基于改进预测滤波的小天体精确着陆自主导航方法研究

针对小天体形状不规则、质量不均匀导致模型建立不准确的问题,研究基于改进的预测滤波实现自主着陆过程中精确导航的关键技术。在导航算法设计中,首先建立了小天体引力场模型,并建立了导航系统运动学模型,然后建立了基于惯性测量单元、光学相机及测速敏感器多信息融合的测量模型,结合扩展卡尔曼滤波(Extended Kalman Filter, EKF)算法对非线性预测滤波(Nonlinear Predictive Filter, NPF)算法进行改进,在该导航算法下,对系统的可观性进行了分析。仿真结果表明:在引力不确定性引起的模型不准确度下,该方法可实时估计模型误差,在与EKF导航精度比较的基础上验证了改进的NPF算法的有效性和精确性。

Autonomous Navigation for Precise Landing on Small Celestial Body Based on Improved Nonlinear Predictive Filter

To solve the problem of irregular shape and uneven mass of small celestial body, the key technology of accurate navigation on autonomous precise landing is studied based on improved nonlinear predictive filter. First, the model of gravitational field is established in the design of navigation, and the multi-information measurement model is established based on the inertial measurement, optical camera and the velocity sensor. The nonlinear predictive filter (NPF) is improved combined with the extended Kalman filter (EKF), and the observability of the system is analyzed with the algorithm. The simulation results show that the proposed method can estimate the model error in real time under certain model error caused by gravitational uncertainty. The validity and accuracy of the improved NPF algorithm are verified comparing with the EKF algorithm.