cat Swarm Optimization ,SCSO)算法与BP神经网络相结合的预测方法。在训练过程中,首先通过SCSO 算法对BP神经网络权重和偏置进行预训练,在此基础上,利用精调后的BP神经网络对卫星姿态控制系统周期渐变故障数据的未来趋势进行预测。实验结果表明,与原始BP神经网络预测方法相比,SCSO-BP预测方法能够有效减小预测误差,具有更好的预测精度。     

基于Volterra级数降阶模型的气动弹性分析

采用Volterra级数进行非定常气动力辨识,建立了基于状态空间的非定常气动力降阶 模型,耦合结构方程,建立了降阶的气动弹性系统和气动伺服弹性系统,开展了颤振分析和 颤振主动抑制的初步研究,计算效率提高了2～3个数量级。通过气动弹性标模AGARD445.6和 气动伺服弹性标模BACT算例验证,证明降阶方法正确,可以提供高效、高精度的气动弹性 分析。
     

基于相似匹配的液体火箭发动机故障模式挖掘

将时间序列相似性匹配方法引入到液体火箭发动机故障模式挖掘中。针对发动机试车数据的特点,提出了一种基于序变换的时间序列相似匹配算法。该算法具有对时间序列幅值和持续时间不敏感、抗噪声能力强等优点。对某型液体火箭发动机故障数据的相似匹配实验表明：该算法能够为液体火箭发动机的故障检测和诊断提供较好的技术支持。     

地球同步轨道SAR曲线轨迹模型和成像算法研究

由于地球同步轨道合成孔径雷达(GEO SAR)轨道高度高,地球自转对其影响较为严重,其相对地球的运动变得更为复杂,低轨SAR中的直线轨迹模型已不能精确逼近其真实成像几何,基于该模型推导的成像算法也不再适用。针对这一问题,本文首先根据GEO SAR平台的运动特点,使用高阶逼近模型建立了适用于GEO SAR长合成孔径时间的斜距方程,并结合级数反演法,推导出该斜距方程下的二维频谱高阶近似表达式。在此基础上提出了一种二维频域成像算法并分析了其运算量。该算法所有操作都由快速傅里叶变换和相位点乘完成,具有较高的效率。点目标仿真结果表明本文斜距方程精度较高,该算法能实现GEO SAR全孔径高精度成像。     

财政投资的季节性动态分析及预测

针对财政投资的季节性特点,以系统动力学的观点为依据,运用X-11ARIMA季节调整的模型预测技术,建立了季节性财政投资分析和预测模型。     

Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California

The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126?GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.     

弹道导弹中段机动突防制导误差修正方法

针对弹道导弹中段反拦截实时机动突防带来的参数偏差问题,给出了在地球非球形摄动影响下的位置和速度偏差量的计算方法,采用改进的fg级数和预测制导方法获得了机动推力的作用方向及发动机的开启时间,并对再入点误差进行了修正。仿真结果表明,采用该方法可有效地修正因机动突防与地球扁率而引起的再入点参数误差,为末制导系统的工作提供了良...     

基于傅里叶展开的电动力绳系卫星最优控制

电动力绳系卫星的推力幅值较小且方向固定,完成轨道机动任务的周期长,其最优控制问题的求解比较困难.采用在傅里叶空间描述的轨道动力学模型,将控制量电流表示为傅里叶级数的形式,并推导了用傅里叶系数作为参量的椭圆轨道运动的平均轨道根数方程.在此基础上构造了电动力绳系卫星轨道机动的最优控制模型,通过直接配置法将其转化为非线性规划...