Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of Aerospace Technology and Management (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462019000100331 |
Resumo: | ABSTRACT: In modern conditions unmanned aerial vehicles (UAVs) generate new classes of threats, including their use for terrorist purposes. A feature of modern UAVs is the ability to perform sudden maneuvers and to keep the same position in the point in space. For the description of the UAV movement with various types of maneuver it is used a rectangular coordinate system. We use the model in the form of stochastic dynamic system with random structure in the discrete time in which the change type UAV movement occurs at random times. When a UAV emits a sign, its location can be determined by wireless sensor networks (WSN) using the TDOA method. On the basis of a mathematical apparatus of the mixed Markov processes for in discrete time optimal and quasi-optimal adaptive algorithms for filtration of UAV movement parameters based on the TDOA-measurement, sensor networks are synthesized. Devices that realize these algorithms are multichannel and belong to the class of devices with feedback between channels. At the same time, in a quasi-optimal algorithm, a sequential procedure of the arriving measurements from sensors of a sensor network is realized, which allows to avoid the inversion of large-dimensional matrices. An analysis of the quasi-optimal adaptive algorithm is performed using statistical modeling. On the intervals of hovering and of the UAV movements without maneuver, the developed algorithm allows to increase significantly the accuracy of the estimation of the UAV coordinates, and also to recognize various types of its movement with high probability level. |
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Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor NetworksUAVWireless sensor networksOptimal and quasi-optimal adaptive algorithmsParameters of the movementTDOAABSTRACT: In modern conditions unmanned aerial vehicles (UAVs) generate new classes of threats, including their use for terrorist purposes. A feature of modern UAVs is the ability to perform sudden maneuvers and to keep the same position in the point in space. For the description of the UAV movement with various types of maneuver it is used a rectangular coordinate system. We use the model in the form of stochastic dynamic system with random structure in the discrete time in which the change type UAV movement occurs at random times. When a UAV emits a sign, its location can be determined by wireless sensor networks (WSN) using the TDOA method. On the basis of a mathematical apparatus of the mixed Markov processes for in discrete time optimal and quasi-optimal adaptive algorithms for filtration of UAV movement parameters based on the TDOA-measurement, sensor networks are synthesized. Devices that realize these algorithms are multichannel and belong to the class of devices with feedback between channels. At the same time, in a quasi-optimal algorithm, a sequential procedure of the arriving measurements from sensors of a sensor network is realized, which allows to avoid the inversion of large-dimensional matrices. An analysis of the quasi-optimal adaptive algorithm is performed using statistical modeling. On the intervals of hovering and of the UAV movements without maneuver, the developed algorithm allows to increase significantly the accuracy of the estimation of the UAV coordinates, and also to recognize various types of its movement with high probability level.Departamento de Ciência e Tecnologia Aeroespacial2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462019000100331Journal of Aerospace Technology and Management v.11 2019reponame:Journal of Aerospace Technology and Management (Online)instname:Departamento de Ciência e Tecnologia Aeroespacial (DCTA)instacron:DCTA10.5028/jatm.v11.1062info:eu-repo/semantics/openAccessTovkach,Igor OlegovychZhuk,Sergey Yakovycheng2019-08-21T00:00:00Zoai:scielo:S2175-91462019000100331Revistahttp://www.jatm.com.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||secretary@jatm.com.br2175-91461984-9648opendoar:2019-08-21T00:00Journal of Aerospace Technology and Management (Online) - Departamento de Ciência e Tecnologia Aeroespacial (DCTA)false |
dc.title.none.fl_str_mv |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
title |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
spellingShingle |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks Tovkach,Igor Olegovych UAV Wireless sensor networks Optimal and quasi-optimal adaptive algorithms Parameters of the movement TDOA |
title_short |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
title_full |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
title_fullStr |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
title_full_unstemmed |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
title_sort |
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks |
author |
Tovkach,Igor Olegovych |
author_facet |
Tovkach,Igor Olegovych Zhuk,Sergey Yakovych |
author_role |
author |
author2 |
Zhuk,Sergey Yakovych |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Tovkach,Igor Olegovych Zhuk,Sergey Yakovych |
dc.subject.por.fl_str_mv |
UAV Wireless sensor networks Optimal and quasi-optimal adaptive algorithms Parameters of the movement TDOA |
topic |
UAV Wireless sensor networks Optimal and quasi-optimal adaptive algorithms Parameters of the movement TDOA |
description |
ABSTRACT: In modern conditions unmanned aerial vehicles (UAVs) generate new classes of threats, including their use for terrorist purposes. A feature of modern UAVs is the ability to perform sudden maneuvers and to keep the same position in the point in space. For the description of the UAV movement with various types of maneuver it is used a rectangular coordinate system. We use the model in the form of stochastic dynamic system with random structure in the discrete time in which the change type UAV movement occurs at random times. When a UAV emits a sign, its location can be determined by wireless sensor networks (WSN) using the TDOA method. On the basis of a mathematical apparatus of the mixed Markov processes for in discrete time optimal and quasi-optimal adaptive algorithms for filtration of UAV movement parameters based on the TDOA-measurement, sensor networks are synthesized. Devices that realize these algorithms are multichannel and belong to the class of devices with feedback between channels. At the same time, in a quasi-optimal algorithm, a sequential procedure of the arriving measurements from sensors of a sensor network is realized, which allows to avoid the inversion of large-dimensional matrices. An analysis of the quasi-optimal adaptive algorithm is performed using statistical modeling. On the intervals of hovering and of the UAV movements without maneuver, the developed algorithm allows to increase significantly the accuracy of the estimation of the UAV coordinates, and also to recognize various types of its movement with high probability level. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462019000100331 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462019000100331 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5028/jatm.v11.1062 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Ciência e Tecnologia Aeroespacial |
publisher.none.fl_str_mv |
Departamento de Ciência e Tecnologia Aeroespacial |
dc.source.none.fl_str_mv |
Journal of Aerospace Technology and Management v.11 2019 reponame:Journal of Aerospace Technology and Management (Online) instname:Departamento de Ciência e Tecnologia Aeroespacial (DCTA) instacron:DCTA |
instname_str |
Departamento de Ciência e Tecnologia Aeroespacial (DCTA) |
instacron_str |
DCTA |
institution |
DCTA |
reponame_str |
Journal of Aerospace Technology and Management (Online) |
collection |
Journal of Aerospace Technology and Management (Online) |
repository.name.fl_str_mv |
Journal of Aerospace Technology and Management (Online) - Departamento de Ciência e Tecnologia Aeroespacial (DCTA) |
repository.mail.fl_str_mv |
||secretary@jatm.com.br |
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1754732532054622208 |