多传感器融合状态估计方法综述

随着传感器网络技术的发展,多传感器融合状态估计凭借其鲁棒性、灵活性、可扩展性以及便于故障检测等优点,长期受到国内外学者的广泛关注,并取得了大量研究成果。数据融合的方法为融合状态估计奠定了理论基础,也是早期研究的主要方向,从20世纪70年代到20世纪末,相继发展出了集中式和分散式滤波架构及相应算法。无线通信技术的成熟以及一致性算法的出现使得分布式状态估计的研究进入了快车道,自2005年以来,大量基于一致性的分布式滤波算法被提出,其中不乏实用的经典方法和优秀的开创性方法。旨在梳理多传感器融合状态估计的发展,探究从数据融合到分布式滤波的内在联系,并对一些经典方法进行了总结。     

基于截断最小二乘和半正定规划的空间非合作目标相对位姿估计

面向空间在轨服务和碎片清除的重大应用需求,围绕空间光场复杂、空间目标尺度变化及相对姿态与位置强耦合等难题,提出了一种基于截断最小二乘与半正定规划的空间非合作目标相对位姿估计方法。基于TOF相机,首先进行体素下采样,提取快速点特征直方图(FPFH)特征,考虑目标的局部几何结构尺寸,计算两组FPFH特征的相似度并预测特征之间的对应关系,采用截断最小二乘和半正定规划方法对姿态和位置进行解耦,实现了空间非合作目标的相对位姿估计。使用非合作目标的3D模型进行仿真验证,仿真结果表明：该方法在三种不同高斯噪声强度下具有较好的估计特性,为后续的工程应用及在轨任务实施提供了理论与技术支撑。     

Design and experimental study of a new flapping wing rotor micro aerial vehicle

A three-wing Flapping Wing Rotor Micro Aerial Vehicle (FWR-MAV) which can perform controlled flight is introduced and an experimental study on this vehicle is presented. A mechanically driven flapping rotary mechanism is designed to drive the three flapping wings and generate lift, and control mechanisms are designed to control the pose of the FWR-MAV. A flight control board for attitude control with robust onboard attitude estimation and a control algorithm is also developed to perform stable hovering flight and forward flight. A series of flight tests was conducted, with hovering flight and forward flight tests performed to optimize the control parameters and assess the performance of the FWR-MAV. The hovering flight test shows the ability of the FWR-MAV to counteract the moment generated by rotary motion and maintain the attitude of the FWR-MAV in space; the experiment of forward flight shows that the FWR-MAV can track the desired attitude.     

Reliability estimation of rotary lip seal in aircraft utility system based on time-varying dependence degradation model and its experimental validation

With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach based on time-varying dependence analysis. The dependence between the two performance indicators of rotary lip seals, namely leakage rate and friction torque, is modeled by time-varying copula function with polynomial to denote the time-varying parameters, and an efficient copula selection approach is utilized to select the optimal copula function. Parameter estimation is carried out based on a Bayesian method and the reliability during the whole lifetime is calculated based on a Monte Carlo method. Degradation test for rotary lip seal is conducted and the proposed model is validated by test data. The optimal copula function and optimal order of polynomial are determined based on test data. Results show that this model is effective in estimating the reliability of rotary lip seals and can achieve a better goodness of fit.     

A multi-constraints based pose coordination model for large volume components assembly

In the assembly process of large volume product, engineering constraints limit the relative pose of components and serve as a standard for judging assembly quality. However, in the traditional process of target pose estimation, a general method is needed for establishing the correlation between engineering constraints and product pose, and it is difficult to evaluate pose by constraints comprehensively. Therefore, the process of target pose estimation and evaluation is separated. In this paper, a pose coordination model based on multi-constraints is proposed, which includes pre-processing, pose estimation, pose adjustment and evaluation. Firstly, engineering constraints are decoupled into 4 types of Minimum Geometrical Reference Constraints (MGRC), and the inequalities for solving target pose are formulated. Then the Constraint Coordination Index (CCI) is defined as the optimization objective to solve the target pose. Finally, with CCI as the numerical index, the target pose is evaluated to illustrate the quality of assembly. Taking the simulation experiment of wing-fuselage jointing as an example, the external and internal parameters of model are analyzed, and the pose estimation based on multi-constraints reduces the CCI by 12%, compared with the point-set-registration method.     

风电场雷达杂波动态重构抑制方法

随着风电场的大范围建设，风轮机杂波对雷达的干扰问题日益严重，常规杂波抑制方法难以有效解决风轮机杂波（WTC）干扰问题，因此提出了一种利用动态字典对风轮机杂波进行稀疏重构进而抑制的方法。首先，建立了WTC干扰下的雷达信号模型并分析了风轮机杂波的信号特征。其次，依据WTC的时频特征提出了一种微动参数粗估计方法，利用粗估计结果缩小了字典稀疏重构参数范围，在此基础上利用正交匹配追踪（OMP）算法对字典进行动态生成，并逐级更新字典原子。最后，通过动态字典对风轮机杂波信号进行稀疏重构，从而实现了对WTC的有效抑制。通过仿真实验，分析了风轮机杂波对目标检测的干扰影响，验证了基于动态稀疏重构的风电场杂波抑制方法在不同情况下的有效性。     

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

The current paper introduces a new multilayer perceptron (MLP) and support vector machine (SVM) based approach to improve daily rainfall estimation from the Meteosat Second Generation (MSG) data. In this study, the precipitation is first detected and classified into convective and stratiform rain by two MLP models, and then four multi-class SVM algorithms were used for daily rainfall estimation. Relevant spectral and textural input features of the developed algorithms were derived from the spectral MSG SEVIRI radiometer channels. The models were trained using radar rainfall data set colected over north Algeria. Validation of the proposed daily rainfall estimation technique was performed by rain gauge network data set recorded over north Algeria. Thus, several statistical scores were calculated, such as correlation coefficient (r), root mean square error (RMSE), mean error (Bias), and mean absolute error (MAE). The findings given by: (r = 0.97, bias = 0.31 mm, RMSE = 2.20 mm and MAE = 1.07 mm), showed a quite satisfactory relationship between the estimation and the respective observed daily precipitation. Moreover, the comparison of the results with those of two advanced techniques based on random forests (RF) and weighted ‘k’ nearest neighbor (WkNN) showed higher accuracy obtained by the proposed model.     

Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data

Attitude estimation is a critical component of the Attitude Determination and Control System (ADCS) of any satellite. It is used to convert the sensor observation data to an estimated attitude using filtering algorithms. However, in the presence of sensor faults, the ADCS fails to achieve the desired attitude accuracy. In this paper, the Fault Tolerant Extended Kalman Filter (FTEKF) is proposed to handle this imperfection. In accordance, various filtering steps are included in the FTEKF design to enhance both attitude estimation and sensor fault detection. The developed algorithm can detect and isolate any unexpected sensor faults in real time, which provides a reliable attitude estimation. A comparative study with the classical and robust Kalman filters is performed through numerical simulations in order to validate the effectiveness of the adopted filter in case of magnetometer fault data.     

地基光学图像中本体-帆板结构航天器姿态估计方法

提出一种利用地基光学图像估计空间目标姿态的方法。针对本体-帆板结构航天器外形结构特点，定义了一种不易遮挡的两轴结构特征，设计了地基光学图像中该特征的提取方法；根据航天器成像过程建立了特征点二三维几何投影方程，实现了航天器三维姿态的解算。利用单站序列图像，可获得航天器姿态变化角速度信息。在轨航天器的试验结果表明，本方法能有效地从地基光学图像估计出航天器姿态。     

水下复杂环境下基于SINS/USBL/DVL多源信息融合的组合导航算法

针对复杂水下声场环境下高精度、长航时导航与定位的需求,构建了捷联惯性导航系统(SINS)/超短基线(USBL)相对测量信息的观测方程和SINS/声学多普勒测速仪(DVL)的观测方程,提出了一种融合SINS/USBL/DVL多源信息的组合定位算法.为解决声学量测信息不确定引起的导航性能下降的问题,充分考虑水声野值所导致的...