星敏感器安装误差标定技术研究

星敏感器是一类具有自主高精度姿态测量能力的仪器,输出姿态精度可达到角秒级。但实际组合导航应用中,星敏感器安装误差往往可达角分级,远远大于仪器本身误差,影响其使用品质,因此有必要在使用前对星敏感器安装误差进行建模标定。研究发现,星敏感器安装误差与惯导姿态误差存在耦合关系,难于分离。设计了一种快速标定方法,利用惯导输出姿态、位置信息以及星敏感器姿态输出构造观测量,建立卡尔曼滤波模型,通过滤波估计实现安装误差的地面标定。仿真结果表明,载体需要进行2个轴向上的机动才能将星敏感器三轴安装误差估计出来。相较于依靠外部基准姿态进行标定的方案,本方法具有快速高效、可操作性强等优点。     

星敏感器在轨光行差修正方法研究

星敏感器作为目前航天器中最重要的姿态测量敏感器,其精度直接影响航天器姿态测量精度,因此对其误差源进行分析和修正则尤为重要。提出了一种星敏感器在轨光行差修正方法,根据光行差产生的原理和特点,将星敏感器沿探测器X和Y方向产生的光行差误差角巧妙地转换为光行差误差四元数,并直接对输出四元数进行修正,从而为修正星敏感器光行差提供了一种方便简洁的方法。     

无陀螺飞行器姿态和角速度确定

通过预测滤波方法研究了利用矢量观测确定无陀螺飞行姿态和角速度的方法。给出的观测滤波法在一定的二次型优化准则下，对飞行器姿态和名义姿态运动模型的等效角速度误差可同时进行实时估计，能够准确跟踪敏感器的测量，有效减小模型误差的影响，数值仿真结果验证了算法的优越性。     

Star-configuration searching for satellite attitude computation

A star pattern recognition algorithm is described which recovers attitude information by processing data obtained from a modular star sensor (MOSS) mounted on a spacecraft information is obtained by matching the stars detected by the MOSS with those inside a stellar catalogue. The system performance has been evaluated both from the point of view of computation time and error probability. The effect of errors in the MOSS measurements and multiple matches cases are also discussed     

弹载大视场星惯组合深度融合导航技术

为了降低弹载星惯组合（Stellar-INS）飞行中段对调姿观星的要求，提高星惯组合姿态精度，提出了大视场（LFOV）星惯组合深度融合导航方法。小视场（NFOV）星敏感器输出星矢量为主，大视场星敏感器可同时输出姿态和星矢量信息，分别推导了基于星敏感器输出姿态和星矢量信息的观测方程，分析了星矢量和姿态观测方法之间的关联性。建立了包含星惯安装误差、陀螺误差以及初始平台误差角的星惯组合全误差项模型，基于线性卡尔曼滤波给出了深度融合导航方法。开展了数学仿真验证，分析了不同调姿观星路径约束下，大/小视场星惯组合性能差异。结果表明，大视场星惯组合深度融合导航方法不仅可以降低调姿观星约束要求，还可以实现组合姿态性能提升。     

面向室内场景的惯性磁感应定位方法

针对卫星拒止的室内导航问题,在现有磁信标定位技术的基础上,通过分析低频旋转磁场的特点,建立了一种不受传感器姿态和磁信标磁矩信息影响的磁感应矢量夹角观测模型,并结合MEMS惯性导航的误差模型提出了一种以磁感应矢量夹角的正余弦值为量测信息的惯性磁感应动态定位方法,避免了磁传感器姿态误差和磁矩误差对定位结果的影响。利用实验室的双轴磁信标实验系统进行静态测试,验证了磁感应定位模型具有不受传感器姿态、环境中遮挡物以及磁矩影响的特点;通过数值仿真的方式对基于无迹卡尔曼滤波(UKF)的惯性磁感应定位方法进行验证,结果表明该方法能有效地抑制惯性导航的发散,且位置最大误差小于0.75 m,满足大多数室内场景下的高精度导航定位需求。     

MULTISENSOR TRACKING SYSTEM WITH ATTITUDE MEASUREMENTS

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SINS辅助的星敏感器在线标定方法

航天器在飞行过程中,星敏感器受到外界温度、地面标定精度等因素影响存在较大的安装误差,这将严重影响星敏感器的定姿精度。为提高星敏感器精度,对其安装误差进行严格的在轨实时标定与修正是确保星敏感器测量精度的关键。提出了一种SINS辅助的在线标定方法,将SINS/星敏感器输出的姿态信息进行配准,构建了组合导航系统的Kalman滤波模型。该方法只需航天器在飞行过程中做简单的机动,即可对星敏感器的安装误差角进行实时在线标定。仿真结果表明,采用该标定方法可使星敏感器和惯导的安装误差角的总体估计率达到95%以上,具有较高的工程应用价值。     

基于平台系统的姿态角传感器测试误差机理分析

新型号惯性稳定平台系统对自瞄准和自标定精度提出了更高的要求,而平台的自瞄准和自标定都需要高精度的姿态角传感器。为了满足系统对传感器的精度要求,在硬件上面无法提高的前提下,软件的补偿是一种更好的选择,而为了进行软件误差补偿,就必须对传感器建立误差模型,而误差模型的建立需要高精度的测试方法,本文就对现有的精度测试方法进行分析,分析测试中各种因素对传感器标定精度结果的影响机理,并通过仿真验证了理论分析的正确性,为后续的传感器高精度标定及误差补偿提供依据。     

Analysis Strapdown Navigation Using Quaternions

A brief review of the theory of strapdown inertial navigation is presented in which the attitude of the sensor box with respect to inertial space is represented by the four-parameter quaternion vector. . A 4X4 matrix R is defined which aids in relating quaternions to direction cosines and facilitates interpretation of the equations for error propagation, which are also derived. In the interpretation, it is shown that the error in the quaternion vector causes aor-(correctable) scale factor error and an equivalent tilt vector error that propagates the same way as the platform tilt vector in a gimbaled system.     

基于MLR的机动平台传感器误差配准算法

 基于固定平台传感器误差极大似然配准(MLR)算法,针对机动平台存在姿态角系统误差的问题,提出了对机动平台传感器系统误差和目标状态进行批处理离线估计的机动极大似然配准(MLRM)算法.该算法利用所有传感器对目标的量测值,通过把传感器量测向目标状态进行投影、对传感器系统误差和目标状态进行期望最大化迭代以及对目标的状态进行融合估计,最终实现量测、姿态角系统误差和目标状态的有效估计.仿真结果表明,该算法迭代收敛速度快,对系统误差估计精度高,对系统误差可观测性较低的配准环境的适应性强并且对传感器姿态角的相关性不敏感,具有很强的工程实用性.     

多个MEMS惯性姿态模块同时标定方法研究

针对MEMS 惯性姿态模块的应用需求, 根据已有的MEMS 三轴加速度计和 三轴陀螺仪的零偏、标度因子和非正交等误差及其随温度的变化模型, 设计了多个 MEMS 惯性姿态模块误差同时标定的方法,该方法可实现多个模块传感器数据的同步采 集,在常温下可对多个MEMS 惯性姿态模块的非正交误差进行批量标定,在全温度范围 内同时标定多个模块的温度漂移误差。试验表明,该方法校正了MEMS 惯性传感器的非 正交误差和温度漂移误差,提高了MEMS 惯性传感器的精度,同时提高了标定的效率, 减少了标定成本,有利于工程实现。     

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.     

ATS-6 Interferometer

The Applications Technology Satellite-6 (ATS-6) RF interferometer is utilized primarily as a precision 3-axis attitude sensor having an unambiguous field of view of 350°. This function requires two separated ground transmitters, each using one of the two available frequency channels or sharing a single channel by time multiplexing. For 3-axis control, one uplink transmitter can provide 2-axis attitude (pitch and roll) with other sensors (e.g., a Polaris tracker) providing yaw attitude. By utilizing two uplink transmitters and the Earth sensor or three time multiplexed uplink transmitters, the interferometer can also provide measurements of ATS-6 spacecraft orbit position. Uplink frequencies are 6.150 and 6.155 GHz. The receiving antennas are spaced at 19.95 wavelengths (?) for the vernier baseline and 1.66 ? for the coarse baseline. Spacecraft system weight is 8.39 kg (18.5 lb) and power requirement is 15.5 W. Flight evaluation results are given for the interferometer including R F link budgets, modulation of uplink carrier, signal-to-noise ratio, and dropout behavior. A hardware calibration model is described, containing major biases in the phase measurements. Techniques for flight calibration as both an attitude and spacecraft position sensor are outlined . Flight testing has shown that on-line calibration of receiver/converter biases must be performed on a short term routine basis. Interferometer resolution was found to be 0.00140 space angle with negligible noise (jitter) at transmitted power levels above 72 dBW. As an attitude sensor, the interferometer has demonstrated the ability to provide stabilization to better than 0.     

基于神经网络的无人直升机姿态控制系统设计

首先根据模型参考自适应控制理论,将模型逆与在线神经网络结合,设计了神经网络自适应姿态控制系统。接着叙述反馈线性化及模型逆理论,分析系统的模型跟踪误差动力特性,设计神经网络控制器及在线算法。然后以某无人直升机俯仰通道为例,对神经网络姿态控制系统进行仿真。结果表明该系统能够对未建模特性、参数不确定性等引起的模型逆误差进行自适应,而且在传感器输出中具有白噪声时仍然能够获得较好的响应特性。     

基于PSD的并联微定位平台位姿检测方法

位置姿态（以下简称位姿）检测是研究六自由度定位平台的技术难点之一,为了快速准确测量六自由度并联微定位平台的位姿,验证平台的定位精度,基于多片二维PSD光电位置传感器设计了六自由度光学位姿检测系统。依据几何光学理论,建立了六自由度位姿解算的数学模型。通过仿真计算,该算法可以快速准确解算六自由度定位平台位姿。进一步分析了该模型在考虑存在测量误差时的理论计算误差,结果表明,基于二维PSD位置传感器的六自由度光学位姿检测系统在解算六自由度定位平台位姿的同时,具备较高的测量精度。     

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.     

皮卫星姿态估计及粗太阳敏感器标定算法研究

粗太阳敏感器是一种由多个光电池片配置组成的模拟式太阳敏感器,它结构简单、资源要求少,在皮卫星平台应用较为广泛。光电池光伏输出特性是粗太阳敏感器测量的基础,使用余弦关系近似等效会引入很大的误差。通过实际测试和深入分析,建立了更高精度的粗太阳敏感器输出特性等效数值模型,并以此为基础,推导了卫星姿态估计及粗太阳敏感器标定的联合在轨实时算法。算法采用多级耦合结构,由1个扩展卡尔曼滤波器(EKF)和6个卡尔曼滤波器组成,同时估计卫星姿态、卫星角速度以及卫星6个面共30个标定参数。仿真表明,和常规的EKF姿态估计算法相比,联合算法的运算量只增加了一半,而估计精度却提高了一个量级。     

改进联邦滤波器在小卫星姿态确定中的应用

采用微小卫星姿态运动学、动力学方程,以磁强计／太阳敏感器为姿态敏感器进行姿态确定,研究了一种基于融合反馈的改进联邦滤波算法,提出了一种基于观测新息修改的信息分配原则。给出了由四元数描述卫星姿态的误差状态方程,并对观测矢量进行推导,获得了基于角速度的观测方程,丰富了观测模型。仿真结果表明：基于角速度观测方程的引入,增强了观测信息的利用率,进而提高了姿态确定的精度,降低了计算量,保证了可靠性。     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.