为解决室内非视距(non line of sight,NLOS)环境以及低信标部署密度下传统定位算法精度急剧下降的问题,提出一种基于测距修正的低功耗蓝牙(bluetooth low energy,BLE)和行人航位推算(pedestrian dead reckoning,PDR)融合定位方法。通过S...为解决室内非视距(non line of sight,NLOS)环境以及低信标部署密度下传统定位算法精度急剧下降的问题,提出一种基于测距修正的低功耗蓝牙(bluetooth low energy,BLE)和行人航位推算(pedestrian dead reckoning,PDR)融合定位方法。通过SketchUp室内3D建模软件联合射线追踪算法实现BLE的接收信号强度(received signal strength,RSS)快速构建,避免人工繁琐的RSS实地采集。设计一种基于卷积神经网络的变分自编码器(variational autoencoder based on convolution neural network,VAE-CNN)模型对BLE测距误差进行预测和修正,提升BLE定位精度。采用扩展卡尔曼滤波(extended Kalman filter,EKF)融合BLE和PDR的定位结果。实验结果表明,采用测距修正后的BLE测距定位以及EKF融合定位在NLOS以及信标部署密度低的环境下具有较好的定位性能。展开更多
Bluetooth low energy(BLE)-based indoor localization has been extensively researched due to its cost-effectiveness,low power consumption,and ubiquity.Despite these advantages,the variability of received signal strength...Bluetooth low energy(BLE)-based indoor localization has been extensively researched due to its cost-effectiveness,low power consumption,and ubiquity.Despite these advantages,the variability of received signal strength indicator(RSSI)measurements,influenced by physical obstacles,human presence,and electronic interference,poses a significant challenge to accurate localization.In this work,we present an optimised method to enhance indoor localization accuracy by utilising multiple BLE beacons in a radio frequency(RF)-dense modern building environment.Through a proof-of-concept study,we demonstrate that using three BLE beacons reduces localization error from a worst-case distance of 9.09-2.94 m,whereas additional beacons offer minimal incremental benefit in such settings.Furthermore,our framework for BLE-based localization,implemented on an edge network of Raspberry Pies,has been released under an open-source license,enabling broader application and further research.展开更多
Secure multicasting is one of the major requirementsfor today’s communication arena.And for any kindof secure communication,a key-distribution schemeis the most sensible part.Being a highly promising,low-cost,and eme...Secure multicasting is one of the major requirementsfor today’s communication arena.And for any kindof secure communication,a key-distribution schemeis the most sensible part.Being a highly promising,low-cost,and emerging wireless technology,Bluetooth has key distribution supports for securemulticasting over its unit one-hop network,piconet.Bluetooth core specification[1]defines basic securityprotocols for key generation,encryption,andauthentication for intra-piconet security.However,not much attention has been paid so far on securingmulticasting over the Bluetooth Scatternet;nevertheless,multicasting is quite a sensible aspectof modern communication arena.Here in this paper,we extend the piconets key distribution scheme topresent a new key management scheme for securemulticasting over Bluetooth Scatternets.Our keymanagement scheme is compatible to the currentBluetooth architecture design as we rely onBluetooth’s existing security algorithms to proposeour resolution.展开更多
文摘为解决室内非视距(non line of sight,NLOS)环境以及低信标部署密度下传统定位算法精度急剧下降的问题,提出一种基于测距修正的低功耗蓝牙(bluetooth low energy,BLE)和行人航位推算(pedestrian dead reckoning,PDR)融合定位方法。通过SketchUp室内3D建模软件联合射线追踪算法实现BLE的接收信号强度(received signal strength,RSS)快速构建,避免人工繁琐的RSS实地采集。设计一种基于卷积神经网络的变分自编码器(variational autoencoder based on convolution neural network,VAE-CNN)模型对BLE测距误差进行预测和修正,提升BLE定位精度。采用扩展卡尔曼滤波(extended Kalman filter,EKF)融合BLE和PDR的定位结果。实验结果表明,采用测距修正后的BLE测距定位以及EKF融合定位在NLOS以及信标部署密度低的环境下具有较好的定位性能。
基金supported by James M.Cox Foundation,National Institute on Deafness and Other Communication Disorders(grant no.1R21DC021029-01A1)Cox Enterprises Inc.,National Institute of Child Health and Human Development(grant no.AWD-006196-G1)Thrasher Research Fund Early Career Award Program.
文摘Bluetooth low energy(BLE)-based indoor localization has been extensively researched due to its cost-effectiveness,low power consumption,and ubiquity.Despite these advantages,the variability of received signal strength indicator(RSSI)measurements,influenced by physical obstacles,human presence,and electronic interference,poses a significant challenge to accurate localization.In this work,we present an optimised method to enhance indoor localization accuracy by utilising multiple BLE beacons in a radio frequency(RF)-dense modern building environment.Through a proof-of-concept study,we demonstrate that using three BLE beacons reduces localization error from a worst-case distance of 9.09-2.94 m,whereas additional beacons offer minimal incremental benefit in such settings.Furthermore,our framework for BLE-based localization,implemented on an edge network of Raspberry Pies,has been released under an open-source license,enabling broader application and further research.
文摘Secure multicasting is one of the major requirementsfor today’s communication arena.And for any kindof secure communication,a key-distribution schemeis the most sensible part.Being a highly promising,low-cost,and emerging wireless technology,Bluetooth has key distribution supports for securemulticasting over its unit one-hop network,piconet.Bluetooth core specification[1]defines basic securityprotocols for key generation,encryption,andauthentication for intra-piconet security.However,not much attention has been paid so far on securingmulticasting over the Bluetooth Scatternet;nevertheless,multicasting is quite a sensible aspectof modern communication arena.Here in this paper,we extend the piconets key distribution scheme topresent a new key management scheme for securemulticasting over Bluetooth Scatternets.Our keymanagement scheme is compatible to the currentBluetooth architecture design as we rely onBluetooth’s existing security algorithms to proposeour resolution.
