Problems in formation and control of a required microacceleration level at spacecraft design,tests, and operation

In this paper, we consider the main aspects of a problem in formation and control of a required microacceleration level as the most important characteristic of the space laboratory intended for realizing the gravitational and sensitive technological processes. The estimation model and methodology to control and estimate the microaccelerations are presented that are necessary for the well-founded choice of the spacecraft parameters and carrying out their flight and space tests, when the new special-purpose space laboratories are designed and constructed.     

A problem of choosing a generalized parameter of flexible spacecraft structures to construct a fractal model of microaccelerations

Problems of revealing and forming a generalized parameter are considered to obtain an adequate estimation of microaccelerations aboard a spacecraft with the aid of a real part of the fractal Weierstrass-Mandelbrot function (WMF) at the phase identically equal to zero.     

Fractal assessment of microaccelerations at weak damping of natural oscillation in spacecraft elastic elements. II

Making use of the Weierstrass-Mandelbrot fractal function, some problems connected with the adequate assessment of microaccelerations aboard a spacecraft are considered. The ranges of values for the function parameters that make it possible to simulate the quasi-static component of microaccelerations are also determined.     

The problem of estimating microaccelerations aboard Foton-M4 spacecraft

The paper considers the special features of estimating microaccelerations aboard the Foton-M no. 4 spacecraft, which are connected with the decision on cancelling the spacecraft injection from the reference orbit into the operating one.     

一种评定电磁发射测量不确定度的简化方法

针对评定电磁发射测量不确定度,提出并讨论了以下几个观点:(1)传导发射评定结果仅与测量接收机的总误差有关;(2)应该确立一个国家标准辐射发射检测实验室。对同一个样品,由该实验室获得的测量结果应与其它检测实验室的测试结果进行严格比对;(3)只有在比对测试基础上,其它检测实验室进行辐射发射测量不确定度的评定才具有实际意义,且评定结果仅与天线系数和测量接收机的总误差有关。     

Receiver clock-based integrity monitoring for GPS precision approaches

The errors in the vertical position and clock bias estimates obtained from GPS pseudo-range measurements are highly correlated. Therefore, the error in a vertical position estimate can be predicted if we know the clock bias estimation error. The latter can be estimated if the clock bias changes smoothly and, therefore, predictably. The current technology appears capable of manufacturing clocks which can meet this smoothness requirement for airborne use within the constraints of size, weight, and cost. We discuss the theoretical basis and present empirical data from laboratory and field experiments with a commercial rubidium standard to explore the benefits of integrity monitoring for precision approaches based on the receiver clock.     

基于BP网络的武器装备参数估算

根据武器装备设计要求来确定某些参数往往涉及许多不确定因素。为了实现一些武器装备参数的定量化估算,本文基于BP神经网络计算模型提出了一种新的武器装备参数估算方法,并给出了实现这种方法的详细步骤。将该方法应用于导弹主要参数的估算,测试结果证明了此方法的正确性和可行性。该方法为武器装备的参数估算提供了新的途径。     

一种基于无线信号辅助的室内无死角定位算法

针对传统惯性导航系统定位误差随时间积累的问题,提出了一种基于无线信号辅助定位的室内无死角定位算法。该算法首先利用加速度计、陀螺仪、磁力计和气压计等传感器数据实现三维定位,然后利用无线信号对惯导定位中的位置偏差进行实时校正,再通过航向最优估计算法对航向误差进行修正,在位置和航向上增强惯导系统的实用性。利用实验室自主研发的微惯性测量单元固定在腰部脊椎位置进行实验验证,结果显示基于无线信号辅助的室内无死角定位算法精度达到1%以内,与纯惯导技术相比,能够提供更持久和准确的三维位置信息。     

基于无失效数据的某型发动机可靠性参数Bayes估计

针对装备寿命服从指数分布的情形,以失效率参数作为随机变量构建估计模型。考虑失效率的先验分布为 Gamma分布,在失效率的超参数均服从一定的均匀分布时,提出了失效率的多层 Bayes和期望 Bayes(ExpectedBayes,E-Bayes)估计方法,建立了失效率的多层 Bayes和 E-Bayes估计模型;结合某型装备发动机的无失效储存数据,计算了失效率的多层 Bayes和 E-Bayes估计值,推导了可靠度的多层 Bayes和 E-Bayes估计值。通过比较分析,可靠度的 2种估计结果都是稳健的,而后者略小于前者,且后者的极差比前者减小 81.4%。结果表明,采用 EBayes估计更易于计算,得到的结果更为准确稳健,且更适用于工程应用实际。     

一种改进的自适应故障诊断设计方法及其在飞控系统中的应用

基于自适应故障诊断观测器提出一种新的自适应故障估计设计方法。针对传统自适应故障估计设计方法难以满足故障估计性能的要求以及存在严格的等式约束增加了观测器设计的难度等问题,提出新的自适应故障估计设计方法,该方法不仅能够显著地提升故障估计的性能,而且通过运用不等式变化有效地避免了严格的等式约束,基于Lyapunov稳定性理论以矩阵不等式的形式给出了误差动态系统稳定的新的充分条件。最后,对某型飞控系统的仿真实验验证了所提方法的有效性。     

基于ap-Welch的随机角振动信号的 频谱估计方法研究

在转台的随机角振动试验中,频谱估计的精度是一个非常重要的指标,直接影响到频谱复现的精度.在分析经典的频谱估计方法的基础上,提出了一种基于ap-Welch频谱估计(基于全相位预处理的Welch频谱估计)的方法,从理论上证明了其比Welch频谱估计法具有更强的旁瓣抑制作用.仿真实验结果表明,ap-Welch频谱估计法能够有效提高频谱估计的精度,而且随着全相位阶数的增加,频谱估计的收敛特性也随之改善.     

一种基于非线性跟踪-微分器的角加速度估计方法

针对仅能获取角度信息的角加速度估计问题,基于卡尔曼滤波和非线性跟踪-微分器设计了一种角加速度估计算法。该算法利用卡尔曼滤波得到角速度的估计值,并以此为基础采用非线性跟踪-微分器对角加速度进行估计,通过对卡尔曼滤波与跟踪-微分器角加速度估计进行合理融合获得最终的角加速度输出。仿真结果表明,所设计的估计方法能满足视线角加速度的估计精度要求,具有一定的工程应用价值。     

无人直升机视觉着陆中的运动状态估计算法

对无人直升机(UH)视觉着陆中基于视觉图像处理的运动状态估计问题进行了研究。介绍了视觉着陆原理,分析了运动估计、特征图像处理与着陆控制间的关系,推导并建立了UH相对着陆平台位姿估计算法、线速度与角速度估计算法。相邻两帧图像对应特征点像点位置为位姿估计算法提供数据,一帧图像特征点像点位置及其对应像点平移速度为线速度与角速度估计算法提供数据。利用UH着陆控制仿真数据模拟UH着陆运动过程中像点位置及其对应平移速度的视觉图像处理结果。仿真验证了运动状态估计算法,结果表明所提出的运动状态估计算法能有效地利用视觉图像处理结果数据估计出UH的位置、姿态、线速度和角速度。     

竞争性故障模型可靠性评估的非参数估计方法

针对航空发动机现场数据的可靠性评估面临着小子样与随机删失问题,对可靠性评估中的非参数估计方法进行了对比分析.应用蒙特卡罗方法,在竞争性故障模型下,设计了一种对比可靠性评估方法优劣性的仿真方法.该方法以三重威布尔分布为例,通过模拟产生具有随机删失特点的航空发动机现场故障数据,分别对比4种可靠性评估非参数估计方法的优劣性.最后通过一个工程应用案例验证了模型的有效性.仿真结果表明:在三重威布尔竞争性故障模型下,非参数估计方法的优劣顺序依次是Kaplan-Meier估计、平均秩次法、Herd-Johnson估计、Nelson-Aalen估计.      

装备研制费用参数估算方法研究

参数法是进行装备研制费用估算的有效方法之一.介绍了参数费用估算的历史和基本原理,分析了装备研制费用的主要驱动因素,将其作为估算参数,并给出了装备研制费用参数估算的基本流程.最后,基于国际先进的参数估算软件True Planning,对国外新一代直升机进行了参数估算的实例研究,显示了参数估算的有效性.     

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.     

Estimation Using Stochastic Feedback with Applications to Integrated Navigation Systems

This paper discusses an approach to linear estimation through use of a "control" fed back into the system to cancel out the effect of disturbances or error signals. Although this approach has very restricted application, it has found important usage in integrated navigation systems where one subsystem is an inertial measurement system. This approach is shown to be suboptimal and is compared with the optimal with respect to estimation accuracy and sensitivity to modeling errors. The feedback approach to estimation is shown to be similar to error estimation and correction in which the error states of the system are estimated and external correction applied. For discrete estimation using the feedback approach it is shown that error variance and Kalman gains for one-stage prediction should be used. Two examples are considered which compare the feedback approach to the optimum estimation approach. The system of the first example is quite simple, but provides simple analytical comparisons of the two estimation approaches. The second example system consists of a single-axis inertial guidance system and an independent position measuring system. Accuracy and sensitivity to modeling errors are compared. Other advantages and disadvantages of the two estimation approaches are discussed.     

A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation

Gas-path performance estimation plays an important role in aero-engine health management, and Kalman Filter(KF) is a well-known technique to estimate performance degradation. In previous studies, it is assumed that different kinds of sensors are with the same sampling rate, and they are used for state estimation by the KF simultaneously. However, it is hard to achieve state estimation using various kinds of sensor measurements at the same sampling rate due to a complex network and physical characteristic differences between sensors, especially in an advanced multisensor architecture. For this purpose, a multi-rate sensor fusion using the information filtering approach is proposed based on the square-root cubature rule, which is called Multi-rate Squareroot Cubature Information Filter(MSCIF) to track engine performance degradation. Soft measurement synchronization of the MSCIF is designed to provide a sensor fusion condition for multiple sampling rates of measurement, and a fault sensor is isolated by maximum likelihood validation before state estimation. The contribution of this paper is to supply a novel multi-rate informationfilter approach for sensor fault tolerant health estimation of an aero-engine in a multi-sensor system. Tests are conducted for aero-engine performance degradation estimation with multiple sampling rates of sensor measurement on both digital simulation and semi-physical experiment.Experimental results illustrate the superiority of the proposed algorithm in terms of degradation estimation accuracy and robustness to sensor failure in a multi-sensor system.     

Mini-UAV altitude estimation using an inertially stabilized payload

A novel method is introduced for autonomous attitude estimation of a mini unmanned aerial vehicle (UAV) carrying an inertially stabilized payload. The method is based on utilizing the outputs of rate gyros normally used to inertially stabilize the payload, and other data that is normally available from conventional aircraft-mounted sensors. A decentralized estimation algorithm is developed, which uses the aircraft/payload mathematical models to bound the estimation errors. Exploiting modern multiprocessor computer technology, the new estimation algorithm comprises two parallel extended Kalman filters (EKFs) and a data fusion algorithm. Real-time experimental tests, incorporating a payload model with real rate gyros mounted on a three-axis flight table, have validated the feasibility of the concept. The theoretical and experimental investigation demonstrates that the estimation algorithm is capable of estimating the attitude angles with an estimation error not exceeding 1 deg, at output rates of 13 Hz, thus constituting a viable substitute for the conventional vertical gyroscope     

Hard-constrained versus soft-constrained parameter estimation

The paper aims at contrasting two different ways of incorporating a priori information in parameter estimation, i.e., hard-constrained and soft-constrained estimation. Hard-constrained estimation can be interpreted, in the Bayesian framework, as maximum a posteriori probability (MAP) estimation with uniform prior distribution over the constraining set, and amounts to a constrained least-squares (LS) optimization. Novel analytical results on the statistics of the hard-constrained estimator are presented for a linear regression model subject to lower and upper bounds on a single parameter. This analysis allows to quantify the mean squared error (MSE) reduction implied by constraints and to see how this depends on the size of the constraining set compared with the confidence regions of the unconstrained estimator. Contrastingly, soft-constrained estimation can be regarded as MAP estimation with Gaussian prior distribution and amounts to a less computationally demanding unconstrained LS optimization with a cost suitably modified by the mean and covariance of the Gaussian distribution. Results on the design of the prior covariance of the soft-constrained estimator for optimal MSE performance are also given. Finally, a practical case-study concerning a line fitting estimation problem is presented in order to validate the theoretical results derived in the paper as well as to compare the performance of the hard-constrained and soft-constrained approaches under different settings