Fuzzy Adaptive Kalman Filter Algorithm for RUAV’s Integrated Navigation System

摘要：

The Kalman filter has characteristics of the noise–sensitive. This paper analyzes the adaptive Kalman filter algorithms which are based on Sage-Husae, neural network and fuzzy logic method. And an adaptive Kalman filter based on fuzzy logic is designed to estimate the attitude, heading and velocity of the RUAV. Combining the characteristics of RUAV platform and analyzing the real flight data, the fuzzy inference rules are designed to change the filtering parameters. With the actual flight data, the simulation verifies the validity of this algorithm. The experiments prove that this method can improve the navigation precision of RUAV.

关键词： Integrated Navigation Adaptive Kalman Filter Fuzzy Logic

作者: Lei Dai Chong Wu Juntong Qi Janda Han

作者单位: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 2877-2881

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）