Aiming at the problem that indoor positioning technology based on wireless ultra-wideband pulse technology is susceptible to non-line-of-sight effects and multipath effects in confined spaces and weak signal environme...Aiming at the problem that indoor positioning technology based on wireless ultra-wideband pulse technology is susceptible to non-line-of-sight effects and multipath effects in confined spaces and weak signal environments,a high-precision positioning system based on UWB and IMU in a confined environment is designed.The STM32 chip is used as the main control,and the data information of IMU and UWB is fused by the fusion filtering algorithm.Finally,the real-time information of the positioning is transmitted to the host computer and the cloud.The experimental results show that the positioning accuracy and positioning stability of the system have been improved in the non-line-of-sight case of closed environment.The system has high positioning accuracy in a closed environment,and the components used are consumer-grade,which has strong practicability.展开更多
减小非视距(Non Line Of Sight,NLOS)误差定位算法大多要求在移动台和基站之间至少存在一条视距(Line Of Sight,LOS)路径。提出一种新的NLOS环境中基于散射模型分类传播环境的TOA(Time Of Arrival)定位方法,将散射模型中NLOS传播的统计...减小非视距(Non Line Of Sight,NLOS)误差定位算法大多要求在移动台和基站之间至少存在一条视距(Line Of Sight,LOS)路径。提出一种新的NLOS环境中基于散射模型分类传播环境的TOA(Time Of Arrival)定位方法,将散射模型中NLOS传播的统计特性加入到定位算法中,使用散射模型研究了3种定位算法,方差匹配算法,期望最大算法和贝叶斯算法。并对算法进行仿真,仿真结果表明,本算法性能优于传统定位算法。展开更多
Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a ...Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.展开更多
In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environ...In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.展开更多
Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex enviro...Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.展开更多
This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good resul...This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.展开更多
针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-...针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-CS)。该方法在交互式多模型的框架内,利用CS在机动目标跟踪方面的优势,并选择具有较高跟踪精度且计算代价较低的UKF作为子滤波器。仿真结果表明:在LOS/NLOS混合环境中,IMM-UKF-CS具有较高的跟踪精度、较强的鲁棒性及较低的时间代价,具有良好的应用价值。展开更多
在高大建筑物、树木遮挡等城市复杂环境中,多路径误差和纯反射(NLOS)信号误差难以准确建模,严重影响行人GNSS导航定位的精度和可用性。本文首先对比分析了多路径延迟和纯反射信号延迟的误差特性,然后利用双差观测方程提取多路径和NLOS...在高大建筑物、树木遮挡等城市复杂环境中,多路径误差和纯反射(NLOS)信号误差难以准确建模,严重影响行人GNSS导航定位的精度和可用性。本文首先对比分析了多路径延迟和纯反射信号延迟的误差特性,然后利用双差观测方程提取多路径和NLOS延迟误差,分析了两种延迟误差对伪距、载波相位和多普勒观测值的影响。通过UBLOX-NEO-M8T单频导航型接收机在建筑物附近和树木遮挡两种观测环境下的实测数据处理与分析,结果表明:载噪比(C/N0)较小时多普勒噪声明显变大。对于M8T导航型接收机,多路径影响严重的环境下C/N0低于30 d BHz,多普勒噪声变大。而NLOS影响严重的环境下多普勒噪声与C/N0之间关系不明显,在较大的C/N0,多普勒噪声仍然很大;在树木遮挡时,主要受多路径效应的影响,引起伪距的误差量级在10~150 m之间,对相位和多普勒的影响不明显;在高楼遮挡时,会出现NLOS信号干扰,对伪距和载波相位观测值的影响相同,延迟量大小与反射点的距离有关,可达到几百米,对多普勒观测值也有明显影响。展开更多
针对动态环境下超宽带(Ultra Wide Band,UWB)测距易受到非视距(Not Line of Sight,NLOS)因素影响的问题,基于非对称双边双向测距(Asymmetric Double-Sided Two-Way Ranging,ADS-TWR)算法设计实验以探究常见NLOS因素(钢板、人体、木板)对...针对动态环境下超宽带(Ultra Wide Band,UWB)测距易受到非视距(Not Line of Sight,NLOS)因素影响的问题,基于非对称双边双向测距(Asymmetric Double-Sided Two-Way Ranging,ADS-TWR)算法设计实验以探究常见NLOS因素(钢板、人体、木板)对UWB测距的影响。实验结果表明:NLOS对测距的影响程度不仅与遮挡物性质有关,还与其位置相关,在1.6m范围内越靠近UWB节点,NLOS误差越显著,超过1.6m后测距结果在一定程度上能够满足测距需求;在节点间距动态变化过程中出现NLOS因素时,测距输出值变化速率显著增大。根据分析所得动态NLOS误差特征,提出一种NLOS快速判断方法,设计自适应状态更新方程的卡尔曼滤波消减NLOS影响,经实验验证可提升50%以上的测距精度。展开更多
文摘Aiming at the problem that indoor positioning technology based on wireless ultra-wideband pulse technology is susceptible to non-line-of-sight effects and multipath effects in confined spaces and weak signal environments,a high-precision positioning system based on UWB and IMU in a confined environment is designed.The STM32 chip is used as the main control,and the data information of IMU and UWB is fused by the fusion filtering algorithm.Finally,the real-time information of the positioning is transmitted to the host computer and the cloud.The experimental results show that the positioning accuracy and positioning stability of the system have been improved in the non-line-of-sight case of closed environment.The system has high positioning accuracy in a closed environment,and the components used are consumer-grade,which has strong practicability.
文摘减小非视距(Non Line Of Sight,NLOS)误差定位算法大多要求在移动台和基站之间至少存在一条视距(Line Of Sight,LOS)路径。提出一种新的NLOS环境中基于散射模型分类传播环境的TOA(Time Of Arrival)定位方法,将散射模型中NLOS传播的统计特性加入到定位算法中,使用散射模型研究了3种定位算法,方差匹配算法,期望最大算法和贝叶斯算法。并对算法进行仿真,仿真结果表明,本算法性能优于传统定位算法。
基金supported in part by the Joint Project of National Natural Science Foundation of China(U22B2004,62371106)in part by China Mobile Research Institute&X-NET(Project Number:2022H002)+6 种基金in part by the Pre-Research Project(31513070501)in part by National Key R&D Program(2018AAA0103203)in part by Guangdong Provincial Research and Development Plan in Key Areas(2019B010141001)in part by Sichuan Provincial Science and Technology Planning Program of China(2022YFG0230,2023YFG0040)in part by the Fundamental Enhancement Program Technology Area Fund(2021-JCJQ-JJ-0667)in part by the Joint Fund of ZF and Ministry of Education(8091B022126)in part by Innovation Ability Construction Project for Sichuan Provincial Engineering Research Center of Communication Technology for Intelligent IoT(2303-510109-04-03-318020).
文摘Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.
基金supported by National Natural Science Foundation of China(NSFC)(No.62101274 and 62101275)Natural Science Foundation of Jiangsu Province(BK20210640)Open Research Fund of National Mobile Communications Research Laboratory Southeast University under Grant 2021D03。
文摘In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.
基金supported by the National Natural Science Foundation of China under Grant No.62273083 and No.61973069Natural Science Foundation of Hebei Province under Grant No.F2020501012。
文摘Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.
基金supported by the National Natural Science Foundation of China(62201510,62001091,61801435,61871080,61801435)the Initial Scientific Research Foundation of University of Science and Technology of China(Y030202059018051)+2 种基金Yangtze River Scholar Program,Sichuan Science and Technology Program(2019JDJQ0014)111 Project(B17008)Henan Provincial Department of Science and Technology Research Project(202102210315,212102210029,202102210-137).
文摘This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.
文摘针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-CS)。该方法在交互式多模型的框架内,利用CS在机动目标跟踪方面的优势,并选择具有较高跟踪精度且计算代价较低的UKF作为子滤波器。仿真结果表明:在LOS/NLOS混合环境中,IMM-UKF-CS具有较高的跟踪精度、较强的鲁棒性及较低的时间代价,具有良好的应用价值。
文摘在高大建筑物、树木遮挡等城市复杂环境中,多路径误差和纯反射(NLOS)信号误差难以准确建模,严重影响行人GNSS导航定位的精度和可用性。本文首先对比分析了多路径延迟和纯反射信号延迟的误差特性,然后利用双差观测方程提取多路径和NLOS延迟误差,分析了两种延迟误差对伪距、载波相位和多普勒观测值的影响。通过UBLOX-NEO-M8T单频导航型接收机在建筑物附近和树木遮挡两种观测环境下的实测数据处理与分析,结果表明:载噪比(C/N0)较小时多普勒噪声明显变大。对于M8T导航型接收机,多路径影响严重的环境下C/N0低于30 d BHz,多普勒噪声变大。而NLOS影响严重的环境下多普勒噪声与C/N0之间关系不明显,在较大的C/N0,多普勒噪声仍然很大;在树木遮挡时,主要受多路径效应的影响,引起伪距的误差量级在10~150 m之间,对相位和多普勒的影响不明显;在高楼遮挡时,会出现NLOS信号干扰,对伪距和载波相位观测值的影响相同,延迟量大小与反射点的距离有关,可达到几百米,对多普勒观测值也有明显影响。
文摘针对动态环境下超宽带(Ultra Wide Band,UWB)测距易受到非视距(Not Line of Sight,NLOS)因素影响的问题,基于非对称双边双向测距(Asymmetric Double-Sided Two-Way Ranging,ADS-TWR)算法设计实验以探究常见NLOS因素(钢板、人体、木板)对UWB测距的影响。实验结果表明:NLOS对测距的影响程度不仅与遮挡物性质有关,还与其位置相关,在1.6m范围内越靠近UWB节点,NLOS误差越显著,超过1.6m后测距结果在一定程度上能够满足测距需求;在节点间距动态变化过程中出现NLOS因素时,测距输出值变化速率显著增大。根据分析所得动态NLOS误差特征,提出一种NLOS快速判断方法,设计自适应状态更新方程的卡尔曼滤波消减NLOS影响,经实验验证可提升50%以上的测距精度。