Publications
Talk · Mediterranean Conference on Embedded Computing · June 7, 2022
Efficient Probabilistic Filtering of Data Subject to Channel Noise Under Local Pooling Conditions
Pavel Alekseyevich Lyakhov, Калита Диана Ивановна, Aleksandr Sinitca, Alexander S. Voznesensky
Abstract
The widespread use of wireless sensor networks has led to the solution of one of the important problems associated with assessing their state in conditions of damaged communication channels. Known evaluation algorithms are based on a centralized or distributed data filtering structure. This paper proposes a distributed algorithm of three-stage Kalman filtering, which combines and processes data locally. The proposed design of the algorithm made it possible to reduce and stabilize the mean square error of the filter and limit it uniformly from above.
Target Tracking and Data Fusion in Sensor NetworksDistributed Sensor Networks and Detection AlgorithmsAdvanced Adaptive Filtering TechniquesKalman filterwireless sensor networkschannel noise
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