Self-Adaptive Pattern Recognition Based Kalman Filter Algorithm and Its Application in Indoor Localization

摘要：

Jn this paper,the self-adaptive Pattern Recognition based Kalman Filter (PRKF) is constructed via taken a self-adaptive covariance recursion into the PRKF. Then,the self-adaptive PRKF is simulated in an indoor localization process. Simulation results show that the self-adaptive PRKF is more accurate than PRKF and regular KF,which has a 31.1％ accuracy improvement than PRKF,and 61.0％ accuracy improvement than regular KF.

关键词： Self-adaptive Kalman Filter Pattern recognition Indoor localization

作者: Han Tao Lu Xiaochun Rao Yongnan

作者单位: National Time Service Center,P. R. China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 174-177

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）