It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present...It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.展开更多
Urban traffic volume detection is an essential part of trafficplanning in terms of urban planning in China. To improve the statisticsefficiency of road traffic volume, this thesis proposes a method for predictingmotor...Urban traffic volume detection is an essential part of trafficplanning in terms of urban planning in China. To improve the statisticsefficiency of road traffic volume, this thesis proposes a method for predictingmotor vehicle traffic volume on urban roads in small and medium-sizedcities during the traffic peak hour by using mobile signal technology. Themethod is verified through simulation experiments, and the limitations andthe improvement methods are discussed. This research can be divided intothree parts: Firstly, the traffic patterns of small and medium-sized cities areobtained through a questionnaire survey. A total of 19745 residents weresurveyed in Luohe, a medium-sized city in China and five travel modes oflocal people were obtained. Secondly, after the characteristics of residents’rest and working time are investigated, a method is proposed in this studyfor the distribution of urban residential and working places based on mobilephone signaling technology. Finally, methods for predicting traffic volume ofthese travel modes are proposed after the characteristics of these travel modesand methods for the distribution of urban residential and working placesare analyzed. Based on the actual traffic volume data observed at offlineintersections, the project team takes Luohe city as the research object and itverifies the accuracy of the prediction method by comparing the predictiondata. The prediction simulation results of traffic volume show that the averageerror rate of traffic volume is unstable. The error rate ranges from 10% to 30%.In this thesis, simulation experiments and field investigations are adopted toanalyze why these errors occur.展开更多
Brain-computer interface(BCI)technology represents a burgeoning interdisciplinary domain that facilitates direct communication between individuals and external devices.The efficacy of BCI systems is largely contingent...Brain-computer interface(BCI)technology represents a burgeoning interdisciplinary domain that facilitates direct communication between individuals and external devices.The efficacy of BCI systems is largely contingent upon the progress in signal acquisition methodologies.This paper endeavors to provide an exhaustive synopsis of signal acquisition technologies within the realm of BCI by scrutinizing research publications from the last ten years.Our review synthesizes insights from both clinical and engineering viewpoints,delineating a comprehensive two-dimensional framework for understanding signal acquisition in BCIs.We delineate nine discrete categories of technologies,furnishing exemplars for each and delineating the salient challenges pertinent to these modalities.This review furnishes researchers and practitioners with a broad-spectrum comprehension of the signal acquisition landscape in BCI,and deliberates on the paramount issues presently confronting the field.Prospective enhancements in BCI signal acquisition should focus on harmonizing a multitude of disciplinary perspectives.Achieving equilibrium between signal fidelity,invasiveness,biocompatibility,and other pivotal considerations is imperative.By doing so,we can propel BCI technology forward,bolstering its effectiveness,safety,and depend-ability,thereby contributing to an auspicious future for human-technology integration.展开更多
With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social netw...With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social network.This paper explores the social dynamics of such networks by analyzing the eigenvector centrality of vehicles and classifying communication levels based on their centrality rankings.To support this analysis,a communication system is designed using a multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing framework,incorporating the derived communication levels.Within this system,a particle swarm optimization(PSO)algorithm is employed to optimize a radial basis function(RBF)neural network for channel estimation.This approach significantly improves performance,achieving a bit error rate(BER)below 10−4 at relatively low signal-to-noise ratios(SNRs).Moreover,the proposed method enables the system to approach the theoretical channel capacity limit under low SNR conditions.The communication level detection method presented in this work also achieves 100%accuracy across various signal detection techniques.Overall,the proposed signal detection framework offers promising potential for enhancing the performance and reliability of future vehicular communication systems.展开更多
Global Navigation Satellite Systems(GNSS)is able to achieve centimeter-level accuracy in open-sky areas.However,their performance declines in urban canyons and outdoor shadow areas.Conversely,commercial Fifth Generati...Global Navigation Satellite Systems(GNSS)is able to achieve centimeter-level accuracy in open-sky areas.However,their performance declines in urban canyons and outdoor shadow areas.Conversely,commercial Fifth Generation Mobile Communications Technology(5G)New Radio(NR)signals,with their wider bandwidth and shorter wavelengths,ofer better range accuracy.To enhance positioning accuracy in challenging environments,we developed a deeply integrated method to combine commercial 5G NR signals with the GNSS.This method involves three key steps:Firstly,we use the Secondary Synchronization Signal to aid the Demodulation Reference Signal(SA-DMRS)in the 5G NR synchronization channel,which aims to improve the tracking loop robustness.Secondly,a Phase-Stabilized Kalman Filter(PSKF)is integrated into the Phase-Locked Loop to boost performance under low Carrier-to-Noise Density Ratio conditions.Lastly,the Extended Kalman Filter(EKF)is applied to fuse 5G and GNSS signals for positioning,and the results are fed back to correct the 5G NR tracking loop.Field tests revealed that SA-DMRS boosted range accuracy by 42.3%,PSKF contributed a further 17%improvement,and GNSS-aided improved the range accuracy by about 33.3%.Compared to the GPS(Global Positioning System)-EKF method,our fusion approach enhances horizontal positioning accuracy by approximately 49.8%,and the vertical positioning accuracy is improved by about 53.3%.Additionally,compared to the GPS-only method,the proposed method can still provide positioning services when there are three usable satellites.Compared with the GNSS-only method,the deep coupled method improved the accuracy in the horizontal and vertical by about 51.2%and 24.0%,respectively.These confrm the method’s efectiveness for accurate and reliable positioning in challenging environments.展开更多
文摘It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.
文摘Urban traffic volume detection is an essential part of trafficplanning in terms of urban planning in China. To improve the statisticsefficiency of road traffic volume, this thesis proposes a method for predictingmotor vehicle traffic volume on urban roads in small and medium-sizedcities during the traffic peak hour by using mobile signal technology. Themethod is verified through simulation experiments, and the limitations andthe improvement methods are discussed. This research can be divided intothree parts: Firstly, the traffic patterns of small and medium-sized cities areobtained through a questionnaire survey. A total of 19745 residents weresurveyed in Luohe, a medium-sized city in China and five travel modes oflocal people were obtained. Secondly, after the characteristics of residents’rest and working time are investigated, a method is proposed in this studyfor the distribution of urban residential and working places based on mobilephone signaling technology. Finally, methods for predicting traffic volume ofthese travel modes are proposed after the characteristics of these travel modesand methods for the distribution of urban residential and working placesare analyzed. Based on the actual traffic volume data observed at offlineintersections, the project team takes Luohe city as the research object and itverifies the accuracy of the prediction method by comparing the predictiondata. The prediction simulation results of traffic volume show that the averageerror rate of traffic volume is unstable. The error rate ranges from 10% to 30%.In this thesis, simulation experiments and field investigations are adopted toanalyze why these errors occur.
基金supported by the National Natural Science Foun-dation of China(U2241208,62171473,61671424)the National Key Research and Development Program of China(2022YFC3602803,2023YFF1205300)Key Research and Development Program of Ningxia(2023BEG02063)。
文摘Brain-computer interface(BCI)technology represents a burgeoning interdisciplinary domain that facilitates direct communication between individuals and external devices.The efficacy of BCI systems is largely contingent upon the progress in signal acquisition methodologies.This paper endeavors to provide an exhaustive synopsis of signal acquisition technologies within the realm of BCI by scrutinizing research publications from the last ten years.Our review synthesizes insights from both clinical and engineering viewpoints,delineating a comprehensive two-dimensional framework for understanding signal acquisition in BCIs.We delineate nine discrete categories of technologies,furnishing exemplars for each and delineating the salient challenges pertinent to these modalities.This review furnishes researchers and practitioners with a broad-spectrum comprehension of the signal acquisition landscape in BCI,and deliberates on the paramount issues presently confronting the field.Prospective enhancements in BCI signal acquisition should focus on harmonizing a multitude of disciplinary perspectives.Achieving equilibrium between signal fidelity,invasiveness,biocompatibility,and other pivotal considerations is imperative.By doing so,we can propel BCI technology forward,bolstering its effectiveness,safety,and depend-ability,thereby contributing to an auspicious future for human-technology integration.
基金supported by the Open Fund Project of Key Laboratory of Marine Environmental Survey Technology and Application,Ministry of Natural Resources(No.MESTA-2024-B004).
文摘With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social network.This paper explores the social dynamics of such networks by analyzing the eigenvector centrality of vehicles and classifying communication levels based on their centrality rankings.To support this analysis,a communication system is designed using a multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing framework,incorporating the derived communication levels.Within this system,a particle swarm optimization(PSO)algorithm is employed to optimize a radial basis function(RBF)neural network for channel estimation.This approach significantly improves performance,achieving a bit error rate(BER)below 10−4 at relatively low signal-to-noise ratios(SNRs).Moreover,the proposed method enables the system to approach the theoretical channel capacity limit under low SNR conditions.The communication level detection method presented in this work also achieves 100%accuracy across various signal detection techniques.Overall,the proposed signal detection framework offers promising potential for enhancing the performance and reliability of future vehicular communication systems.
基金The National Natural Science Foundation of China(42171417)Medium-and Long-term Scientifc and Technological Planning Projects for Radio,Television and Audio-Visual Networks+1 种基金Guangxi Science and Technology Major Project(AA22068072)Major Science and Technology Project of Jiangsu Province(No.BG2024003).
文摘Global Navigation Satellite Systems(GNSS)is able to achieve centimeter-level accuracy in open-sky areas.However,their performance declines in urban canyons and outdoor shadow areas.Conversely,commercial Fifth Generation Mobile Communications Technology(5G)New Radio(NR)signals,with their wider bandwidth and shorter wavelengths,ofer better range accuracy.To enhance positioning accuracy in challenging environments,we developed a deeply integrated method to combine commercial 5G NR signals with the GNSS.This method involves three key steps:Firstly,we use the Secondary Synchronization Signal to aid the Demodulation Reference Signal(SA-DMRS)in the 5G NR synchronization channel,which aims to improve the tracking loop robustness.Secondly,a Phase-Stabilized Kalman Filter(PSKF)is integrated into the Phase-Locked Loop to boost performance under low Carrier-to-Noise Density Ratio conditions.Lastly,the Extended Kalman Filter(EKF)is applied to fuse 5G and GNSS signals for positioning,and the results are fed back to correct the 5G NR tracking loop.Field tests revealed that SA-DMRS boosted range accuracy by 42.3%,PSKF contributed a further 17%improvement,and GNSS-aided improved the range accuracy by about 33.3%.Compared to the GPS(Global Positioning System)-EKF method,our fusion approach enhances horizontal positioning accuracy by approximately 49.8%,and the vertical positioning accuracy is improved by about 53.3%.Additionally,compared to the GPS-only method,the proposed method can still provide positioning services when there are three usable satellites.Compared with the GNSS-only method,the deep coupled method improved the accuracy in the horizontal and vertical by about 51.2%and 24.0%,respectively.These confrm the method’s efectiveness for accurate and reliable positioning in challenging environments.
