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基于强跟踪性能的QEKF组合导航自适应滤波研究
引用本文:夏琳琳,赵琳,程建华.基于强跟踪性能的QEKF组合导航自适应滤波研究[J].测绘学报,2008,37(4):410-417.
作者姓名:夏琳琳  赵琳  程建华
作者单位:1. 东北电力大学,自动化工程学院,吉林,吉林,132012
2. 哈尔滨工程大学,自动化学院,黑龙江,哈尔滨,150001
摘    要:以低成本陆用航姿参考系统(AHRS)/GPS紧耦合系统为研究对象,建立了基于伪距、伪距率、航向角的组合观测数学模型。引入强跟踪滤波(STF)算法,利用渐消因子的作用,增强滤波器对状态快速变化的跟踪能力。同时,针对微惯性器件漂移过大的缺点,采用二阶EKF(QEKF)方法,通过对Hessian矩阵的求解,补偿系统观测方程线性化的二阶截断误差。仿真表明:STQEKF方法可高速准确地逼近系统非线性模型,实现陆地载体导航控制,在传感器精度有限的情况下,使姿态和位置的控制效果较标准EKF分别提高了约8.9%-38.2%和48.7%-54.4%

关 键 词:航姿参考系统/GPS  强跟踪滤波  次优渐消因子  二阶EKF  Hessian矩阵  非线性系统

Research on Adaptive QEKF Based on Strong Tracking Algorithm for Integrated Navigation
XIA Lin-lin,ZHAO Lin,CHENG Jian-hua.Research on Adaptive QEKF Based on Strong Tracking Algorithm for Integrated Navigation[J].Acta Geodaetica et Cartographica Sinica,2008,37(4):410-417.
Authors:XIA Lin-lin  ZHAO Lin  CHENG Jian-hua
Institution:XIA Lin-lin1,ZHAO Lin2,CHENG Jian-hua21.School of Automation Engineering,Northeast Electric Power University,Jilin 132012,China,2.College of Automation,Harbin Engineering University,Harbin 150001,China
Abstract:The parameter model for low cost tightly-coupled Attitude and Heading Reference System(AHRS)/GPS is established based on fusing pseudo_range-pseudo_range rate-heading measurements.Strong Tracking Filtering(STF) is introduced to enhance the tracking effect for the highly changeable states of the system owing to the suboptimal parameters.In sequence,due to the large drifts of Micro-Inertial Measurement Units(MIMUs),the quadratic EKF(QEKF) approach is proposed,and the quadratic truncation error extracted from the linearization is compensated by computing Hessian matrix.Simulation indicates that STQEKF solution can approach the nonlinear model with high accuracy and rapid,accomplishing navigation control for land vehicles.The control effect for attitude and position is increased by 8.9%~38.2% and 48.7%~54.4% respectively compared with the standard EKF,even if the accuracy of the sensors is modest.
Keywords:AHRS/GPS  strong tracking filter  suboptimal parameter  quadratic EKF  Hessian matrix  nonlinear system
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