微小卫星太阳敏感器/磁强计实时标定算法研究

 提出了一种对磁强计/太阳敏感器的无姿态信息的在轨实时标定方法。在现有的标定算法中，仅采用地磁矢量的模作为观测量，本文引入地磁矢量与太阳矢量之间的数量积作为观测量，增强了其可观性，也使对太阳敏感器的实时标定成为可能。扩展卡尔曼滤波器(Extended Kalman Filter，EKF)虽然获得广泛应用，但其线性化过程会引入截断误差，而无香卡尔曼滤波器(Unscented Kalman Filter，UKF)是非线性滤波方法，不须对系统进行线性化。分别利用EKF与UKF的滤波标定算法进行标定研究，仿真结果表明了本文算法的有效性，如磁强计偏置的标定精度，UKF比EKF高26%。     

基于磁强计测量的微小卫星轨道姿态 耦合确定方法

针对基于磁强计测量的微小卫星, 提出了基于串并联混合策略的轨道姿态 耦合确定方法。滤波初期,考虑到估计误差较大,采用先地磁场大小测量的轨道确定、 后地磁场矢量测量的姿态确定的串联策略;稳定后,采用基于矢量测量的轨道、姿态同 步确定的并联策略。为降低轨道、姿态确定的相互影响,设计了基于信息的鲁棒Kalman 滤波,通过自动调节增益矩阵处理两个滤波系统间的影响。仿真表明,该方法在提高鲁 棒性的同时,还能适当提高状态估计的精度。     

近地卫星磁测自主定轨及原型化

利用三轴磁强计的测量信息可实时地确定卫星轨道。采用扩展卡尔曼滤波作为处理磁测自主定轨问题的滤波算法．并以地磁场强度幅值作为测量值，建立了近地卫星磁测自主定轨的数学模型。在数学模型的基础上实现了基于PC机、dSPACE一体化系统的原型化(Prototyping)实验。该原型化实验对磁测自主定轨的方案、理论、算法及实时运行特性做了进一步的验证。     

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。     

The Juno Magnetic Field Investigation

The Juno Magnetic Field investigation (MAG) characterizes Jupiter’s planetary magnetic field and magnetosphere, providing the first globally distributed and proximate measurements of the magnetic field of Jupiter. The magnetic field instrumentation consists of two independent magnetometer sensor suites, each consisting of a tri-axial Fluxgate Magnetometer (FGM) sensor and a pair of co-located imaging sensors mounted on an ultra-stable optical bench. The imaging system sensors are part of a subsystem that provides accurate attitude information (to ～20 arcsec on a spinning spacecraft) near the point of measurement of the magnetic field. The two sensor suites are accommodated at 10 and 12 m from the body of the spacecraft on a 4 m long magnetometer boom affixed to the outer end of one of ’s three solar array assemblies. The magnetometer sensors are controlled by independent and functionally identical electronics boards within the magnetometer electronics package mounted inside Juno’s massive radiation shielded vault. The imaging sensors are controlled by a fully hardware redundant electronics package also mounted within the radiation vault. Each magnetometer sensor measures the vector magnetic field with 100 ppm absolute vector accuracy over a wide dynamic range (to 16 Gauss = \(1.6 \times 10^{6}\mbox{ nT}\) per axis) with a resolution of ～0.05 nT in the most sensitive dynamic range (±1600 nT per axis). Both magnetometers sample the magnetic field simultaneously at an intrinsic sample rate of 64 vector samples per second. The magnetic field instrumentation may be reconfigured in flight to meet unanticipated needs and is fully hardware redundant. The attitude determination system compares images with an on-board star catalog to provide attitude solutions (quaternions) at a rate of up to 4 solutions per second, and may be configured to acquire images of selected targets for science and engineering analysis. The system tracks and catalogs objects that pass through the imager field of view and also provides a continuous record of radiation exposure. A spacecraft magnetic control program was implemented to provide a magnetically clean environment for the magnetic sensors, and residual spacecraft fields and/or sensor offsets are monitored in flight taking advantage of Juno’s spin (nominally 2 rpm) to separate environmental fields from those that rotate with the spacecraft.     

低轨微纳卫星全磁自主导航算法研究

针对低轨微纳卫星体积小、功耗低的设计约束,提出了基于低轨地磁的定轨/定姿全磁自主导航算法.该算法仅利用三轴磁强计测量值和卫星动力学方程建立Kalman滤波器,实现了低轨微纳卫星的全自主轨道确定和姿态测量,理论仿真结果表明,该全磁导航算法精度能够满足低轨微纳卫星的一般要求.利用高精度地磁模拟器搭建了微纳卫星全磁自主导航地面仿真验证系统,对算法进行了全物理仿真测试和实验误差分析,进一步验证了全磁自主导航算法的可行性,为低轨微纳卫星提供了一种低成本、高自主、高可靠性的导航方法.     

Simultaneous spacecraft attitude and orbit estimation using magnetic field vector measurements

Based on magnetometer measurements only, three-axis attitude, rate, and orbit estimation are successfully achieved. A single Augmented Dynamics Extended Kalman Filter (ADEKF) is configured by combining the spacecraft nonlinear attitude dynamics and quaternion kinematics with orbital mechanics. The filter design is adopted for three-axis stabilized spacecraft in low Earth orbits where the aerodynamic drag is the dominant source of disturbances in addition to the spacecraft magnetic residuals. To reduce the computational burden, another Interlaced Extended Kalman Filter (IEKF) is developed to uncouple the attitude/rate from the orbit dynamics. Both filters are implemented using the magnetometer measurements and their corresponding time derivatives. As a part of EgyptSat-1 flight scenario, detumbling and standby modes are used for performance testing of the ADEKF. The concept of local observability is applied to the basic filter and the stability is investigated by incorporating extensive Monte Carlo simulations with uniformly distributed initial conditions. The filter shows the capability of estimating the attitude better than 5 deg and rate of order 0.03 deg/s in each axis. In orbit estimation, the filter is capable of estimating the position with accuracy less than 8 km and velocity upto 5 m/s in each axis.     

微小卫星剩磁在轨标定技术研究

 基于微小卫星姿态确定系统常采用无陀螺配置方案，克服环境干扰力矩的影响并提高微小卫星姿态确定的精度是此类姿态确定系统的关键。分析了星上稳定剩余磁场对无陀螺微小卫星姿态确定的干扰机理，建立了卫星剩余磁矩与磁强计偏置标定模型。以磁强计、太阳敏感器作为姿态敏感器件，并采用扩展卡尔曼滤波器实现标定算法，为无陀螺磁测微小卫星消除剩磁干扰，获得高精度姿态估计提供了一种新方法。仿真结果表明：该方法能准确估计卫星剩余磁矩与磁强计偏置，磁强计偏置的标定精度在1 nT左右，剩余磁矩的标定精度为0.000 1 A·m²量级，有效消除了剩磁对无陀螺卫星姿态确定的影响，显著提高了姿态确定精度，滤波器能在500 s内收敛。     

一种用于仿生导航无人机航姿求解的混合滤波方法

针对现有组合导航系统易被干扰欺骗以及姿态求解精度不足的问题，设计了惯性测量单元(IMU)与偏振光传感器组成的航姿参考系统(AHRS)。同时，考虑到传统的姿态求解方法精度不高，提出了一种用于仿生导航无人机航姿求解的混合滤波方法。将Mahony滤波后的姿态值作为系统观测量，再结合扩展卡尔曼滤波(EKF)实现传感器数据的深层融合，以获得高精度的姿态角信息。实验结果表明：在静态环境下采用混合滤波方法求解的姿态值能有效滤除偏振光传感器和加速度计内部噪声干扰，其稳定性明显优于两种方法各自求解时的情况；在动态实验中该方法能有效抑制单独采用Mahony滤波时存在的超调问题，表现出更高的动态解算精度，从而为偏振光组合导航系统提供了更精确的姿态估计信息。     

An epoch state filter for use with analytical orbit models of low earth satellites

Kalman filters provide a well established means for satellite orbit determination. In combination with space based sensors like GPS, DORIS or PRARE, accurate estimates of the spacecraft position and velocity can be obtained in real-time on-board the space vehicle. Traditionally, numerical methods of varying complexity are applied for propagating the state vector between measurements and updates of the state vector are referred to the epoch of the latest sensor output. In the present study a different approach is followed, which offers increased on-board autonomy and is particularly promising for small satellites with moderate accuracy requirements. An analytical orbit model is used to describe the spacecraft trajectory and mean elements at epoch are estimated instead of the instantaneous, osculating state vector. This adds the capability of performing on-board orbit prediction over time scales of up to one week, which is required, for instance, for the autonomous forecast of eclipse times or station contacts. Making use of the SGP4 orbit model that is compatible with NORAD twoline elements, an epoch state Kalman filter has been implemented and tested with GPS flight data of GPS/MET (MicroLab-1) and MOMSNAV (MIR). It is demonstrated that the proposed method provides an accuracy compatible with that of the analytical model and is robust enough to handle large data gaps in case of limited on-board resources for GPS operations. By adjusting the ballistic coefficient along with the mean elements, a considerable improvement of mid-term orbit predictions is achieved over methods that are restricted to the estimation of the state vector alone.     

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.     

三轴矢量原子磁力仪综述

原子磁力仪可分为标量磁力仪和矢量磁力仪两大类。标量磁力仪的测量结果与传感器的姿态无关,对平台的机动不敏感。矢量磁力仪能够获得更多的磁场信息,可以实现更精确的磁源定位。目前,共有7种三轴矢量原子磁力仪,测量方法分别为磁场扫描法、磁场旋转调制法、磁场轮流抵消法、磁场投影法、磁场交叉调制法、磁场分立调制法和自旋进动调制法。重点对上述7种三轴矢量原子磁力仪的测量方法进行了整理和分析。     

基于PnP和自适应线性卡尔曼滤波的实时位姿估计

针对实时位姿估计中扩展卡尔曼滤波(EKF)线性化引入非线性误差和依赖已知噪声分布的缺点,提出一种基于PnP的自适应线性卡尔曼滤波位姿估计求解方法。将PnP位姿估计求解策略引入卡尔曼滤波观测方程,通过对动态方程误差统计参数实时估计,自适应调节卡尔曼滤波递推参数。所提算法求解精度高,固定了观测方程的观测向量维度,提高了算法实用性。通过仿真试验,比较了该算法与EKF的位姿估计精度,通过量化误差分析,证明了该方法可以提高三维运动位姿估计精度,也验证了该方法的有效性。     

微小型无人机三轴磁强计现场误差校正方法

详细分析微小型无人机导航用三轴磁强计的误差来源,建立三轴磁强计的等效误差模型,提出基于两步估计算法和圆约束非对准误差估计算法的三轴磁强计现场误差校正方法.在充分考虑地磁场偏转和倾斜特性的基础上,提出适合微小型无人机应用的现场数据采样策略,能够在较少的旋转操作下获得较好的采样数据.仿真表明:在所有磁场误差都存在的情况下,...     

基于MEMS陀螺仪辅助的粒子群优化磁力计校正

目前磁力计校正中存在需要采集大量数据、获取良好的初值和已知准确的传感器噪声分布等问题,传统的粒子群优化磁力计校正算法能够解决以上问题,但是该算法只能用于磁力计简化模型,校正其中9个误差参数,造成补偿不准确的问题。该算法借助MEMS陀螺仪建立矢量目标函数,采用随机漂移粒子群优化算法估计磁力计12个误差参数,具有较强的全局搜索能力和动态适应性。经过仿真与实测实验表明,该算法在磁力计绕其任意2个单轴不完整旋转1周即可实现校正,并且能够在磁场变化情况下保持精度,相比于传统算法补偿精度高、操作简单。     

基于航向匹配的磁力计外场无依托标定算法CSCD

三轴磁力计的测量精度会受到自身和环境的影响,因此在使用前必须要进行标定。传统标定方法需要特定的精密仪器和标定环境,或是对计算量和采集数据的方式有较高的要求,针对这些问题,提出了基于航向匹配的磁力计外场无依托标定算法。该算法无需特定精密仪器、对数据采集和计算量的要求也较低,且可以在现场实现有效动态标定。该算法基于航向角是磁航向角与磁偏角代数和的原理,通过等价数学变换构建了磁力计零偏关于姿态角与磁力计测量值的线性模型,最终采用最小二乘法对磁力计的零偏进行估计。该算法可以估计三轴磁力计的零偏,对磁力计的测量结果有较好的补偿作用。实验结果表明,该算法可有效标定三轴磁力计,减小其测量误差。经标定的磁力计可以应用于地磁匹配导航,辅助惯性导航修正其位置误差,尤其是在长直路段内,磁力计标定过程中识别出的磁异常数据可以为地磁匹配导航提供基础信息。     

一种非线性滤波器的误差分析及应用

针对一类具有未建模误差和扰动的非线性系统的状态估计问题,提出一种在线估计并补偿模型误差的非线性滤波算法,该算法利用非线性预测滤波(NPF)基于预测输出残差的方差最小的基本原则估计模型误差,冉利用扩展卡尔曼滤波(EKF)的思想对补偿后的模型进行状态估计;详细推导了状态估计误差及其方差阵的传播模型.以卫星姿态确定系统为例,...     

空间平台机动变轨自主导航研究

针对空间平台在高轨道机动变轨过程中自主导航的需求,采用了基于Kalman滤波器的捷联惯导与星敏感器的组合导航方案。结合Kalman滤波中协方差更新的误差分配分析方法,分析了影响空间平台状态估计误差的主要因素。采用适用于高轨道的球谐重力模型,运用STK工具包设计了变轨机动轨迹,将该轨迹应用于组合导航方案的仿真验证。仿真结果表明,量测噪声是影响空间平台姿态精度的主要因素,加速度计零偏对变轨过程速度精度有决定性影响,改善两者的精度可以实现空间平台机动变轨的高精度自主导航。     

高斯-厄米特滤波器在捷联惯导系统初始对准中的应用

 为提高静基座初始对准精度,缩短对准时间,采用了基于大方位失准角的对准模型,引入了高斯-厄米特滤波器(GHF)。针对GHF中均值和协方差阵的多元非线性高斯积分求解问题,利用初始对准误差方程的非线性是由大方位失准角导致的特点,通过状态的线性变换,求其线性状态解析解,将高维积分转化成一元数值积分,在不损失精度的前提下,解决了GHF在对准应用的"维数灾难"问题。将此算法用于实际系统,对比于扩展卡尔曼滤波器(EKF)、无迹卡尔曼滤波器(UKF),结果表明在大方位失准角条件下,GHF方法偏航角的对准精度提高了16%,对准时间缩短了75％。     

基于改进的磁场检验和主方向算法的行人航向估计

针对以惯导为核心的行人定位算法存在航向角失真的问题，提出了一种融合惯性测量单元(IMU)和磁力计的行人导航算法，利用步幅航向的变化量将行人的运动分为直线行走和曲线行走两部分，当检测到行人直线行走时，提出一种实时建立主方向的自适应航向角漂移修正算法，对航行角误差进行补偿；当行人曲线行走时，辅助地磁场信息，使用磁场强度、地磁倾角、惯性导航系统(inertial navigation system，INS)与磁力计解算的航向角之差这三个特征值构建广义似然比检验量，对磁场进行判断获得稳定状态磁场信息，通过卡尔曼滤波对航向角误差进行补偿。将传感器置于足部进行实验，实验结果表明,两种算法可以实现优势互补，有效地抑制地磁信息的干扰，提高导航精度，算法结果相对于无航向角修正的零速修正算法、零角速度更新算法和单独使用磁力计进行融合的算法，定位误差分别降低了91.02%、82.93%和61.39%，室外和室内终点定位误差分别为4.545 4 m和0.543 6 m，占总路程的0.69%和0.17%。