基于Rodrigues参数的姿态估计算法

 以Rodrigues参数作为姿态描述参数提出一种快速的全姿态估计算法。Rodrigues参数具有简洁高效的特点,但它具有奇异性,不适用于大角度情况。首先将序贯旋转方法和Rodrigues参数相结合,提出了一种简洁、无奇异的姿态描述方法。然后应用该姿态描述方法,针对“矢量观测+陀螺”这种典型的姿态测量方案,讨论飞行器的姿态估计问题。在姿态估计算法设计中,给出了陀螺模型和观测矢量模型,推导了状态和状态误差协方差阵的预测方程和量测更新方程,并提出了预测方程的一种高效积分方法。仿真结果表明在估计精度等同的条件下,该姿态估计算法比四元数算法效率大约提高10%。     

基于EKF的小型涵道式无人机航姿系统算法研究

针对小型涵道式无人机,设计了一种基于扩展Kalman滤波的航姿估计算法。采用四元数作为状态变量,利用陀螺仪的输出构成状态方程,通过加速度计与磁阻传感器构造观测方程来进行扩展Kalman滤波解算。相对于通常的航姿估计算法,这种算法减少了运算量,更适合于基于嵌入式微处理器的航姿估计。实验结果表明这种算法有效的抑制了航姿系统的各种噪声与干扰,同时保证了姿态输出的精度与实时性,可以为小型无人机提供准确的航姿信息。     

IDENTIFICATION OF GYRO DRIFTS UNDER THREE AXIS ATTITUDE COUPLING

ＩＤＥＮＴＩＦＩＣＡＴＩＯＮＯＦＧＹＲＯＤＲＩＦＴＳＵＮＤＥＲＴＨＲＥＥＡＸＩＳＡＴＴＩＴＵＤＥＣＯＵＰＬＩＮＧＪＩＮＧＷｕｘｉｎｇ（荆武兴），ＷＡＮＧＸｕｅｘｉａｏ（王学孝），ＷＵＹａｏｈｕａ（吴瑶华）（ＨａｒｂｉｎＩｎｓｔｉｔｕｔｅｏｆＴｅｃｈｎ...     

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.     

Autonomous fault-tolerant attitude reference system using DTGs insymmetrically skewed configuration

A novel symmetrically skewed configuration for an attitude reference system (ARS) using three dynamically tuned gyros (DTGs) is developed. Simple schemes for autonomous detection and identification of a faulty DTG in real time and subsequent reconfiguration of the attitude estimation algorithm are proposed. The performance of the present configuration is shown to be better than that of configurations proposed earlier, and it is shown to have better features. It tolerates all types of failures of DTG failures, requires very simple computations, and gives less error in attitude estimate than the other configurations     

一种星敏感器-陀螺组合定姿的实时在轨标定方法

研究了一种星敏感器一陀螺组合定姿方式中的姿态敏感器误差的实时在轨标定方法。首先,选择直观的欧拉角作为姿态描述参数,根据星敏感器和陀螺的测量原理建立星敏感器一陀螺在轨标定的测量方程和状态方程,并以此建立数学模型。其次,采用简单高效的EKF（ExtendedKalmanFilter,扩展卡尔曼滤波）作为估值算法,进行了在轨标定数值仿真。对于航天器姿态定向中出现的姿态角和星敏感器安装角之间的耦合问题,通过在特定姿态通道上施加简单姿态机动实现了解耦。数值结果表明,该实时在轨标定方法,尤其是所提出的姿态角和星敏感器安装角解耦策略,可以实现对航天器姿态的实时精确估计以及对星敏感器安装误差、陀螺常值漂移和相关漂移等误差的实时在轨标定。该方法可用于航天器姿态测量设备的实时在轨标定和航天器姿态的高精度实时确定。     

基于模糊自适应卡尔曼滤波的大气数据辅助姿态算法

 针对中低精度航姿参考系统(AHRS)在机体机动时不能利用加速度计修正水平姿态,以及噪声统计特性随实际工作情况变化的问题,提出了一种基于模糊自适应卡尔曼滤波的大气数据辅助姿态解算的方法。首先,考虑大气数据系统和航姿参考系统的优势,利用真空速、攻角和侧滑角等大气数据信息对非重力加速度进行补偿,以辅助水平姿态解算;其次,基于模糊自适应卡尔曼滤波原理,对观测模型的参数进行估计和修正,以实现水平姿态的最优估计;最后,选取某型飞机的试飞数据进行仿真验证。仿真结果表明,该方法可使飞机的水平姿态估计精度达到1.3°,且在偏差较大时有明显的纠偏作用。因此,相对于无机动加速度补偿和常规卡尔曼滤波来说,该方法能够更好地进行姿态估计,具有一定的实用价值。     

Toward Accurate On-Ground Attitude Determination for the Gaia Spacecraft

The work presented in this paper concerns the accurate On-Ground Attitude (OGA) reconstruction for the astrometry spacecraft Gaia in the presence of disturbance and of control torques acting on the spacecraft. The reconstruction of the expected environmental torques which influence the spacecraft dynamics will be also investigated. The telemetry data from the spacecraft will include the on-board real-time attitude, which is of order of several arcsec. This raw attitude is the starting point for the further attitude reconstruction. The OGA will use the inputs from the field coordinates of known stars (attitude stars) and also the field coordinate differences of objects on the Sky Mapper (SM) and Astrometric Field (AF) payload instruments to improve this raw attitude. The on-board attitude determination uses a Kalman Filter (KF) to minimize the attitude errors and produce a more accurate attitude estimation than the pure star tracker measurement. Therefore the first approach for the OGA will be an adapted version of KF. Furthermore, we will design a batch least squares algorithm to investigate how to obtain a more accurate OGA estimation. Finally, a comparison between these different attitude determination techniques in terms of accuracy, robustness, speed and memory required will be evaluated in order to choose the best attitude algorithm for the OGA. The expected resulting accuracy for the OGA determination will be on the order of milli-arcsec.     

低成本捷联惯导不对称动态误差的神经网络补偿

 针对低成本捷联惯导系统(SINS)中陀螺动态误差的不对称性在角振动条件下造成姿态漂移的问题,设计了多层前向神经网络的补偿模型。在标定模型参数时,为降低对外部参考信号测量精度的要求,提出用姿态解算的最终误差作为网络优化目标的训练方法。由于最终的姿态误差不是网络的期望输出,无法采用有导师的训练方法,为此采用了微粒群优化算法。仿真实验结果表明:补偿后的陀螺动态误差的不对称度减小了一个数量级。     

星上光学有效载荷的两级隔振研究

为实现星上光学有效载荷的高成像性能,对星上光学有效载荷的两级隔振进行了研究。所谓两级隔振,即除了对控制力矩陀螺群(CMGs)等执行机构振动源进行隔振外,还在光学有效载荷和星体之间加入隔振装置。首先建立了含有两级隔振系统以及CMGs和太阳帆板的整星动力学模型,并采用ADAMS工程软件验证了所推导模型的正确性;其次,在合理假设的基础上简化模型,分别求得由扰动源到星体和有效载荷的传递函数矩阵,分析CMGs隔振平台参数变化对姿态控制系统的影响,选择合理参数分析两级隔振系统的频域特性;最后通过数值仿真分析了两级隔振系统在星上应用的可行性,并通过频谱对比分析两级隔振系统对光学有效载荷姿态稳定度的改善程度。     

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。     

Identification of the state-space model and payload mass parameter of a flexible space manipulator using a recursive subspace tracking method

The on-orbit parameter identification of a space structure can be used for the modification of a system dynamics model and controller coefficients. This study focuses on the estimation of a system state-space model for a two-link space manipulator in the procedure of capturing an unknown object, and a recursive tracking approach based on the recursive predictor-based subspace identification (RPBSID) algorithm is proposed to identify the manipulator payload mass parameter. Structural rigid motion and elastic vibration are separated, and the dynamics model of the space manipulator is linearized at an arbitrary working point (i.e., a certain manipulator configuration). The state-space model is determined by using the RPBSID algorithm and matrix transformation. In addition, utilizing the identified system state-space model, the manipulator payload mass parameter is estimated by extracting the corresponding block matrix. In numerical simulations, the presented parameter identification method is implemented and compared with the classical algebraic algorithm and the recursive least squares method for different payload masses and manipulator configurations. Numerical results illustrate that the system state-space model and payload mass parameter of the two-link flexible space manipulator are effectively identified by the recursive subspace tracking method.     

DOA estimation for attitude determination on communication satellites

In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system （GPS） attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit （LEO） satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio （SNR） with DOA estimation.     

Pseudo-linear inertial navigation algorithm

A new method is illustrated for processing the output of a set of triad orthogonal rate gyros and accelerometers to reconstruct vehicle navigation parameters (attitude, velocity, and position). The paper introduces two vectors with dimensions 4 × 1 as velocity and position quaternions. The navigation equations for strapdown systems are nonlinear but after using these parameters, the navigation equations are converted into a pseudo-linear system. The new set of navigation equations has an analytical solution and the state transition matrix is used to solve the linear time-varying differential equations through time series. The navigation parameters are updated using the new formulation for strapdown navigation equations. Finally, the quaternions of velocity and position are converted into the original position and velocity vectors. The combination of the coning motion and a translational oscillatory trajectory is used to evaluate the accuracy of the proposed algorithm. The simulations show significant improvement in the accuracy of the inertial navigation system, which is achieved through the mentioned algorithm.     

基于值域的多约束GNSS单频单历元定姿新算法

多天线增强了全球卫星导航系统（GNSS）单频单历元姿态测量解算模型的强度,但随着天线数量增加,模糊度维数成倍增加,从模糊度域确定搜索空间的计算量将显著增长。基于此,提出了基于值域的多约束多天线GNSS单频单历元姿态测量新算法：该算法将姿态约束融入值域搜索模型,利用姿态约束条件推导搜索步长,通过姿态域三维搜索确定模糊度搜索空间,以基于最优条件姿态解非迭代近似估计的方法固定模糊度。实验结果表明,新算法中模糊度搜索效率较原方法提高约65.8%,固定模糊度效率较标准迭代算法提高约95.3%,且与标准迭代算法性能相当;所提算法能够实现GNSS单频单历元的模糊度固定和载体全姿态测量,具有较高的正确率。     

Linearization errorʼs measure and its influence on the accuracy of MEKF based attitude determination method

Multiplicative Extended Kalman Filter (MEKF) is one of the most widely used satellite attitude estimation methods. However, the linearization error?s influence is an inherent limitation of this method. In this paper, we aim to analyze this linearization error in the typical satellite attitude determination system with star sensors and gyros. The formulation of linearization error is first derived and the curvature metric is then employed to measure the linearization error. Additionally, we show the reason why linearization error has influence on the performance of MEKF. Based on these analyses, we point out that star sensors? sampling frequency, initial estimated error and accuracy of gyro?s measurement model are the factors that could enlarge the system model?s linearization error. They all affect the linearization error and attitude determination accuracy by decreasing the predicted accuracy. More concretely, the influence of star sensor?s sampling frequency is large, while initial estimated error and gyro?s measurement error within a certain range have little influence on MEKF. Finally, combined with plenty of experiments, validity of the above analyses is verified.     

纬度未知条件下捷联惯导系统晃动基座的初始对准

针对纬度未知条件下捷联惯导系统(SINS)晃动基座的初始对准问题,提出晃动基座下的纬度估计算法和初始对准方法。前者通过惯性坐标系下两个不同时刻的重力加速度向量的夹角来求取纬度;后者利用惯性坐标系下的姿态更新来实时地反映载体在晃动干扰下的姿态变化,结合初始姿态的最优估计实现初始对准。理论分析表明,本文提出的纬度估计算法的误差主要由加速度计误差决定,陀螺误差和晃动干扰对其影响很小。仿真结果表明,本文提出的纬度估计算法和初始对准方法适用于纬度未知条件下晃动基座的初始对准。     

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.     

基于纵向滤波的星敏感器低频误差在线估计

多敏感器数据融合是获得更高精度姿态测量的有效方法,敏感器数据融合前必须先修正低频误差。首先,介绍了星敏感器低频误差（LFE）的产生机理及对其在线估计的必要性。其次,针对传统算法的不足,提出了基于纵向滤波的低频误差在线估计算法,该算法将传统低频误差估计问题转化为若干个常值误差估计问题,提高了估计精度。最后,给出了该算法具体实施方式,说明相关参数物理意义及选取原则。通过理论分析及仿真,算法误差可忽略不计。通过在轨数据仿真,星敏感器轨道周期低频误差可被消除。     

An adaptive attitude algorithm based on a current statistical model for maneuvering acceleration

A current statistical model for maneuvering acceleration using an adaptive extended Kalman filter(CS-MAEKF) algorithm is proposed to solve problems existing in conventional extended Kalman filters such as large estimation error and divergent tendencies in the presence of continuous maneuvering acceleration. A membership function is introduced in this algorithm to adaptively modify the upper and lower limits of loitering vehicles' maneuvering acceleration and for realtime adjustment of maneuvering acceleration variance. This allows the algorithm to have superior static and dynamic performance for loitering vehicles undergoing different maneuvers. Digital simulations and dynamic flight testing show that the yaw angle accuracy of the algorithm is 30% better than conventional algorithms, and pitch and roll angle calculation precision is improved by 60%.The mean square deviation of heading and attitude angle error during dynamic flight is less than3.05°. Experimental results show that CS-MAEKF meets the application requirements of miniature loitering vehicles.