离心机静态姿态误差的测试

将电子水平仪安装在精密离心机仪器工作基面上，并分别旋转主轴及方位轴，测试对于水平面的角度，经数据处理，得出主轴轴线对水平面的垂直度及主轴和水平轴处于初始位置时方位轴轴线与水平的面的垂直度，如果预先已测出水平轴轴线与方位轴轴线的重直度，通过坐标系之间的姿态关系，可求出主轴轴线与水平轴轴线之间的垂直度及水平轴的零位误差。     

三轴转台误差对加速度计误差模型系数标定精度的影响

为了更精确地在三轴转台上标定惯性组合中的加速度计,建立了三轴转台的误差模型,推导了加速度计输出与转台误差、加速度计安装误差间的关系,分析了转台误差对加速度计输出计算精度的影响,建立了转台误差与加速度计误差模型系数的标定误差之间的联系.分析结果表明转台误差对标度因子KI以及交叉耦合误差KIO、KOP、KIP影响较大.文中方法对确定转台的精度指标和进一步提高惯性仪表标定精度以及误差补偿提供了一定依据.     

加速度计序贯式测试方法研究

介绍了加速度计在离心机上的序贯式测试方法。通过加速度计在离心机上一次安装即可实现加速度计 1g重力场标定、离心机静态半径测试和加速度计全量程试验。这是一种非常有应用前景的试验方法     

基于FD的微小型姿态系统的姿态估计算法

分别利用微惯性测量单元(MIMU,Micro Inertial Measurement Unit)中的3个加速度计与3个陀螺仪对载体的姿态角进行估计,同时,搭建捷联惯性导航系统,建立姿态误差方程,使用卡尔曼滤波估计载体姿态误差角.构造残差及统计量,利用状态残差检验的故障检测方法,对载体的运动状态进行分离,判断加速度计估计出的姿态角的可用性,对姿态角进行融合.既保证了姿态估计系统的动态性能,又提高了估计精度.由于使用微电子机械系统(MEMS,Micro Electro Mechanical System)惯性器件,使得姿态估计系统的体积小、重量轻、造价低,特别适于微小型载体使用.      

机抖激光陀螺捷联惯性测量组合的标定方法研究

为了提高激光陀螺捷联惯性导航系统的导航准确度,对机抖激光陀螺的抖动偏频产生的惯性仪表输出误差的特点进行了分析,并在标定过程中有效地进行了补偿,提高了陀螺和加速度计的标定准确度。     

"嫦娥一号"卫星轨控标定方法研究与实现

在航天测控任务中,对轨控效果进行标定并合理利用可以实现更为精准的轨道控制.提出了一种综合利用控前控后精密轨道、轨控过程遥测姿态数据、遥测加速度计测量数据对沉底发动机、轨控发动机、加速度计刻度系数进行标定的方法;介绍了该方法在中国首次月球探测任务中的应用情况;最后分析了标定结果对定轨及定姿精度的敏感程度,从而在理论上进一步说明在后续深空探测中利用精密轨道进行轨控标定的可行性和重要性.     

交直流转换电路的电路参数误差分析

为了达到更好的交直流转换效果,针对整流输出准确度影响较大的三种元器件(运算放大器、电阻以及二极管),分别进行电路误差分析,将输出结果与理想状态下全波精密整流电路的输出进行比较,总结精密整流电路减小误差的方法,为全波整流电路设计中提高交直流转换准确度提供参考.经电路测试验证,对电压有效值(0.4～4)V,频率(1～50)...     

无依托状态加速度计的新型标定方法

为解决加速度计性能参数时变性的问题,提出了无依托状态下加速度计标定方法.在无需借助转台等传统标定设备、无需拆卸惯性元件的条件下,充分利用惯导系统(INS,Inertial Navigation System)自身资源,以静基座初始对准获得的准确姿态信息为前提,利用当地重力g作为标定基准,考虑到误差模型非线性的特点,引入非线性寻优策略辨识零位偏差,将误差模型蜕变为线性后,运用线性最小二乘方法辨识安装误差矩阵和刻度因数误差,从而实现加速度计关键参数标定.数值仿真结果显示:经过标定后加速度计测量误差可减小20倍,说明在无依托状态下具有工程实用价值.      

星敏感器低频误差分析

介绍星敏感器的误差分类、低频误差定义、误差产生原因及其测试标定方法等.星敏感器输出姿态周期性误差的主要原因为视场空间误差和热弹性变形误差,典型星敏感器采取相应的解决措施后,低频误差可控制在0.8″以内.     

压缩映射原理在平台惯导系统加速度计标定中的应用

传统的平台惯导系统加速度计所采用的自标定方法受到加速度计零偏预装值的影响存在着一定的误差,而且加速度计标定参数准确性的验证方法也较为烦琐,不利于操作。基于压缩映射原理,针对平台惯导系统加速度计提出了一种迭代式标定方法,消除了传统加速度计自标定方法中的误差,同时提出了一种简单、有效地验证加速度计标定参数准确性的方法,并对这种迭代式加速度计标定方法的收敛性进行了证明以及试验验证。     

微硅加速度传感器的动态特性补偿方法研究

提出了一种用以扩展加速度传感器使用频率范围的动态特性补偿方法,其基本原理是根据加速度传感器的输入输出传递函数,构造出一个基于硬件的补偿网络,这个补偿网络的传递函数的零极点分别与加速度传感器的传递函数的极零点相抵消,从而使由加速度传感器输出的信号经过补偿环节后其动态特性得到补偿,扩展了加速度传感器的使用频带,同时并不要求加速度传感器处于临界阻尼状态。     

基于电流注入法的加速度表测试方法研究

针对不同结构的加速度表 ,从理论上研究了利用电流注入法模拟加速度表运动特性的方法 ,研究了加速度表接入闭环测试系统后的相关问题 ,为加速度表的动态测试提供了新的方法     

Event-triggered attitude control of spacecraft

The problem of spacecraft attitude stabilization control system with limited communication and external disturbances is investigated based on an event-triggered control scheme. In the proposed scheme, information of attitude and control torque only need to be transmitted at some discrete triggered times when a defined measurement error exceeds a state-dependent threshold. The proposed control scheme not only guarantees that spacecraft attitude control errors converge toward a small invariant set containing the origin, but also ensures that there is no accumulation of triggering instants. The performance of the proposed control scheme is demonstrated through numerical simulation.     

The attitude inversion method of geostationary satellites based on unscented particle filter

The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.     

Testing a new multivariate GNSS carrier phase attitude determination method for remote sensing platforms

GNSS (Global Navigation Satellite Systems)-based attitude determination is an important field of study, since it is a valuable technique for the orientation estimation of remote sensing platforms. To achieve highly accurate angular estimates, the precise GNSS carrier phase observables must be employed. However, in order to take full advantage of the high precision, the unknown integer ambiguities of the carrier phase observables need to be resolved. This contribution presents a GNSS carrier phase-based attitude determination method that determines the integer ambiguities and attitude in an integral manner, thereby fully exploiting the known body geometry of the multi-antennae configuration. It is shown that this integral approach aids the ambiguity resolution process tremendously and strongly improves the capacity of fixing the correct set of integer ambiguities. In this contribution, the challenging scenario of single-epoch, single-frequency attitude determination is addressed. This guarantees a total independence from carrier phase slips and losses of lock, and it also does not require any a priori motion model for the platform. The method presented is a multivariate constrained version of the popular LAMBDA method and it is tested on data collected during an airborne remote sensing campaign.     

Central difference predictive filter for attitude determination with low precision sensors and model errors

Attitude determination is one of the key technologies for Attitude Determination and Control System (ADCS) of a satellite. However, serious model errors may exist which will affect the estimation accuracy of ACDS, especially for a small satellite with low precision sensors. In this paper, a central difference predictive filter (CDPF) is proposed for attitude determination of small satellites with model errors and low precision sensors. The new filter is proposed by introducing the Stirling’s polynomial interpolation formula to extend the traditional predictive filter (PF). It is shown that the proposed filter has higher accuracy for the estimation of system states than the traditional PF. It is known that the unscented Kalman filter (UKF) has also been used in the ADCS of small satellites with low precision sensors. In order to evaluate the performance of the proposed filter, the UKF is also employed to compare it with the CDPF. Numerical simulations show that the proposed CDPF is more effective and robust in dealing with model errors and low precision sensors compared with the UKF or traditional PF.     

Sensor-fault tolerant attitude determination using two-stage estimator

Satellite attitude determination accuracy significantly drops when sensor-fault occurs. Hence, a proper mitigation strategy to detect sensor-fault and accurately estimate corresponding fault magnitudes is mandatory for robust and accurate attitude determination. In this paper, a novel sensor-fault tolerant precise attitude estimator is proposed consisting of two stages. In the first stage, sensor-fault is detected, and the associated sensor parameter change is roughly estimated using an interacting multiple-model (IMM) approach. Subsequently, the second stage is triggered. The sensor parameter change is precisely estimated with a new sensor-parameter-augmented filter. This is defined as a selectively augmented extended Kalman filter (SAEKF) in this paper. The conventional augmented extended Kalman filter (AEKF) is computationally more expensive than the proposed SAEKF. The SAEKF augments only the sensor parameters affected by sensor-faults, not the full sensor parameters, into the state vector. This leads to a significant computational time-saving. A transition method from the first stage to the second stage is also investigated. Numerical simulation results demonstrate that the proposed two-stage approach has smaller attitude determination errors than the existing algorithms, ranged from 21.7% to 88.8%, in cases with gyro scale factor error or misalignment.     

加速度计加速退化机理一致性边界确定方法

以加速退化模型——Arrhenius模型为研究对象,发现加速度计在加速试验过程中,保持加速机理不变的应力与退化轨迹斜率存在密切关系.通过针对退化轨迹模型分别为一次函数、指数函数和幂函数三种常见情况,从激活能不变角度推导出保证加速度计加速机理不变的应力-斜率公式,然后基于退化轨迹斜率区间检验提出了一种加速机理一致性条件确定方法,最后根据加速度计恒定高温标度因数稳定性退化仿真试验数据,准确得到了保持加速度计标度因数稳定性退化机理一致的应力边界,验证了该方法的可行性.