State estimation over lossy channel via online measurement coding: Algorithm design and performance optimization |
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| Institution: | 1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;2. Department of Automation, Shanghai University, Shanghai 200444, China;3. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China;1. School of Automation, Beijing Institute of Technology, Beijing 100081, PR China;2. Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA;1. School of Computer Science & Techology, Tianjin Polytechnic University, Tianjin 300387, China;2. Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems, Tianjin Polytechnic University, Tianjin 300387, China;1. Faculty of Physics, Semnan University P.O. Box: 35195-363, Semnan, Iran;2. Department of Physics, Alzahra University, Tehran, Iran;3. Department of Electrical Engineering, Tarbiat Modares University, Tehran, Iran;1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, PR China;2. State Key Laboratory of Synthetical Automation of Process Industries, Northeastern University, Shenyang 110819, PR China;1. Department of Mechanical Engineering Sciences, University of Surrey, Guilford, UK;2. Department of Automatic Control, Universitat Politècnica de Catalunya, Barcelona, Spain;3. Department of Mathematics & Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain;4. Department of Electrical and Electronic Engineering, Universidad de Cuenca, Cuenca, Ecuador;1. Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, 150001 Harbin, People''s Republic of China;2. Department of Control Science and Engineering, Harbin Institute of Technology, 150001 Harbin, People''s Republic of China |
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| Abstract: | Unpredictable packet loss that occurs in the channel connecting a local sensor and a remote estimator will deteriorate the performance of state estimation. To relieve this detrimental impact, an online linear temporal coding scheme is studied in this paper. If the packet of the last step is lost, a linear combination of the current and the last measurements with proper weights is transmitted; otherwise, only the current data is sent. By virtue of the innovation sequence approach, a linear minimum mean-squared error estimation algorithm is designed. To optimize performance, a novel estimator is also proposed which provides a recursive expression of the error covariances. The proposed two algorithms are proved to be equivalent via a set of transformations. With the aid of some optimization techniques, a recursive algorithm is presented to obtain the optimal coding weight in terms of minimizing the average estimation error covariance. |
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