摘要
由于火星大气进入段的突风、沙尘暴、大气密度变化以及模型参数选取不当等因素的影响,导致动力学方程中存在未知输入(偏差),又由于惯性测量单元漂移等因素的影响,导致量测数据中存在未知输入(偏差),这两种未知输入(偏差)将严重影响火星大气进入段自主导航的精度。本文基于双未知输入扩展自校准滤波,建立了一种新的火星大气进入段自主导航算法,该算法能自动对动力学方程和量测方程中的未知输入进行识别、估计和补偿,消除系统误差,并通过数据融合减小偶然误差,提高滤波精度,实现高精度的自主导航。算例结果表明,与基于扩展Kalman滤波的传统导航算法相比,本文算法在探测器运动状态的6个维度上均大幅提升了导航精度。
Due to the influence of factors such as gusts,dust storms,changes in atmospheric density,and improper selection of model parameters in mars atmospheric entry phase,unknown-inputs(deviations)exist in the dynamic equations,and due to factors such as inertial measurement unit drift,as a result,there are unknown-inputs(deviations)in the measurement data,and these dual unknown-inputs(deviations)will seriously affect the accuracy of autonomous navigation in mars atmospheric entry.Based on the dual unknown-inputs extended self-calibration filter,a new autonomous navigation algorithm for mars atmospheric entry is established.This algorithm can automatically identify,estimate and compensate unknown inputs in the dynamic equations and measurement equations,eliminating systematic errors,and reducing accidental errors through data fusion,improving filtering accuracy and achieving high-precision autonomous navigation.The example calculation results show that compared with the traditional navigation algorithm based on extended Kalman filter,the algorithm proposed in this paper significantly improves the navigation accuracy in all six dimensions of the detector’s motion state.
作者
杨海峰
傅惠民
YANG Haifeng;FU Huimin(Research Center of Small Sample Technology,Beijing University of Aeronautics and Astronautics,Beijing 100191,China)
出处
《智能计算机与应用》
2020年第2期12-16,22,共6页
Intelligent Computer and Applications
基金
国家重点基础研究发展计划(2012CB720000)
工信部2018年智能制造综合标准化项目《基于数字仿真的机械产品可靠性测试方法标准研究与试验验证》。
关键词
自校准
火星探测
自主导航
滤波
偏差
精度
self-calibration
mars exploration
autonomous navigation
filter
bias
accuracy
