Abstract
This paper addresses the problem of state estimation in the wireless sensor network (WSN). Firstly, the quantized Kalman filter based on the quantized observations is presented. Focuses are on tradeoff between the communication energy and the estimation accuracy. A closed-form solution to the optimization problem for minimizing the energy consumption is given, where the total energy consumption is minimized subject to a constraint on the stead state error covariance. An illustrative numerical example is provided to demonstrate the usefulness and flexibility of the proposed approach.
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Wang, C., Qi, G., Li, Y., Sheng, A. (2012). Quantized Steady-State Kalman Filter in a Wireless Sensor Network. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_66
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DOI: https://doi.org/10.1007/978-3-642-31020-1_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31019-5
Online ISBN: 978-3-642-31020-1
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