A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding

X-ray pulsar-based navigation (XPNAV) is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint prob-ability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC) and nonlinear least squares (NLS) estima-tors, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML) estimators.     

基于卫星和星敏感器的冗余激光惯组在轨标定

采用高精度卫星导航速度、位置信息以及星敏感器提供的姿态信息设计十表冗余捷联惯组的标定模型,包含陀螺和加速度计的零次项和标度因数,对卫星和星敏感器辅助的冗余激光陀螺捷联惯组进行实时在轨标定.利用标准Kalman滤波和Sage-Husa自适应滤波作为估计算法,对十表冗余捷联惯组参数进行在线估计.数值仿真结果表明:参数标定精度均在7％以内,是一种实时的在轨标定方法,满足误差补偿要求.冗余惯组在轨标定方法为航天器高精度定姿和定轨提供了一种理论参考.     

基于雷达航迹的航空器质量估算

为保障基于轨迹运行的顺利实施,必须提高四维航迹预测的精度,而四维航迹的精准预测依赖于航空器质量准确估算。鉴于此,构建并分析了航空器能量模型;基于雷达航迹与航空器基础资料( BADA),提出了新型的航空器质量估算方法与步骤;利用最小二乘算法求解了航空器质量的估计值;分别基于预测航迹、雷达轨迹与QAR数据,采用相对误差作为评价指标,实施验证与分析。验证结果表明,提出的方法可将航空器质量估算误差控制在5%以内,从而能够有效地提高航迹预测精度。     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

某型装备轴承件无失效时的可靠性参数估计

针对寿命服从威布尔分布的某型装备轴承件在无失效数据时的可靠性参数估计问题,首先,以失效概率为待估参数,取其先验分布为Beta分布,在2个超参数的先验密度函数为2种不同情形下,建立了失效概率的2种EBayes估计模型,分析了稳健性、渐近性和单调性;然后,对威布尔分布参数进行了加权最小二乘估计,进而建立了可靠度的2种E-Bayes估计模型,分析了稳健性和单调性;最后,结合实例数据进行了可靠性参数估计与分析,指出第2种估计模型更加合理有效。     

Vision-based pose estimation for cooperative space objects

Imaging sensors are widely used in aerospace recently. In this paper, a vision-based approach for estimating the pose of cooperative space objects is proposed. We learn generative model for each space object based on homeomorphic manifold analysis. Conceptual manifold is used to represent pose variation of captured images of the object in visual space, and nonlinear functions mapping between conceptual manifold representation and visual inputs are learned. Given such learned model, we estimate the pose of a new image by minimizing a reconstruction error via a traversal procedure along the conceptual manifold. Experimental results on the simulated image dataset show that our approach is effective for 1D and 2D pose estimation.     

根据两颗导航星信息估计捷联惯导系统误差的一种方法

针对高机动短时间飞行的飞行器,介绍了一种根据它相对2颗导航卫星的伪距离和伪速度信息,估计捷联惯导系统定位和定速度误差的方法.考虑到由确定飞行器相对每颗星的径向距离和速度的非线性方程施加的约束,根据这些误差矢量长度最小值的条件确定误差值.用空间解析几何法得出了计算捷联惯导系统误差估值的最终算法,这种算法能给出非线性最小值问题的精确解.     

基于距离像特征的复合速度估计算法研究

首先分析了步进频率宽带信号混频处理原理和目标速度对距离像的影响。在此基础上，提出了基于距离像熵和距离像对比度的速度估计算法，详细分析了这两种算法的数学原理、步骤、效果、适用条件等。最后，基于这两种算法又提出了复合速度估计算法，大大提高了速度估计精度。     

航天型号项目成本估算方法研究与实现

介绍了国内外航天型号研制项目成本估算的研究现状,分析了航天型号研制项目成本估算的作用与特点。研究了参数成本估算法、工程成本估算法、类比成本估算法、外推成本估算法、仿真模型法和综合成本估算法等方法。给出了用综合成本估算法估算的风云四号气象卫星研制成本算例。     

一种基于机动辨识预测的空空导弹导引律

现有的空空导弹导引头在有噪声和干扰的环境下获得目标精确信息存在时间延迟,且新一代目标的机动能力更强,不对导弹加以补偿会造成较大脱靶量,所以需对目标状态有效预测。针对新一代目标规避空空导弹常用的大机动模式,为满足新一代空空导弹发展需求,设计了一种新型复合导引律。从目标自身出发,研究高机动目标规避导弹采用的典型机动形式,对机动轨迹进行离线建模,构建具有扩展能力的目标机动模型库。设计自适应滤波器对测量噪声进行降噪。同时,利用模型库设计了机动辨识预测器,对目标实际机动进行在线辨识。基于在线辨识的结果对目标机动进行预测,并对时间延迟进行补偿和修正,实现对高机动目标的精确打击。仿真结果表明:该方法对不同类型的机动目标均有较高的预测精度和命中精度。