Self-Tuning Asynchronous Filter for Linear Gaussian System and Applications |
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Authors: | Wenjun Lv Yu Kang Yunbo Zhao |
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Affiliation: | 1.Department of Automation, University of Science and Technology of China, Hefei 230027, China2.State Key Laboratory of Fire Science, Department of Automation and Institute of Advanced Technology, University of Science and Technology of China, Hefei 230027, China3.Key Laboratory of Technology in GeoSpatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China4.College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China |
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Abstract: | In this paper, optimal filtering problem for a class of linear Gaussian systems is studied. The system states are updated at a fast uniform sampling rate and the measurements are sampled at a slow uniform sampling rate. The updating rate of system states is several times the sampling rate of measurements and the multiple is constant. To solve the problem, we will propose a self-tuning asynchronous filter whose contributions are twofold. First, the optimal filter at the sampling times when the measurements are available is derived in the linear minimum variance sense. Furthermore, considering the variation of noise statistics, a regulator is introduced to adjust the filtering coefficients adaptively. The case studies of wheeled robot navigation system and air quality evaluation system will show the effectiveness and practicability in engineering. |
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Keywords: | Air quality evaluation system linear Gaussian system wheeled robot navigation system |
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