Design of unbiased state estimators for WSNs with consensus on measurements and estimates and improved robustness (2019)
Abstract / truncated to 115 words
Wireless sensor networks (WSNs) is a technology with important developments in recent years. Its incursion in areas such as healthcare, industry and services has been steadily increasing, mainly due to the miniaturization of electronics and the growing acceptance of cyber-physical systems. However, a very important subject of research continues to be the development of estimators with the robustness needed for the harsh conditions associated with the WSNs applications. Moreover, such estimators should comply with the unique characteristics imposed by the WSNs like scalability, energy saving and redundancy, while maintaining a consensus on the network. A very popular algorithm for optimal estimation is the Kalman filter (KF). Many works have implemented it as a sensor fusion ... toggle 6 keywordswireless sensor network – state estimation – consensus on measuremens – consensus on estimates – ufir filter – kalman filter
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