共查询到19条相似文献,搜索用时 156 毫秒
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基于最优融合估计理论,给出并证明了多敏感器组合姿态确定系统状态最优融合估计形式。设计了基于信息分配的多信息融合联合滤波器结构和算法,分析估计性能,讨论了决定联合滤波器融合的性能信息分配因子选择方法,提出了一种基于协方差阵特征值平方分解的动态自适应信息分配因子确定方法。以某卫星多姿态敏感器组合测量为例,推导了卫星姿态确定的误差状态方程和各子系统的量测方程及观测阵。仿真结果表明:采用联合滤波器对多敏感器卫星姿态确定系统进行信息融合能改善定姿精度,有效抑制滤波发散,并提高整个系统的运算与收敛速度。 相似文献
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在矢量观测的基础上,针对单独的星敏感器定姿,提出了一种将粒子滤波(PF)和预测滤波相结合的姿态确定算法,通过设计粒子初始化,结合重要性采样、重采样和规则化等手段,成功地将姿态四元数作为状态粒子进行更新和传递,避免了状态方程的线性化和协方差矩阵的计算;利用预测滤波算法估计模型误差和姿态角速度,在保证滤波精度的同时,有效降低了粒子滤波器的维数.实验在某对地观测通用小卫星平台上进行,选取卫星自由飞行状态和飞轮控制对地稳定模式,分别对滤波器进行了仿真,实验结果验证了该算法对本质非线性、非高斯的卫星姿态估计问题具有快速的收敛性能和良好的稳定精度.该方法还为粒子滤波器的设计和无角速度敏感器测量的飞行器姿态确定提供了借鉴. 相似文献
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基于低成本MEMS传感器的皮卫星融合定姿算法研究 总被引:1,自引:1,他引:1
基于低成本低精度的MEMS陀螺、太阳敏感器、磁强计组合,设计了Unscented Kalman融合滤波算法.同时考虑到可能的故障模式,提出了仅依赖磁强计的备份滤波算法.在姿态参数选取上,采用修正罗德师里德参数来描述卫星姿态,降低了滤波器的维数,避免了采用四元数时解算状态误差协方差参数的奇异.利用MEMS陀螺采集的随机噪声数据进行半物理仿真,仿真结果表明:该融合算法能有效对卫星姿态进行实时估计,在个别敏感器失效的情况下,同样能实现较高的精度,满足普通任务的要求.该算法具有工程实现意义,是对低精度MEMS敏感器在低成本皮卫星上应用的有益探索. 相似文献
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本文探讨了利用方位矢量和陀螺速率观测信息确定卫星姿态的问题。该问题实际上是一个非线性/非高斯状态滤波问题,因此,经典的基于EKF和UKF算法的姿态滤波器有可能失败,尤其是当初始状态的先验估计不可能精确得知的情况下。近来,粒子滤波理论已经开始应用于姿态确定问题,但是,这类算法往往需要大量的“粒子”,这对有限计算能力来说是一个沉重的负担。为此,本文尝试利用双重滤波方法,在每个序贯估计过程中,将有陀螺姿态确定问题暂时分解为1个四元数估计问题和1个陀螺常漂参数估计问题。本文提出了2个双重滤波器,包括1个姿态确定双重粒子滤波器和1个姿态确定的混合型滤波器。这两者都采用一个相同的四元数粒子滤波器,但在粒子重采样和平滑处理方面,不同于近来提出的类似滤波器。至于陀螺常漂估计,双重粒子滤波器发展了一个辅助粒子滤波器,而混合滤波器中则发展了一个参数UKF滤波器。通过与经典的姿态确定滤波器的仿真比较,证实了本文新提的2个算法的有效性和优越性。
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This paper proposes a novel multiple model estimator for the satellite attitude determination system composed of gyroscopes and star sensors. The main objective is to calibrate the low frequency error of the star sensor and improve the attitude determination accuracy. In the proposed approach, first, the specific frequencies of the low frequency error is extracted according to the frequency spectrum of the estimate of the gyroscope drift obtained from a standard Kalman filter; then, a bank of Kalman filters based on multiple models is implemented to identify the amplitudes of the error signals with the specific frequencies, such that a reference model is obtained to compensate for the effects of the low frequency error. Simulation results indicate that the proposed approach outperforms the existing calibration approach based on the state augmentation technique. 相似文献
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编队自主导航是实现分布式遥感系统星间协同观测的基础。为实现分布式遥感系统星间相对状态的精确确定,提出一种基于MEMS激光雷达与纳型星罗盘的星间相对状态估计方法。借助相对姿态、轨道运动学方程建立了星间相对状态的无迹卡尔曼滤波(UKF)算法,解决了MEMS激光雷达测量与参考航天器姿态耦合的问题,并利用预定入轨参数及高精度轨道外推(HPOP)对方法进行仿真校验。结果表明,该方法具有可行性和实用性,估计精度满足分布式遥感任务需求,能够较好解决中远距离星间相对状态估计问题。 相似文献
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A novel algorithm is presented in this study for estimation of spacecraft?s attitudes and angular rates from vector observations. In this regard, a new cubature–quadrature particle filter (CQPF) is initially developed that uses the Square-Root Cubature–Quadrature Kalman Filter (SR-CQKF) to generate the importance proposal distribution. The developed CQPF scheme avoids the basic limitation of particle filter (PF) with regards to counting the new measurements. Subsequently, CQPF is enhanced to adjust the sample size at every time step utilizing the idea of confidence intervals, thus improving the efficiency and accuracy of the newly proposed adaptive CQPF (ACQPF). In addition, application of the q-method for filter initialization has intensified the computation burden as well. The current study also applies ACQPF to the problem of attitude estimation of a low Earth orbit (LEO) satellite. For this purpose, the undertaken satellite is equipped with a three-axis magnetometer (TAM) as well as a sun sensor pack that provide noisy geomagnetic field data and Sun direction measurements, respectively. The results and performance of the proposed filter are investigated and compared with those of the extended Kalman filter (EKF) and the standard particle filter (PF) utilizing a Monte Carlo simulation. The comparison demonstrates the viability and the accuracy of the proposed nonlinear estimator. 相似文献
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针对考虑位姿耦合的非合作航天器交会对接场景,在没有速度测量情况下为了同时解决安全约束、模型不确定性、执行器故障和输入饱和问题,提出一种基于容积卡尔曼滤波算法(CKF)的自主安全接近方法。首先基于容积卡尔曼滤波器和扩张状态观测器(ESO)分别估计目标航天器的位姿信息和相对速度信息;然后通过将一种新颖的安全包络与人工势函数(APF)结合设计自适应滑模控制器,并设计非奇异辅助系统对执行器故障和输入饱和带来的影响进行集中处理。提出的控制策略在不违反安全约束情况下,能在固定时间内实现位置接近和姿态同步。通过李雅普诺夫方法可以保证闭环系统固定时间稳定。仿真结果表明,所提控制方法具有较高的精度和良好干扰抑制能力。 相似文献
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As one of the most critical issues for high-accuracy satellite attitude determination, the relative installation error of star tracker usually leads to inconsistency of the output attitude information. In this paper, an approach named regularized robust filter algorithm is proposed to control the relative installation error of star tracker in the attitude measurement data. Based on the uncertainty model established for the attitude measurement system, the weighted least square solution is presented and the regularized robust filter is deduced firstly. The algorithm parameters are then optimized with the design indices in order to minimize the upper boundary for the variance of the estimated error. Compared with the traditional Kalman filter, the regularized robust filter takes into consideration the effects of model uncertainty, which can be used to optimize the filter parameters during its design stage. Thus, the information of both the system model and the measurement data can be applied effectively. Moreover, the existence conditions need not be validated in the proposed filter algorithm, which is convenient for on-orbit application. Finally, simulation results demonstrate the validity and efficiency of the proposed method. The relative installation error of attitude determination is mostly reduced and the estimation precision is improved greatly. 相似文献
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针对星上计算机运算资源有限的问题,为了降低卫星姿态确定系统故障诊断的运算量,提出一种基于卡尔曼滤波器的故障检测与分离方法。该方法首先基于卫星姿态运动方程设计了一种加性卡尔曼滤波器,然后将卡尔曼滤波器与简化观测器思想相结合,进一步提出一种采用简化滤波器思想的姿态敏感器故障诊断律。所提出的故障诊断方法既可以实现对陀螺故障的检测与分离,又能够诊断星敏感器的故障。此外,该方法只利用一个滤波器即可实现故障检测与分离,其计算量小,有利于在轨实施。最终采用一个由三正交一斜装陀螺组件和星敏感器构成的姿态确定系统对所提出的方法进行了仿真校验,仿真结果表明了所提方法的有效性。 相似文献