Less Computational Unscented Kalman Filter for Practical State Estimation of Small Scale Unmanned Helicopters

摘要：

This paper presents the unscented Kalman filter (UKF) with reduced simplex sigma-point for the navigation system in a small scale unmanned helicopter. UKF is widely applied to nonlinear systems. However, the disadvantage of traditional UKF is the high computational cost caused by the unscented transformation step. The computational cost is proportional to the number of the constructed sigma-points. Therefore a reduced simplex sigma-point selection is proposed to be practically applied for the sensor fusion on the unmanned helicopter. The simulation and experimental results verify the computational load reduction.

关键词： Unscented Kalman Filter Sigma points Sensor fusion Unmanned helicopter

作者: Wenwu Zeng Xiaorui Zhu Yanjie Li Zexiang Li

作者单位: Harbin Institute of Technology Shenzhen Graduate School,Shenzhen,Guangdong 518055,China Hong Kong University of Science and Technology,Hong Kong

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 1658-1663

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）