基于改进自适应无迹卡尔曼滤波的国产民机导航数据滤波算法  

Domestic Civil Aircraft Navigation Data Filtering Algorithm Based on Improved Adaptive Unscented Kalman Filter

作　　者：杨军利[1] 王立新 钱宇[1] 刘瑜 YANG Jun-li;WANG Li-xin;QIAN Yu;LIU Yu(School of Flight Technology,Civil Aviation Flight University of China,Guanghan 618307,China)

机构地区：[1]中国民用航空飞行学院飞行技术学院,广汉618307

出　　处：《科学技术与工程》2021年第35期15123-15129,共7页Science Technology and Engineering

基　　金：国家自然科学基金民航联合基金(U2033213);民航飞行技术与飞行安全重点实验室自主研究项目(FZ2020ZZ01)。

摘　　要：针对国产民用飞机导航数据存在杂波不能准确测量的问题,提出一种基于改进自适应无迹卡尔曼滤波(adaptive unscented Kalman filter,AUKF)算法的导航数据滤波方法。将无迹卡尔曼滤波(unscented Kalman filter,UKF)与改进Sage-Husa次优无偏极大后验噪声估计器结合构造出改进AUKF,有效解决了在模型不确定或干扰信号统计特性不完全得知的情况下,滤波精度低甚至发散的问题,同时与维纳滤波器和小波阈值法滤波效果进行对比。选择ARJ21飞机实际运行的高度、经度及纬度数据进行仿真。结果表明:改进后的AUKF算法较其他滤波算法精度更高,有效提高了导航数据的可靠性。研究对提高国产民机导航定位精度具有重要意义。Aiming at the problem that the domestic civil aircraft navigation data can not be accurately measured due to clutter,a navigation data filtering method based on improved adaptive unscented Kalman filter(AUKF)algorithm was proposed.The improved AUKF was constructed by combining unscented Kalman filter(UKF)with improved Sage-Husa sub optimal unbiased maximum posterior noise estimator.The problem of low accuracy and divergence was effectively solved in the case of uncertain model or incomplete knowledge of statistical characteristics of interference signals.At the same time,the filter effect was compared with Wiener filter and wavelet threshold method.The simulation was carried out with the longitude,latitude and altitude data of domestic ARJ21.The results show that the filtering accuracy of the improved AUKF algorithm is higher than others,and effectively improves the reliability of navigation data.The research is of great significance to improve the navigation and positioning accuracy of domestic civil aircraft.

关 键 词：自适应无迹卡尔曼滤波 Sage-Husa算法 维纳滤波器 小波阈值法 国产民用飞机 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] V271.2[自动化与计算机技术—计算机科学与技术]