Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks

Wireless sensor networks state assessment is one of the areas of research in digital signal processing. Traditional algorithms include centralized and distributed filtering of data received from sensors. These algorithms iteratively use the information obtained in the course of measurements from all...

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Príomhchruthaitheoirí:	Lyakhov, P. A., Ляхов, П. А., Kalita, D. I., Калита, Д. И.
Formáid:	Статья
Teanga:	English
Foilsithe / Cruthaithe:	2023
Ábhair:	Kalman filter Wireless sensor networks Conditionally local combination Distributed filtering Multiplicative noise Reliable filtration
Rochtain ar líne:	https://dspace.ncfu.ru/handle/20.500.12258/24074
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id	ir-20.500.12258-24074
record_format	dspace
spelling	ir-20.500.12258-240742023-07-07T10:10:57Z Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks Lyakhov, P. A. Ляхов, П. А. Kalita, D. I. Калита, Д. И. Kalman filter Wireless sensor networks Conditionally local combination Distributed filtering Multiplicative noise Reliable filtration Wireless sensor networks state assessment is one of the areas of research in digital signal processing. Traditional algorithms include centralized and distributed filtering of data received from sensors. These algorithms iteratively use the information obtained in the course of measurements from all pairs of sensors, leading to an increase in the computational load and a decrease in algorithm reliability. This article proposes an algorithm for distributed reliable filtering with conditionally local aggregation of data received from sensors for a wireless sensor network to solve this problem. Software simulation has shown the possibility of minimizing the upper bound of the mean squared error update error that occurs when processing a noise faulty communication channel compared to known algorithms. The ability to use information from neighboring pairs of sensors and local measurements in the proposed algorithm made it possible to accelerate the appearance of stability of the value in errors. It is proved that the algorithm proposed in the paper is scalable for large networks. The results can be effectively applied in various wireless monitoring systems. 2023-07-07T10:10:18Z 2023-07-07T10:10:18Z 2023 Статья Lyakhov, P.A., Kalita, D.I. Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks // Automatic Control and Computer Sciences. - 2023. - 57(2), pp. 154-166. - DOI: 10.3103/S0146411623020062 http://hdl.handle.net/20.500.12258/24074 en Automatic Control and Computer Sciences application/pdf
institution	СКФУ
collection	Репозиторий
language	English
topic	Kalman filter Wireless sensor networks Conditionally local combination Distributed filtering Multiplicative noise Reliable filtration
spellingShingle	Kalman filter Wireless sensor networks Conditionally local combination Distributed filtering Multiplicative noise Reliable filtration Lyakhov, P. A. Ляхов, П. А. Kalita, D. I. Калита, Д. И. Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
description	Wireless sensor networks state assessment is one of the areas of research in digital signal processing. Traditional algorithms include centralized and distributed filtering of data received from sensors. These algorithms iteratively use the information obtained in the course of measurements from all pairs of sensors, leading to an increase in the computational load and a decrease in algorithm reliability. This article proposes an algorithm for distributed reliable filtering with conditionally local aggregation of data received from sensors for a wireless sensor network to solve this problem. Software simulation has shown the possibility of minimizing the upper bound of the mean squared error update error that occurs when processing a noise faulty communication channel compared to known algorithms. The ability to use information from neighboring pairs of sensors and local measurements in the proposed algorithm made it possible to accelerate the appearance of stability of the value in errors. It is proved that the algorithm proposed in the paper is scalable for large networks. The results can be effectively applied in various wireless monitoring systems.
format	Статья
author	Lyakhov, P. A. Ляхов, П. А. Kalita, D. I. Калита, Д. И.
author_facet	Lyakhov, P. A. Ляхов, П. А. Kalita, D. I. Калита, Д. И.
author_sort	Lyakhov, P. A.
title	Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
title_short	Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
title_full	Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
title_fullStr	Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
title_full_unstemmed	Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks
title_sort	reliable kalman filtering with conditionally local calculations in wireless sensor networks
publishDate	2023
url	https://dspace.ncfu.ru/handle/20.500.12258/24074
work_keys_str_mv	AT lyakhovpa reliablekalmanfilteringwithconditionallylocalcalculationsinwirelesssensornetworks AT lâhovpa reliablekalmanfilteringwithconditionallylocalcalculationsinwirelesssensornetworks AT kalitadi reliablekalmanfilteringwithconditionallylocalcalculationsinwirelesssensornetworks AT kalitadi reliablekalmanfilteringwithconditionallylocalcalculationsinwirelesssensornetworks
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Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks

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