卡尔曼滤波在无人机导航系统的应用

Application of Kalman Filter in UAV Navigation System

无人机具有在三维空间中的机动能力,能够进入人类很难到达的环境中完成许多危险的任务。针对无人机在未知环境中短暂GPS丢星的导航问题,根据GPS、惯性导航系统的各自优、缺点,设计了一种集中式卡尔曼滤波组合,即采用一个共同的卡尔曼滤波器对GPS和INS进行信息融合。测量数据取自最优估计后的GPS数据,滤波方程的状态矢量是惯性导航系统参数误差状态和GPS导航参数误差状态的组合,用来对原系统校正,增加了无人机导航系统的可靠性,提高了系统的精度和抗干扰能力。对保证无人机长久飞行及面临短暂丢星等方面具有较强的现实应用意义。

UAV has the ability to maneuver in three -dimensional space, which makes themselves able to enter the environment which is difficult for humans to reach and to complete many dangerous tasks. In order to solve the problem, when the signal of GPS is lost temporarily, a kind of centralized Kalman filter is designed according to the advantages and disadvantages of GPS and inertial navigation system. It is used to deal with the data of fil- tercd GPS and inertial navigation system, and the measured data are taken from the GPS data after the optimal estimation. The state vector of the filter equation is a combination of the parameters of the inertial navigation sys- tem and the state of the GPS navigation parameters, which is used to correct the original system in order to obtain accurate navigation parameters, and verify the effectiveness of algorithm by simulation.