Ultimate IR Horizon Sensor

The accuracy of presently available IR horizon sensors is not sufficient to meet the stringent attitude sensing and control requirements for future remote sensing and meteorological satellites. The different sources of error in a horizon sensor are analyzed. The accuracy of the sensor is presently limited by the detector noise. Use of HgCdTe in place of an immersed bolometer detector, which is used in conventional horizon sensors eliminates many of the errors. Hence, it is possible to design an ultimate IR horizon sensor whose accuracy is limited only by the uncertainty of the Earth horizon. Comparison of performances of the two types of detectors for horizon sensing is given and possible configurations of sensor using this detector are discussed.     

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。     

跟踪弹道导弹时预警卫星姿态前馈协同控制

基于角动量守恒定理,推导了跟踪弹道导弹时,具有活动部件的预警卫星姿态前馈协同控制。该控制算法基于角动量守恒方程估计红外相机运动产生的角动量扰动以及为抑制该扰动所需的期望飞轮转速,将期望飞轮转速与实际转速的偏差作为前馈信号加入到传统控制系统中,推导出预警卫星姿态前馈控制模型。最后通过数值仿真验证了控制方法,仿真结果与理论分析具有很好的一致性。并且该控制方法简单、可靠,能够适应卫星在轨实时控制。     

捷联惯导系统圆锥误差分析

捷联惯导系统由于数学平台隔离作用的不完善,当运载体沿机体坐标轴存在同频率的角振动和线振动时,角振动引起的整流效应将在姿态更新计算中产生圆锥误差,角振动和线振动引起的整流效应将在速度计算中产生划桨误差,在位置计算中产生涡卷误差。文中详细分析了圆锥误差产生机理,针对某型飞机装备 SIGMA50 GPS/SINS 组合导航系统对底座安装的精度要求,分析了安装误差、陀螺频带不够宽、姿态更新率过低对姿态精度的影响,并对维护捷联惯导系统提出建议。     

IDENTIFICATION OF GYRO DRIFTS UNDER THREE AXIS ATTITUDE COUPLING

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

Terminal Seeker Pointing-Angle Error at Target Acquisition

Missile terminal guidance seekers that employ optical, infrared, or radar sensors to acquire, lock-on, and track their target are subject to a missile-to-target line-of-sight pointing error during the acquisition phase. The error is due primarily to missile navigation errors (attitude and position) and inaccuracies in predicting the target location. The computational process to obtain the seeker-to-target pointing vector is formulated. Linear perturbation ion of the pointing vector yields the pointing-angle error tions.quaons. A simple quantitative example is given.     

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.     

基于深度学习的非合作航天器姿态估计

针对空间非合作航天器姿态测量时受光照和地球背景影响大的问题,提出了一种基于卷积神经网络的端到端姿态估计方法.在该方法中,主干网络采用AlexNet与ResNet.首先,移除主干网络末端的全连接层,并列连接3个全连接层,采用三分支网络分别对姿态角进行估计.然后,设计了将分类问题与回归问题相结合的损失函数,通过分类方法将姿态估计限定在某一范围内,再使用回归方法进一步微调姿态.姿态分类损失函数确定姿态角度基准点,姿态回归损失函数对估计角度进行微调.相较于仅采用回归方法进行姿态估计,此方法能够有效减小姿态估计平均绝对误差、标准差与最大误差.实验对比了不同主干网络的测量精度,平均绝对误差在0.376°～0.746°之间,最优标准差为0.474°.     

A view finder control system for an earth observation satellite

A real time TV view finder is used on-board a low earth orbiting (LEO) satellite to manually select targets for imaging from a ground station within the communication footprint of the satellite. The attitude control system on the satellite is used to steer the satellite using commands from the groundstation and a television camera onboard the satellite will then downlink a television signal in real time to a monitor screen in the ground station. The operator in the feedback loop will be able to manually steer the boresight of the satellite's main imager towards interested target areas e.g. to avoid clouds or correct for any attitude pointing errors. Due to a substantial delay (in the order of a second) in the view finding feedback loop and the narrow field of view of the main imager, the operator has to be assisted by the onboard attitude control system to stabilise and track the target area visible on the monitor screen.This paper will present an extended Kalman filter used to estimate the satellite's attitude angles using quaternions and the bias vector component of the 3-axis inertial rate sensors (gyros). Absolute attitude sensors (i.e. sun, horizon and magnetic) are used to supply the measurement vectors to correct the filter states during the view finder manoeuvres. The target tracking and rate steering reaction wheel controllers to accurately point and with high agility stabilise the satellite, will be presented. The controller reference generator for the satellite-to-target attitude and rate vectors, as used by the reaction wheel controllers, will be derived.     

利用Singer模型的无陀螺姿态和角速度估计

 给出了一种利用Singer跟踪模型的扩展卡尔曼滤波器 (ExtendedKalmanFilter) ,用于无陀螺姿态和姿态角速度估计。在滤波器中 ,姿态和姿态误差分别由姿态四元数和误差四元数表示 ,而姿态角加速度由一阶Markov过程描述 ,从而避免采用姿态动力学模型。利用数值仿真计算验证了滤波器的性能。在所有的仿真过程 ,滤波器显示出快速收敛能力。稳态估计误差主要由测量更新频率和精度决定。     

基于遗传算法的机器人负载重力补偿优化算法研究

航空航天装配领域,利用安装在机器人末端的六维力传感器来感知外力是实现工业机器人柔顺装配的关键技术之一,而负载的存在会干扰对外力的感知。针对工业机器人末端负载的重力补偿,提出一种基于遗传算法的重力补偿优化算法。此方法以误差平方和最小为目标建立了最优解模型,利用遗传算法求解,最终可以在不使用测量仪器的情况下,估计力传感器安装偏角,提高重力补偿精度。同时设计了特定的机器人测量姿态来减少系统误差。试验表明,优化算法可以补偿任意角度的力传感器安装偏角,与补偿前相比,各方向最大重力补偿误差及平均重力补偿误差都有所减小。     

多测速系统中系统误差实时估计与校准算法

在实际目标跟踪系统中,测量设备都存在系统误差,会导致跟踪滤波精度显著下降。针对多测速系统,对其测速系统误差进行了简化数学建模;然后将其增广为状态变量,应用扩维无迹卡尔曼滤波对目标运动状态和系统误差进行联合估计,以实时校准系统误差、提高状态估计精度。在存在主副站2类系统误差的条件下,设定恒定和线性时变2类系统误差场景,对算法进行仿真分析。仿真结果表明,算法在2类系统误差情形下都能有效校准系统误差,位置、速度滤波精度可提高80%以上;尤其是当系统误差恒定时,算法可完全消除系统误差的影响。     

基于ECEF的广义最小二乘误差配准技术

 雷达组网数据处理首先要进行误差配准,来准确地估计和消除系统误差。传统的误差配准技术多基于球极投影,当雷达之间距离较远时,给配准结果引入一定的误差。基于地球中心坐标系(ECEF),提出了一种广义最小二乘的ECEF-GLS误差配准技术,较好地解决了远距离误差配准问题,误差分析表明,如果忽略模型线性化引入的误差,配准结果达到了CRLB下限。最后,使用仿真数据验证了算法的性能,并和Zhou提出的基于ECEF坐标系的最小二乘ECEF-LS误差配准算法进行了比较。     

基于电磁波三维结构向量的飞行器姿态估计

以电磁波三维空间结构向量为参照的飞行器姿态/航向测量研究，可弥补空间参照物缺乏，丰富空间飞行器姿态/航向测量工具。本文根据各缺损电磁矢量传感器姿态位置与接收信号之间的变化规律，建立飞行器载电磁矢量传感器阵列导向矢量。根据协同导航的多个信号空间谱和最大化，实现平台姿态/航向测量。飞行器多位置的多个传感器共同测量姿态可避免遮挡，获得更高姿态精度的同时拓展了系统的适用领域。接收电磁信息完备状态下，不需导航信号，测绘平稳的杂波就能作为姿态基准。仿真试验验证了姿态估计的有效性。     

星敏感器低频误差与陀螺漂移离线校正方法

获取高精度事后姿态数据是提高遥感平台成像质量的必要条件之一,离线处理可有效降低敏感器测量误差,从而获得更高的姿态确定精度。基于滤波的校正方法中,星敏感器低频误差(LFE)与陀螺漂移将产生耦合影响导致校正精度低,本文针对该问题推导了耦合误差的数学模型,并设计了一种两步双向平滑事后处理算法,将陀螺漂移与低频误差分两步校正,通过反复滤波剥离陀螺漂移与低频误差。同时,针对低频误差参数收敛速度慢、噪声参数调节困难的问题,利用一种基于极大似然估计(MLE)的固定窗口自适应双向滤波算法进行处理以获得更好的噪声估计,提高了收敛速度和收敛精度。文中仿真工况下,离线姿态确定精度可达到0.8″(3σ),低频误差参数完全收敛时间不超过4个轨道周期。     

Architectures and GPS/INS integration: impact on missionaccomplishment

The GPS (Global Positioning System) signal contains information which, when properly combined with information from INS and other sensors, provides exceptionally high accuracy position, velocity, attitude, and time measurements. These ten elements of information (three each in position, velocity, and attitude, and one in time) are common, in various combinations, to most avionics functions. When viewed from a system perspective, this high-precision information can be thought of as an integration basis, or a reference set, which offers opportunities for reconfiguration of the offensive, defensive, communication, navigation, and other sensors. Various integration architectures for fusion of these sensors can inherently enhance, enable, or severely limit these potential mission capabilities. The choice of integration architecture, can directly and profoundly affect performance, cost of integration, cost of ownership, and exploitation of much greater mission capability. This is illustrated by an example     

Novel attitude determination method by integration of electronic level meter,INS, and low-cost turntable for level attitude evaluation and calibration of INS

Attitude references are greatly needed for the evaluation and calibration of Inertial Navigation Systems (INSs), which are widely used in gravimeter, marine, and aeronautical navigation. High-accuracy turntable, INS, and Global Navigation Satellite System have been utilized to verify the performance of relatively low-accuracy INS. The accuracy requirement of the attitude reference continuously increases with the rapid improvement of inertial sensors and navigation algorithms. However, the cost of attitude determination system increases rapidly with the increase of attitude accuracy requirement. To solve this limitation, the integration of level meter, INS, and low-cost turntable is proposed to provide level attitude, such as roll and pitch. The turntable is utilized to rotate the INS. An integration model of the level meter and INS is built to estimate the level attitude and reduce the cost of the turntable. The proposed method successfully avoids the dependence on high-accuracy turntables. An observability degree analysis is conducted to improve the level attitude accuracy further. The simulation and turntable test results indicate that the proposed method can provide high-accuracy level attitude without high-accuracy INS or turntable and is applicable to error calibration and attitude evaluation of INS.     

快速定位定向系统设计及车载实验研究

定位定向系统是能为载体提供精确地理位置坐标、指北方向和姿态角的导航系统,通常用于舰船、飞机、车辆等功能平台,为平台上的设备提供准确的位置和姿态参考信息.本文针对车载平台机动性高的特点,设计能够实现运动中对准的快速定位定向系统,开展捷联惯导数字递推算法、航位推算、多源信息组合导航、动基座对准算法、系统免标定、误差补偿等算法和技术研究.最后,开展静态对准、静态导航和动态车载实验研究.实验结果表明,动态对准时间小于5min,对准姿态精度小于1mil,方位保持精度小于1mil/2h,横滚角、俯仰角保持精度小于0.5mil/2h,里程计/惯导组合水平定位精度小于0.15％D,卫星/惯导组合水平定位精度小于10m.