X射线脉冲星导航技术研究进展

X射线脉冲星能够为近地轨道、深空和星际空间飞行航天器提供位置、速度、时间和姿态等丰富的导航信息,实现航天器高精度自主导航和运行管理,有着巨大的发展潜力.本文论述了X射线脉冲星导航技术研究历程;重点研究了X射线脉冲星导航的基本原理、信息处理流程和自主导航算法,进而提出了脉冲星导航的关键技术;分析了国内脉冲星观测研究的基础条件,以及开展X射线脉冲星导航技术研究的必要性和可行性.      

A variational Bayesian-based robust adaptive filtering for precise point positioning using undifferenced and uncombined observations

In the application of precise point positioning (PPP), especially in the dynamic mode, the classical Kalman filter (KF) usually produces a large number of estimation errors or diverges when there are gross errors in the observation data or unexpected turbulences occur in target motion state or both of them. For such problem, a variational Bayesian (VB)-based robust adaptive Kalman filtering (VB-RAKF) is proposed in this paper. This filter introduces a classification robust equivalent weight function to resist observation gross error and the inverse Wishart prior to model inaccurate process noise covariance matrix (PNCM). To improve the instantaneous accuracy of state estimation, the VB approach is used to obtain better estimations of inaccurate PNCM. Several sets of observation data collected by IGS reference stations and vehicles are employed to check the robustness and positioning accuracy of the VB-RAKF model. The results show that the VB-RAKF algorithm is more robust than the KF, and can effectively resist the gross error in observation data and control state disturbance. In the IGS reference station tests, when compared to the KF, the static positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 13%, 8% and 22%, respectively, and the simulated dynamic positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 19%, 9% and 21%, respectively. The in-vehicle dynamic test verifies that the VB-RAKF outperforms the KF, and shows that the VB-RAKF has better performance than the KF when dealing with observation data which has obvious gross errors, and similar performance as the KF when gross errors are small.     

A multi-objective binary-encoding differential evolution algorithm for proactive scheduling of agile earth observation satellites

A robust model and a Multi-objective Binary-encoding Differential Evolution (MBDE) algorithm are proposed in this paper for agile earth observation satellite proactive scheduling considering satellite resource failure and emergency task insertion. Firstly, considering that the reserved slack time in schedule can absorb uncertainties, two indicators are proposed: schedule profits and slack time, based on which, a robust model of proactive scheduling is established. Secondly, to solve the multi-objective model, solutions are represented via binary-encoding, mutation, crossover, and selection operators are re-designed, besides, an external archive update strategy is adopted to store elitist solutions in the evolution process, moreover, non-dominated Pareto set evaluation metrics are improved. Finally, computational results have demonstrated that, compared with NSGA-II and SPEA-2, the MBDE algorithm is able to obtain well-distributed solutions with good convergence more efficiently. The study can provide the method support for proactive scheduling of agile earth observation satellites.     

Optimal robust non-fragile Kalman-type recursive filtering with finite-step autocorrelated noises and multiple packet dropouts

In this paper, the optimal robust non-fragile Kalman-type recursive filtering problem is studied for a class of uncertain systems with finite-step autocorrelated measurement noises and multiple packet dropouts. The system state, measurement output and filter parameters are all subject to stochastic uncertainties or multiplicative noises, where the measurement noises are finite-step autocorrelated. When there exist multiple packet dropouts in the system output, the original system is converted into an auxiliary stochastic uncertain system by the augmentation of system states and measurements. The process noises and measurement noises of the auxiliary system are shown to be finite-step autocorrelated and cross-correlated. Then, a robust non-fragile Kalman-type recursive filter is designed that is optimal in the minimum-variance sense. The proposed filter is not only robust against the uncertainties in the system model and measurement model, but also non-fragile against the implementation error with the filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed method.     

Robust adaptive filtering method for SINS/SAR integrated navigation system

This paper presents a new robust adaptive filtering method for SINS/SAR (Strap-down Inertial Navigation System/Synthetic Aperture Radar) integrated navigation system. This method adopts the principle of robust estimation to adaptive filtering of observational data. A robust adaptive filter is developed to adaptively determine the covariance matrix of observation noise, and adaptively adjust the covariance matrix of system state noise according to the adaptive factor constructed based on predicted residuals. Experimental results and comparison analysis demonstrate that the proposed method cannot only effectively resist disturbances due to system state noise and observation noise, but it can also achieve higher accuracy than the adaptive Kalman filtering method.     

柔性关节空间机械臂的自适应滑模控制

探究一类时滞柔性关节空间机械臂鲁棒自适应滑模控制问题。针对该种空间机械臂具有强非线性特点，同时考虑系统的未建模动态与扰动以及时滞影响，提出一种新的鲁棒自适应滑模控制器。基于Lyapunov-Krasovskii泛函和线性矩阵不等式等凸优化方法，给出滑动模态的鲁棒渐近稳定条件，并证明系统状态在有限时间内到达滑模面。最后，三组仿真校验表明了所设计的控制器可行。     

Optimal robust linearized impulsive rendezvous

The optimization of time-fixed linearized impulsive rendezvous with control uncertainty is investigated. One performance index related to the variances of the terminal state error is defined as the performance index of robustness which is calculated by linear covariance method. The two-objective optimization problem of minimizing the total characteristic velocity and the performance index of robustness is formulated based on the Clohessy–Wiltshire (C-W) system and solved by the nondominated sorting genetic algorithm. The Pareto-optimal solution sets of one homing rendezvous mission are provided and the Pareto optimality is verified by comparing with the fuel-optimal and the robustness-optimal solutions. It is shown that the proposed approach can quickly investigate the relation between the fuel cost and the trajectory robustness, besides evaluate different rendezvous maneuver schemes.     

Going to Alpha Centauri B and setting up a Radio Bridge

How to exploit the Sun as a gravitational lens has been studied extensively during the last 20 years, especially by this author (Refs. 1, 2, 3, 4, 5, 6 and 7). In essence, a spacecraft dubbed FOCAL (an acronym for “Fast Outgoing Cyclopean Astronomical Lens”) should be launched in the direction of the sky opposite to the area of the sky we wish to see highly magnified both at radio and other frequencies. After FOCAL reached the minimal focal distance of 550 AU from the Sun, highly magnified radio images of celestial objects located on the opposite side of the Sun will automatically be produced. In this paper we apply the FOCAL mission concept to the goal of exploring the neighborhood of the Alpha Centauri B star, where the nearest exoplanet to the Solar system was recently discovered. We suggest that:     

Two freedom linear parameter varying μ synthesis control for flight environment testbed

To solve the problem of robust servo performance of Flight Environment Testbed(FET)of Altitude Ground Test Facilities(AGTF) over the whole operational envelope, a two-degree-offreedom μ synthesis method based on Linear Parameter Varying(LPV) schematic is proposed, and meanwhile a new structure frame of μ synthesis control on two degrees of freedom with double integral and weighting functions is presented, which constitutes a core support part of the paper. Aimed at the problem of reference command's rapid change, one freedom feed forward is adopted, while another freedom output feedback is used to meet good servo tracking as well as disturbance and noise rejection; furthermore, to overcome the overshoot problem and acquire dynamic tuning,the integral is introduced in inner loop, and another integral controller is used in outer loop in order to guarantee steady errors; additionally, two performance weighting functions are designed to achieve robust specialty and control energy limit considering the uncertainties in system. As the schedule parameters change over large flight envelope, the stability of closed-loop LPV system is proved using Lyapunov inequalities. The simulation results show that the relative tracking errors of temperature and pressure are less than 0.5% with LPV μ synthesis controller. Meanwhile, compared with non-LPV μ synthesis controller in large uncertainty range, the proposed approach in this research can ensure robust servo performance of FET over the whole operational envelope.     

A robust solution for hesitate phenomenon in pick up process of aerospace electromagnetic relay

As for aerospace electromagnetic relay (AEMR) which is of small batches and having difficulty in automatic production, the uncertainty phenomenon is remarkable due to excessive manual work involved in the assembly and adjustment processes. This kind of uncertainty may increase the coil voltage difference (CVD) caused by hesitate phenomenon in the pick up process of AEMR. Taking a certain type of AEMR for example, the CVD problem in the actual producing process has been studied in this paper. The primary cause of this issue, two-steps of armature motion (namely hesitate phenomenon) in the pick up process, has been found by analyzing the matching characteristics of electromagnetic and mechanical torques of AEMR. Through the optimization of the matching characteristics, the two-steps of armature motion problem is solved by robust design of the return reed which is a key part of AEMR. The validity of this research has been proved by the comparison of characteristics of AMER before and after the optimization.