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Design of an Adaptive Two-step Kalman Filter Based on Fuzzy Logic |
JIN Mei1, ZHANG Zhi-fu1, JIN JU2, YU Guo-hui3, LI Wen-chao1 |
1.Measurement Technology and Instrumentation Key Lab of Hebei Province,Yanshan University, Qinhuangdao,Hebei 066004, China;
2.School of Civil Engineering, Hebei University of Technology, Tianjin 300401, China;
3.Audio-Visual Machinery Research Institute, Qinhuangdao, Hebei 066004, China |
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Abstract To analyze the modeling of the inertial/magnetic tracking system, the centralized Kalman filter algorithm depending on PC is often used to process the data. Because this algorithm is complex and the data processing speed is slow, it is difficult to realize high-speed motion tracking in the embedded system. An adaptive two-step Kalman filter method based on fuzzy logic for real-time motion tracking of human body is proposed. The parameters of Kalman filter are self- adjusted according to the different motion states of human body. The method can not only improve the estimation accuracy and fault-tolerant performance of the system to a certain degree, but also reduce the matrix dimension.
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