Zobrazeno 1 - 10
of 25
pro vyhledávání: '"underground personnel positioning"'
Autor:
WANG Taiji
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 6, Pp 103-111 (2024)
In response to the problems of cumulative errors in step size estimation and the large sample size required by traditional deep learning methods in the pedestrian dead reckoning (PDR) based underground personnel positioning system in coal mines, a st
Externí odkaz:
https://doaj.org/article/d54f60aafd1644178a7bb606fe1b6731
Autor:
LI Mingfeng, LI Yan, LIU Yong, WU Xuesong, XU Jisheng, CHANG Jianming, WANG Tao, PAN Hongguang
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 1, Pp 25-34 (2024)
In practical applications of coal mine personnel positioning systems, there are problems of insufficient equipment computing power and storage resources. The problems result in preventing the use of complex ranging and positioning algorithms, inadequ
Externí odkaz:
https://doaj.org/article/29b693beb51b445a911cdbd96aad2336
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 6, Pp 96-102, 135 (2024)
Most existing fusion positioning methods for ultra-wideband (UWB) and pedestrian dead reckoning (PDR) ignore the correction of positioning errors in non line of sight (NLOS) environments. The methods use simple threshold division as the basis for NLO
Externí odkaz:
https://doaj.org/article/6f83dedcfcd44418b6cb5baa97946257
Publikováno v:
Gong-kuang zidonghua, Vol 48, Iss 6, Pp 134-138 (2022)
Aiming at the requirement of high real-time and high precision personnel positioning in underground mine, the positioning algorithm of underground personnel based on ultra wide band (UWB) is studied. The double-sided two-way ranging (DS-TWR) mode is
Externí odkaz:
https://doaj.org/article/46882b0e049e4ce4990755f5a5a641ee
Publikováno v:
Gong-kuang zidonghua, Vol 47, Iss 8, Pp 128-132 (2021)
The positioning accuracy of the precise personnel positioning system in underground mine is affected by the non-line-of-sight error and clock error. At present, the system mostly uses Kalman filter-based positioning method to reduce the error, but th
Externí odkaz:
https://doaj.org/article/977cb143041941b99ac459a35f1ea702
Publikováno v:
Gong-kuang zidonghua, Vol 47, Iss 1, Pp 43-48 (2021)
As the traditional pedestrian dead reckoning (PDR) algorithm being used for underground personnel positioning, the positioning error gradually increases due to the cumulative error of the step frequency detection, step length estimation and heading e
Externí odkaz:
https://doaj.org/article/2162e26eaf914696b3478310d0501627
Publikováno v:
Gong-kuang zidonghua, Vol 46, Iss 3, Pp 63-68 (2020)
Underground WLAN location fingerprinting personnel positioning system mainly realizes overall division of location fingerprinting samples through clustering algorithm, but existing clustering algorithm only carries out the clustering division accordi
Externí odkaz:
https://doaj.org/article/bf8ca30a6e284506b771ea3d9604eef4
Publikováno v:
Gong-kuang zidonghua, Vol 45, Iss 7, Pp 80-85 (2019)
In view of problems of slow convergence, easy to form local extremum and large positioning error in strong time-varying electromagnetic environment of underground positioning algorithms based on traditional BP neural network, an underground adaptive
Externí odkaz:
https://doaj.org/article/45d6d7dcda4945a5a18fc2dd1f5d670a
Publikováno v:
Gong-kuang zidonghua, Vol 45, Iss 4, Pp 43-48 (2019)
In view of problems of large amount of calculation, low real-time performance and low positioning accuracy of existing fingerprint-based underground positioning algorithm, underground personnel positioning algorithm based on clustering and K-nearest
Externí odkaz:
https://doaj.org/article/339d0e41e7014d3fb7ae09bd3917925a
Publikováno v:
Gong-kuang zidonghua, Vol 44, Iss 8, Pp 96-99 (2018)
In view of problems of low positioning accuracy of underground personnel positioning system and incomplete functions of underground personnel vital signs monitoring system, a wearable device with functions of personnel positioning, falling or lying p
Externí odkaz:
https://doaj.org/article/0362b8bfe34f4cb3b4cd721431f2b68b