一种带自适应因子的IMM-UKF的GPS/BD-2导航方法  

An IMM-UKF with Adaptive Factor for GPS / BD-2 Satellite Navigation System

作　　者：董宁[1] 徐玉娇[1] 刘向东[1] 

机构地区：[1]北京理工大学自动化学院,北京100081

出　　处：《宇航学报》2015年第6期676-683,共8页Journal of Astronautics

基　　金：国家自然科学基金(11372034)

摘　　要：针对GPS/北斗-2(BD-2)卫星导航系统中机动载体运动模型和噪声统计特性不确定性导致滤波精度低的问题,为提高导航定位的精确性和稳定性,提出一种自适应的滤波方法。首先,提出了一种新的自适应UKF(AUKF)算法,该方法将残差序列的协方差矩阵视为过程噪声协方差矩阵的不确定量,基于此采用平滑滤波的方法设计自适应因子,并利用该自适应因子实时调整过程噪声协方差矩阵,减弱了噪声统计特性不确定性对滤波精度的影响;其次,采用交互式多模型(IMM)算法设置模型集M,并通过实时调整模型概率来实现各个模型间的软切换,解决了单一模型对载体运动状态描述不全面而导致滤波精度低的问题。仿真结果证明该算法能有效提高载体在复杂机动状态下的定位精度。In this paper, a novel adaptive filter algorithm is proposed to improve position accuracy of the GPS/BeiDou- 2 （BD-2） integrated satellite navigation system for a maneuver vehicle in the presence of model and noise statistics uncertainty. Firstly, a new adaptive UKF is proposed to solve the problem of noise uncertainty by use of an adaptive factor obtained from the smoothing filter based on the residual error treated as the uncertainty of process noise. This adaptive method significantly reduces the effect of noise uncertainty on fihering performance. Secondly, in our method, a set M of models is taken into consideration and a ＇ soft switching＇ among the model set based on model probability is carried out by using interactive multiple model （IMM） algorithm, by which the position error caused by the model uncertainty can be reduced. The simulation results verify the effectiveness of the proposed method, and show preferable position accuracy for the complex maneuver vehicle.

关 键 词：自适应 无迹卡尔曼滤波 交互式多模型 模型不确定 噪声统计特性不确定性 卫星导航系统 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计]