测绘学报

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星敏感器/GNSS定姿系统的联合非线性预测滤波算法

张智斌1,钱山张力军3,李恒年4   

  • 收稿日期:2011-03-24 修回日期:1900-01-01 出版日期:2011-05-05 发布日期:2015-06-24
  • 通讯作者: 张智斌

Federated Nonlinear Filtering for Attitude Determination System with Star Sensor and GNSS Sensor

  • Received:2011-03-24 Revised:1900-01-01 Online:2011-05-05 Published:2015-06-24

摘要: 无陀螺姿态确定系统是航天领域的一个重要研究方向。提出了一种联合式非线性预测滤波算法,解决该系统在姿态动力学模型误差非高斯分布条件下的多敏感器信息融合问题。首先,从算法结构和估计准则两个方面证明了非线性预测滤波(NPF)与Kalman滤波的等效性,分析了联合式NPF的算法流程,讨论了模型误差方差矩阵的计算方法,给出了加权系数矩阵的设计准则;然后,介绍了星敏感器和全球卫星导航系统(GNSS)的定姿原理,推导了星敏感器/GNSS组合姿态确定系统的联合式NPF滤波模型,分析了系统的算法实现流程;最后,进行了数值仿真试验,结果表明:联合式NPF算法融合了NPF与联邦滤波的优良品质,可有效解决姿态动力学模型误差非高斯分布条件下无陀螺姿态确定系统的多敏感器信息融合问题。

Abstract: Gyroless attitude determination system is an important research direction in the aerospace area. In this paper, a federated nonlinear predictive filtering algorithm is presented for the gyroless attitude determination system with multiple sensors. The approach combines the good qualities of both the nonlinear predictive filter (NPF) and federated filter. Moreover, this algorithm can solve the information fusion problem effectively for the system of which the attitude dynamics model error is Non-Gaussian distribution. Firstly, the equivalence relation between NPF and Kalman filter is demonstrated from algorithm structure and estimation criterion. The flow of federated nonlinear predictive filtering algorithm is analyzed and the calculation of the model error covariance is discussed. Secondly, the principles of the star sensor and Global Navigation Satellite System (GNSS) are introduced and the federated nonlinear predictive filtering model of star sensor/GNSS integrated attitude determination system is deduced. At last, simulation results using this algorithm indicate the filter accurately estimates the attitude of the spacecraft with the utilization of the star sensor and GNSS sensor.