基于三轴磁强计和重力测量的融合导航算法  

An Integrated Navigation Algorithm Based on Three-Axis Magnetometer and Gravity Measurement

作　　者：吴萌[1] 马杰[1] 田金文[1] 刘劲[1] 

机构地区：[1]华中科技大学多谱信息处理技术国家重点实验室,湖北武汉430074

出　　处：《信息与控制》2011年第6期760-766,共7页Information and Control

基　　金：国家863计划资助项目(2006AAJ109);航空科学基金资助项目(20070818001)

摘　　要：为了减小地磁导航的估计误差协方差,提高导航的可靠性和准确性,将重力作为一种新的量测信息引入到地磁导航系统中,提出了基于三轴磁强计与重力测量的融合导航算法.该算法以飞行器的位置与速度向量作为状态向量,建立状态方程;以飞行器所在位置的地磁场强度矢量与重力场强度矢量作为观测向量,建立观测方程;设计了一种联邦滤波器,用于融合三轴磁强计与重力测量仪表提供的量测信息.由于量测方程与状态方法都是非线性的,因此采用无迹卡尔曼滤波器(UKF)作为子滤波器可获得较高精度.仿真结果表明:该方法得到的位置估计误差小于30m,速度误差小于5m/s.与单一地磁导航、重力导航方法相比,该组合导航方法显示出更好的收敛性与可靠性.In order to reduce the estimation error covariance of geomagnetic navigation and improve the reliability and the stability of geomagnetic navigation, an integrated navigation algorithm based on three-axis magnetometer and gravity measurement is proposed which introduces gravity as new measure information into the geomagnetic navigation system. The algorithm uses the position and the velocity of the aircraft as state vectors to establish state equation, and the intensity vectors of the magnetic field and the gravity field as observation vectors to establish observation equation. A kind of federated filter is designed to fuse the measured information from three-axis magnetometer and gravity measurement. For both the state and the measurement equations of those two methods are nonlinear, the unscented Kalman filter （UKF） is used as the sub- filter to improve the accuracy. The simulation results show that the position estimation error of the method is less than 30 m and velocity estimation error is less than 5 m/s. Comparing with mono-geomagnetic navigation system and mono-gravity navigation system, the integrated navigation algorithm shows better convergence and reliability.

关 键 词：三轴磁强计 重力测量 联邦滤波 子滤波器 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计]