摘要
针对基于DGPS/DR的移动机器人组合定位问题,采用一种尺度无迹变换扩展卡尔曼滤波(SUT-EKF)算法。根据组合定位系统中的状态方程是非线性的,并且观测方程是线性的特点,将SUT预测移动机器人位姿,利用EKF融合最新观测值更新机器人位姿。该算法在状态预测阶段避免计算Jacobian矩阵,从而有效地减小线性化对非线性系统误差的影响。仿真结果表明,该算法具有较好的滤波精度和稳定性。
Aiming at the integrated localization issue for mobile robot based on DGPS/DR,an algorithm based on scale unscented transformation and extended Kalman filter（SUT-EKF）is used.For the characteristic of nonlinear state equation and linear measurement equation,the robot location can be predicted by SUT and can be updated with new observations by EKF.The algorithm doesn＇t compute the Jacobian matrix,it can decrease effectively the error of nonlinear system brought by the linearization.Simulation results show that the new algorithm has better filtering precision and stability.
出处
《测绘学报》
EI
CSCD
北大核心
2010年第5期528-533,共6页
Acta Geodaetica et Cartographica Sinica
基金
国家863计划(2006AA04Z238)
关键词
尺度无迹变换
扩展卡尔曼滤波
移动机器人
组合定位
scale unscented transformation（SUT）
extended Kalman filter（EKF）
mobile robot
integrated localization
