卫星地面站资源配置的SVM回归模型

针对卫星地面站资源配置问题输入输出关系的复杂性,提出支持向量机（SVM）回归模型。在模型学习过程中,利用正交设计抽样抽取小数量样本对SVM进行训练,求解二次规划问题,根据测试结果对模型参数进行调整以实现较小的预测误差。实验结果表明,该方法具有较好的拟合精度和泛化能力。     

基于滑动时窗策略自适应优化支持向量机的航空发动机性能参数在线预测

针对传统航空发动机性能参数时间序列预测方法存在的不足,提出了基于滑动时窗策略自适应优化支持向量机(Support Vector Machine,SVM)在线预测模型。该方法解决了训练样本动态适应性差的特点和老旧数据信息影响预测模型精度的问题。在该方法中,滑动时窗策略实时更新时窗数据训练样本,最终误差预报准则(Final Prediction Error,FPE)自适应地确定嵌入维数,遗传算法(Genetic Algorithm,GA)则实时自适应优化SVM建模参数。应用航空发动机排气温度偏差值(Delta Exhaust Gas Temperature,DEGT)数据进行实例验证,结果表明基于滑动时窗策略的自适应GA优化的SVM (GASVM)在线预测模型比传统的GASVM预测模型预测精度有显著提高。进一步分析了预测模型不同时窗宽度对短期预测精度的影响,展示了1步～10步预测的效果,结果表明在线预测模型在不同时窗宽度下短中期(5步以内)预测效果良好且稳定。文中提出的在线预测模型可用于航空发动机性能参数的预测,实现对航空发动机未来性能变化的预警。     

相控阵雷达长时跟踪波束调度与波形优化策略

针对相控阵雷达多目标跟踪波束调度和波形参数优化控制的问题，本文提出了一种基于马尔可夫决策过程（MDP）的相控阵雷达跟踪波束调度与波形参数优化策略，该方法以无迹卡尔曼滤波（UKF）算法为基础来估计目标的状态。首先将本文的序列决策问题建模为马尔可夫决策过程，定义了资源的效费比和长期回报率，然后与当前实际跟踪误差综合考虑作为MDP的回报函数，进而给出了调度的优化模型，最后将长时决策问题转化为动态规划算法结构进行求解，并且提出了一种并行混合遗传粒子群优化算法来求解各决策时刻的最优策略。仿真结果表明了长时策略的先进性以及寻优算法的优越性，与传统的短时策略相比，跟踪精度可提高11.17%。     

测控中的星载计算机快速切换

针对低轨卫星长期管理与测控中的星载计算机所需要的切换、维护的测控时间相对较长的问题,在分析原有主、备星载计算机的时间比对方法的基础上,直接针对备机建立新的时间同步模型,并进行公式推导和理论误差分析;然后建立新的测控事件调度模型,实现时间同步数据与主备机一致性数据的同时注入,优化工作流程,并有效缩短测控时间;最后编写新的遥控作业,在测控中进行实践.应用结果表明,采用新方法可以在一个测控圈次内完成在轨星载计算机的切换与维护,MTTR(Mean Time To Repair,平均恢复时间)小于8 min,时间同步精度优于1 ms,所需测控圈次相对于原方法减少83％以上,适用于在轨卫星长期管理与测控.     

基于模糊信息粒化和优化SVM的航空发动机性能趋势预测

提出采用模糊信息粒化(FIG)和优化的支持向量机(SVM)来预测航空发动机参数的变化趋势和变化空间。利用模糊信息粒化方法对性能参数进行粒化处理。以K CV验证误差最小作为优化目标,采用遗传算法(GA)实现支持向量机惩罚参数和核函数参数的自适应优化选择；训练SVM模型并进行并对模糊粒子非线性预测。利用某航空公司的某型航空发动机性能参数监测数据进行验证,结果表明:该算法可以有效实现航空发动机性能参数变化趋势和变化空间预测。在实例基础上分析了窗口大小对算法预测精度的影响以及算法多步预测的效果,得出算法最佳窗口大小为3个数据且算法3步以内预测误差小于10%。      

航空发动机小偏差状态变量模型的建立方法

采用最小二乘拟合法建立用于航空发动机鲁棒控制系统设计的小偏差状态变量模型，即根据发动机非线性模型的小偏差动态响应数据直接拟合出其小偏差状态变量模型。由于建模误差在最小二乘意义下最小，因而应用该方法可以保证所建模型具有较高精度。此外该方法亦不受模型阶次的限制。应用该方法建立某型涡记扇发动机的小偏差状态变量模型，具有较高的精度，从而验证了该方法的有效性。     

Improvement of Satellite Tracking Accuracy Using Optical Observations

A method to improve satellite tracking accuracy is presented and discussed theoretically and experimentally in terms of two parts: correction for errors of the tracking system and correction of satellite orbit predictions. In the first part, it is concluded that the pointing error of the tracking system can be determined accurately using data from stellar observations, so that correction is possible with an accuracy of about 0.001°. In the second part, it is shown that apparent errors of satellite orbital elements can be deduced from the optical observation of one orbit, and one can track the satellite after the correction with high accuracy for several subsequent orbits. The accuracy is 0.1-0.2 mrad or better for satellites at 1000 km altitude when given orbit prediction accuracy is approximately 1°.     

Robust extended Kalman filter with input estimation for maneuver tracking

This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of the maneuver acceleration is obtained by the combination of an unbiased minimum-variance input and state estimation method and a low-pass filter. Then a threshold-based maneuver detection approach is developed to determinate the start and end time of the unknown maneuvers. During the maneuvering period, the estimation error of the maneuver acceleration is modeled as the sum of a fluctuation error and a sudden change error. A robust extended Kalman filter is developed for dealing with the acceleration estimate error and providing state estimation. Simulation results show that, compared with the Unbiased Minimum-variance Input and State Estimation (UMISE) method, the proposed method has the same position estimation accuracy, and the velocity estimation error is reduced by about 5 times during the maneuver period. Besides, the acceleration detection and estimation accuracy of the proposed method is much higher than that of the UMISE method.     

基于伪距信息的COMPASS-MEO导航卫星单星定轨分析

COMPASS-MEO导航卫星的伪距观测量包含星站距离、接收机钟差和卫星钟差以及各种噪声。本文首先分析了接收机钟差和卫星钟差在一定间隔内主要表现为线性变化的特性,可以考虑将接收机和卫星钟差作为测距的偏差和偏差变化率和轨道一起进行求解。其次,利用实测的MEO导航单星伪距数据,进行了数据预处理和定轨试验,分别对站间无时间同步信息和有时间同步信息两种情况进行定轨、残差分析和参数解算。使用重叠弧段、轨道预报和激光观测数据验证定轨结果的精度。结果表明,两种情况下的定轨结果无明显差别。该定轨方法可以运用于MEO导航单星精密轨道的计算。     

卫星双向法与卫星测距

卫星双向时间比对是目前远距离台站时间比对精度最高的时间同步技术,时间比对精度达几百皮秒,比GPS共视技术的时间比对精度几乎高一个数量级。中科院国家授时中心根据多台站卫星时间比对经验,提出利用卫星双向比对技术进行卫星测距(称转发器定轨)。实验证明:利用卫星双向技术(卫星需要转发器)进行卫星测距,可得到高精度卫星轨道(内符精度为几厘米)和卫星预报轨道。     

Robust fault-tolerant attitude control for satellite with multiple uncertainties and actuator faults

In this paper, the satellite attitude control system subject to parametric perturbations, external disturbances, time-varying input delays, actuator faults and saturation is studied. In order to make the controller architecture simple and practical, the closed-loop system is transformed into a disturbance-free nominal system and an equivalent disturbance firstly. The equivalent disturbance represents all above uncertainties and actuator failures of the original system. Then a robust controller is proposed in a simple composition consisting of a nominal controller and a robust compensator. The nominal controller is designed for the transformed nominal system. The robust compensator is developed from a second-order filter to restrict the influence of the equivalent disturbance. Stability analysis indicates that both attitude tracking errors and compensator states can converge into the given neighborhood of the origin in finite time. To verify the effectiveness of the proposed control law, numerical simulations are carried out in different cases. Presented results demonstrate that the high-precision attitude tracking control can be achieved by the proposed fault-tolerant control law. Furthermore, multiple system performances including the control accuracy and energy consumption index are fully discussed under a series of compensator parameters.     

Adaptive robust cubature Kalman filtering for satellite attitude estimation

This paper is concerned with the adaptive robust cubature Kalman filtering problem for the case that the dynamics model error and the measurement model error exist simultaneously in the satellite attitude estimation system. By using Hubel-based robust filtering methodology to correct the measurement covariance formulation of cubature Kalman filter, the proposed filtering algorithm could effectively suppress the measurement model error. To further enhance this effect and reduce the impact of the dynamics model error, two different adaptively robust filtering algorithms, one with the optimal adaptive factor based on the estimated covariance matrix of the predicted residuals and the other with multiple fading factors based on strong tracking algorithm, are developed and applied for the satellite attitude estimation. The quaternion is employed to represent the global attitude parameter, and three-dimensional generalized Rodrigues parameters are introduced to define the local attitude error. A multiplicative quaternion error is derived from the local attitude error to maintain quaternion normalization constraint in the filter. Simulation results indicate that the proposed novel algorithm could exhibit higher accuracy and faster convergence compared with the multiplicative extended Kalman filter, the unscented quaternion estimator, and the adaptive robust unscented Kalman filter.     

成像观测卫星多星联合调度模型及其列生成求解算法研究

首先介绍成像观测卫星调度问题的特点和主要约束,将成像观测卫星调度分为调度预处理、调度模型及求解、调度结果评估3个阶段。在此基础上,论述成像观测卫星调度模型,并采用列生成法,将多卫星调度问题分解为集合分割主问题和单卫星调度子问题,通过循环迭代来求解调度模型。最后,针对本文提出的算法设计一个问题实例,并给出算法计算结果。结果分析表明,本文提出的模型和算法能较好解决实际应用问题。     

适航指令案例安全风险灰色评估与预测模型

基于1996～2019年的适航指令（CAD）数据，以关联分析得出的典型故障构建评价指标。用风险系数确定白化权函数的边界条件，根据偏差最大化原则确定各指标的权重，提出了基于灰色白化权聚类的安全风险评估模型。利用等时间间隔的各指标数据构成灰色预测模型，并通过优化权重值将预测精度提高了2.88%。预测的故障数量与实际发生相符，证明了预测模型的准确性，可依此有针对地提出改进和预防措施，从而减少故障的发生。     

基于遗传算法的航空发动机状态变量模型建立方法

提出了一种采用遗传算法建立用于航空发动机控制系统设计的小偏差状态变量模型的方法,即根据发动机稳态工作点处的线性化数学模型的动态响应应该与该稳态工作点处的非线性数学模型动态响应一致的原则来构造遗传算法的适应度函数,通过优化算法,得出系统的状态变量模型。该方法不受系统模态及模型阶次的限制。应用该方法建立某型涡扇发动机的小偏差状态变量模型,具有较高的建模精度,根据该状态变量模型设计鲁棒控制器取得了良好的控制效果,从而验证了该方法的有效性。      

基于支持向量机回归的电力负荷预测研究

不同于传统的基于经验风险最小化的回归方法,支持向量机回归方法基于结构风险最小化准则.与神经网络相比,该方法在解决学习精度和推广性之间的矛盾方面有明显的优势.本文以城市电力负荷预测为应用背景,对比研究了基于统计学习理论的支持向量机回归方法和神经网络方法.预测结果显示支持向量机可能是一种非常有前景的预测工具,其预测精度明显好于神经网络.     

Ensuring GPS navigation integrity using receiver autonomousintegrity monitoring

The many advantages of Global Positioning System (GPS) based navigation have created a tremendous amount of interest in using GPS as the primary navigation aid onboard commercial and civil aircraft. Even in the presence of Selective Availability, the accuracy of GPS is sufficient to guide aircraft point-to-point between airports without requiring other navigation aids such as VOR or DME. Unfortunately, there is a finite probability that a GPS satellite will fail, causing the transmission of potentially misleading navigation information. Thus, before GPS can be widely adopted as a navigation aid, techniques must be devised to detect any possible failures and notify the user prior to the degradation of navigation accuracy. This paper discusses the problem of detecting possible GPS satellite failures using a technique called Receiver Autonomous Integrity Monitoring (RAIM)     

鲁棒EKF在脉冲星导航系统中的应用

针对脉冲星导航系统的滤波问题,传统的扩展卡尔曼滤波(EKF)算法存在不能克服系统模型存在不确定性参数以及乘性噪声等缺陷,提出一种鲁棒EKF算法。首先,分析了状态预测误差方程和估计误差方程,利用统计学原理,得到了状态预测方差矩阵和状态估计方差矩阵计算等式。由于系统模型存在不确定性参数,状态预测协方差矩阵和状态估计协方差矩阵无法计算;因此,利用4个重要矩阵不等式,分析并找到预测方差矩阵和状态估计方差矩阵的上界。最后,利用状态估计误差协方差矩阵上界设计状态增益矩阵,使得状态估计协方差矩阵的迹最小。将该算法对脉冲星导航系统进行仿真,仿真结果验证了所提算法的有效性。     

基于任务聚类的多星观测调度方法

星上传感器侧摆次数有限,在卫星观测调度时进行任务聚类可以节省资源,提高观测效率.提出了动态聚类调度算法(DCSA)来解决多星多轨道圈次的观测调度问题,DCSA把聚类和调度动态结合起来,并使用模拟退火算法搜索全局最优解;分析了在满足分辨率需求前提下多任务聚类的约束条件,并对聚类任务的侧摆角度和时间窗口进行合理优化;根据任...     

一种无卫星辅助的制导弹药滚转角误差修正算法

针对海军舰载制导弹药MEMS惯导系统在卫星失锁后滚转角误差较大的问题，提出了一种不依赖卫星的制导弹药误差修正算法。根据弹体高速旋转时的定轴性使得短期内弹体侧向位移为零的特点，建立了弹体发射坐标系导航误差方程。利用自适应扩展Kalman滤波估计与修正卫星失效条件下的滚转角误差。为了检测并抑制量测突变引起的随机误差，使用自适应因子来调整滤波器参数。车载模拟试验和弹道仿真结果表明，10s对准时间内，滚转角误差能够收敛到0.5°以内，满足制导弹药控制精度的要求, 降低了制导弹药飞行过程中对卫星导航的依赖，提高了系统的自主性。