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Optimal Estimation for Multirate Systems with Unreliable Measurements and Correlated Noise

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Kalman Filtering and Information Fusion

Abstract

In recent years, sensor networks have shown to be a persistent focus of research due to the rapid development of technology and its wildly use in multiple industries including military, law enforcement, agricultural and forestry-based projects, surveillance, and even information collection. Accordingly, considerable research attention has been devoted to state estimation techniques over sensor networks, not only due to a large number of potential applications but also because they provide more information than traditional communication systems with a single sensor.

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Authors and Affiliations

  1. School of Automation, Beijing Institute of Technology, Beijing, China

    Hongbin Ma, Liping Yan, Yuanqing Xia & Mengyin Fu

Authors
  1. Hongbin Ma
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  2. Liping Yan
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  3. Yuanqing Xia
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  4. Mengyin Fu
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Correspondence to Hongbin Ma .

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Ma, H., Yan, L., Xia, Y., Fu, M. (2020). Optimal Estimation for Multirate Systems with Unreliable Measurements and Correlated Noise. In: Kalman Filtering and Information Fusion. Springer, Singapore. https://doi.org/10.1007/978-981-15-0806-6_10

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