基于无迹卡尔曼滤波的仪表着陆系统/GBAS着陆系统/惯性导航系统组合导航融合方法  

Instrument Landing System/GBAS Landing System/Inertial Navigation System Integrated Navigation Fusion Method Based on Unscented Kalman Filter

作　　者：于耕 于泠洁 YU Geng;YU Lingjie(School of Civil Aviation, Shenyang Aerospace University, Shenyang 110136, R.P. China;School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, R.P. China)

机构地区：[1]沈阳航空航天大学民用航空学院,沈阳110136 [2]沈阳航空航天大学电子信息工程学院,沈阳110136

出　　处：《科学技术与工程》2017年第36期236-241,共6页Science Technology and Engineering

基　　金：国家自然科学基金(U1433115);中航工业产学研协同创新专项(CXY2012SH16);中国航天科技集团公司卫星应用科研创新基金(2014_CXJJ-TX_12)资助

摘　　要：针对进近着陆过程中,仪表着陆系统(ILS)会受到空域以及外界环境的影响而产生导航偏差,影响进近着陆时导航的精度;而现在正在引进GBAS着陆系统(GLS)。提出一种将ILS和GLS分别与惯性导航系统(INS)相组合,利用改进的联邦无迹卡尔曼滤波,将其输出的位置之差作为量测值;再根据线性最小方差准则,提出了按照最优系数加权的方法融合局部导航数据,从而得到全局最优估值。相比于传统的UKF滤波算法,能有效地降低测量噪声,减小飞机降落时与标准航道的偏角误差,从而提高进近着陆引导的水平精度。Localizer and glideslope signals in current instrument landing system(ILS)are susceptible to the environmental interference due to the increasing airspace usage during the precision approach and landing,which affects the precision of landing guidance.GLS landing system is now being introduced.In order to solve this problem,an inertial navigation system(INS)/GLS/ILS integrated navigation system was proposed,to improve the landing guidance performance.Measurements were acquired by the difference between output positions using the improved federated Unscented Kalman Filtering method.A matrix weighted data fusion algorithm is derived based on the rule of linear minimum variance to fuse the local state estimates for generating the global optimal state estimation.Compared to the traditional UKF,the improved algorithm can reduce the noise influence effectively,so as to improve the accuracy of the approach and landing guidance.

关 键 词：仪表着陆系统(ILS) GLS 惯性导航系统 无迹卡尔曼滤波 联邦卡尔曼滤波 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]