为了解决传统室内定位技术成本较高、稳定性差以及难于部署等问题,提出一种将到达时间(time of arrival,TOA)与到达角(angle of arrival,AOA)相结合的室内定位系统.该系统由定位基站与被控定位单元组成,其特征在于使用对射式布置的超声...为了解决传统室内定位技术成本较高、稳定性差以及难于部署等问题,提出一种将到达时间(time of arrival,TOA)与到达角(angle of arrival,AOA)相结合的室内定位系统.该系统由定位基站与被控定位单元组成,其特征在于使用对射式布置的超声波传感器获取定位基站与被控定位单元之间的距离特征,利用角度传感器获取被控定位单元相对于定位基站的角度特征,以单基站就实现了精确的室内定位过程.分析了该系统基本结构与原理,建立定位与控制模型,在一定范围内对其定点定位精度与跟随定位精度进行了实验验证.实验结果表明:该系统结构简单,易于安装布置,鲁棒性强,在测试范围内的最大定点定位误差不超过5 cm,跟随定位误差不超过15 cm.展开更多
提出一种在低空场景下基于接收信号强度(Rcecived Signal Strength,RSS)与到达角度(Angle of Arrival,AOA)信息融合的单站无源定位算法。该算法采用单架无人机设备虚拟多站设备接收无线电辐射源信号,融合RSS估计的距离信息与AOA方向角信...提出一种在低空场景下基于接收信号强度(Rcecived Signal Strength,RSS)与到达角度(Angle of Arrival,AOA)信息融合的单站无源定位算法。该算法采用单架无人机设备虚拟多站设备接收无线电辐射源信号,融合RSS估计的距离信息与AOA方向角信息,依据最小二乘准则(LS)构造算法的优化目标函数,采用凸松弛技术将目标函数等价为二阶锥规划(SOCP)问题并通过内点法求解。实验结果表明,该算法的定位精度在2 km范围内可达20 m,其定位性能优于单站无源定位算法,且由于采用单架无人机采集信号,其设备复杂度相较于多站无源定位较低。展开更多
工厂环境下的高精度室内定位对于智能制造、仓储管理和人员安全监控至关重要。以某工厂智能化升级改造为例,阐述基于蓝牙的信号到达角(Angle of Arrival,AOA)定位技术的基本原理,针对工厂前区设备密集、后区相对空旷的特点,采用基于蓝牙...工厂环境下的高精度室内定位对于智能制造、仓储管理和人员安全监控至关重要。以某工厂智能化升级改造为例,阐述基于蓝牙的信号到达角(Angle of Arrival,AOA)定位技术的基本原理,针对工厂前区设备密集、后区相对空旷的特点,采用基于蓝牙的AOA定位技术规划基站部署,优化基站的部署间距和高度。通过立柱交点定位测试法和基站下方定位测试法,验证该系统在不同测试方案下均展现出出色的定位精度,平均误差值分别为0.6 m和0.4 m,满足了设计精度要求。展开更多
传统到达角度(Angle-Of-Arrival,AOA)/接受信号强度指示(Received Signal Strength Indicator,RSSI)混合定位往往需要多个锚节点布设阵列天线以实现高精度定位,为解决在锚节点资源受限下精度较低的问题,提出了一种基于Mesh网络的混合AOA...传统到达角度(Angle-Of-Arrival,AOA)/接受信号强度指示(Received Signal Strength Indicator,RSSI)混合定位往往需要多个锚节点布设阵列天线以实现高精度定位,为解决在锚节点资源受限下精度较低的问题,提出了一种基于Mesh网络的混合AOA/RSSI协作定位方法。仅有中心主锚节点提供AOA角度的情况下,采取最小二乘法对联合真实和虚拟锚节点所对应角度和距离信息进行初步定位;利用未知节点之间的协作通信和测距信息,位置估计问题被转换为无约束非线性优化问题,给予短距离链路更高权重,通过迭代求解最终实现协作定位。仿真结果表明,所提算法在锚节点资源受限情况下有效地提升了定位精度。展开更多
在智慧楼宇以及电力检修运维中,需要及时获取设备或人员位置信息。针对室内因非视距传输和多径效应引起的定位精度不高问题,提出了一种基于奇偶交错布局的室分与5G结合的室内三维定位方案。首先,采用到达时间差(time difference of arri...在智慧楼宇以及电力检修运维中,需要及时获取设备或人员位置信息。针对室内因非视距传输和多径效应引起的定位精度不高问题,提出了一种基于奇偶交错布局的室分与5G结合的室内三维定位方案。首先,采用到达时间差(time difference of arrival,TDOA)和到达角度(angle of arrival,AOA)融合定位。其次,把具体定位算法融入到定位架构里,基于边缘计算快速获取室内对应移动目标的位置信息。在进行TDOA定位过程中,MEC端的定位服务器结合压缩感知进行信道估计,并在分段正交匹配追踪(stagewise orthogonal matching pursuit,StOMP)算法的基础上加入奇异值进行降噪处理。在进行AOA定位过程中,先利用改进的波束空间变换技术构造矩阵进行降维,为保证降维过程中信息不损失,提出对附加角度误差进行分析处理,然后,采用多重信号分类(multiple signal classification,MUSIC)算法进行定位。最后,5GC核心网服务器利用Chan-Taylor算法进行TDOA/AOA融合定位。仿真结果证明了所提出的定位方法能够实现对移动目标的精准定位。展开更多
方面级情感分类是一种细粒度的情感分析任务,旨在分析出文本不同方面的情感.针对方面级情感分类模型存在分类精度低、泛化性弱等问题,提出基于对抗学习的AOA-BERT方面级情感分类模型(Attention-Over-Attention-BERT for aspect-level se...方面级情感分类是一种细粒度的情感分析任务,旨在分析出文本不同方面的情感.针对方面级情感分类模型存在分类精度低、泛化性弱等问题,提出基于对抗学习的AOA-BERT方面级情感分类模型(Attention-Over-Attention-BERT for aspect-level sentiment classification model based on adversarial learning,AOA-BERT).首先,将文本和方面词单独建模,通过BERT编码提取隐含层特征.其次,将隐含层特征放入AOA(Attention-Over-Attention)网络提取权重向量.最后,将权重向量与建模后的文本特征向量相乘,并做交叉熵损失、回传参数.此外,通过对抗学习算法生成和学习对抗样本,作为一种文本数据增强方法,优化决策边界.实验结果表明,和大多数深度神经网络情感分类模型相比,AOA-BERT能提升情感分类的准确性.同时,通过消融实验,证明了AOA-BERT结构设计的合理性.展开更多
This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is si...This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile. The estimation of the refractivity is organized as an optimization problem and a genetic Mgorithm is used to search for the optimal solution from various trial refractivity profiles. Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters. Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.展开更多
Based on the modified spectrum, the analytic expressions for the variance and normalized covariance of angleof-arrival （AOA） fluctuations are presented, which are applicable to the weak and strong regimes. The exper...Based on the modified spectrum, the analytic expressions for the variance and normalized covariance of angleof-arrival （AOA） fluctuations are presented, which are applicable to the weak and strong regimes. The experimental data of AOA fluctuations validate the new derived expressions in weak and strong regimes. The results show that the receiving aperture D, outer scale and cell scale larger than the scattering disc S contribute significantly to the AOA fluctuations, and contributions from the small-scale turbulence are negligible. For the case of 4S/D 〈〈 1, the receiving aperture dominates low-pass filtering effects and the new displacement variances are in good agreement with the results from the old weak-fluctuation theory. For the case of 4S/D 〉〉 1, the scattering disc dominates the low-pass filtering effects and the new displacement variances depart from the results from the old weak-fluctuation theory.展开更多
设计了基于到达角度法(Angle of Arrival,AOA)的蓝牙定位系统,并搭建了基于CC2652R1蓝牙开发板和STM32单片机的低功耗蓝牙定位系统。现场测试实验结果表明,本系统能够在室内复杂环境下获取亚米级精度的定位信息,精度可达20 cm,适用于电...设计了基于到达角度法(Angle of Arrival,AOA)的蓝牙定位系统,并搭建了基于CC2652R1蓝牙开发板和STM32单片机的低功耗蓝牙定位系统。现场测试实验结果表明,本系统能够在室内复杂环境下获取亚米级精度的定位信息,精度可达20 cm,适用于电力智慧运维、智慧工厂、商城导引、仓储物流等场景。展开更多
Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the ...Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the Sample Covariance Matrix (SCM), thus the fast algorithm has lower computational complexity with insignificant performance degradation when comparing with conventional subspace approaches. Furthermore, the proposed algorithm has no performance degradation. Finally, computer simulations verify the effectiveness of the proposed algorithm.展开更多
As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to loc...As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates.展开更多
文摘为了解决传统室内定位技术成本较高、稳定性差以及难于部署等问题,提出一种将到达时间(time of arrival,TOA)与到达角(angle of arrival,AOA)相结合的室内定位系统.该系统由定位基站与被控定位单元组成,其特征在于使用对射式布置的超声波传感器获取定位基站与被控定位单元之间的距离特征,利用角度传感器获取被控定位单元相对于定位基站的角度特征,以单基站就实现了精确的室内定位过程.分析了该系统基本结构与原理,建立定位与控制模型,在一定范围内对其定点定位精度与跟随定位精度进行了实验验证.实验结果表明:该系统结构简单,易于安装布置,鲁棒性强,在测试范围内的最大定点定位误差不超过5 cm,跟随定位误差不超过15 cm.
文摘提出一种在低空场景下基于接收信号强度(Rcecived Signal Strength,RSS)与到达角度(Angle of Arrival,AOA)信息融合的单站无源定位算法。该算法采用单架无人机设备虚拟多站设备接收无线电辐射源信号,融合RSS估计的距离信息与AOA方向角信息,依据最小二乘准则(LS)构造算法的优化目标函数,采用凸松弛技术将目标函数等价为二阶锥规划(SOCP)问题并通过内点法求解。实验结果表明,该算法的定位精度在2 km范围内可达20 m,其定位性能优于单站无源定位算法,且由于采用单架无人机采集信号,其设备复杂度相较于多站无源定位较低。
文摘工厂环境下的高精度室内定位对于智能制造、仓储管理和人员安全监控至关重要。以某工厂智能化升级改造为例,阐述基于蓝牙的信号到达角(Angle of Arrival,AOA)定位技术的基本原理,针对工厂前区设备密集、后区相对空旷的特点,采用基于蓝牙的AOA定位技术规划基站部署,优化基站的部署间距和高度。通过立柱交点定位测试法和基站下方定位测试法,验证该系统在不同测试方案下均展现出出色的定位精度,平均误差值分别为0.6 m和0.4 m,满足了设计精度要求。
文摘传统到达角度(Angle-Of-Arrival,AOA)/接受信号强度指示(Received Signal Strength Indicator,RSSI)混合定位往往需要多个锚节点布设阵列天线以实现高精度定位,为解决在锚节点资源受限下精度较低的问题,提出了一种基于Mesh网络的混合AOA/RSSI协作定位方法。仅有中心主锚节点提供AOA角度的情况下,采取最小二乘法对联合真实和虚拟锚节点所对应角度和距离信息进行初步定位;利用未知节点之间的协作通信和测距信息,位置估计问题被转换为无约束非线性优化问题,给予短距离链路更高权重,通过迭代求解最终实现协作定位。仿真结果表明,所提算法在锚节点资源受限情况下有效地提升了定位精度。
文摘在智慧楼宇以及电力检修运维中,需要及时获取设备或人员位置信息。针对室内因非视距传输和多径效应引起的定位精度不高问题,提出了一种基于奇偶交错布局的室分与5G结合的室内三维定位方案。首先,采用到达时间差(time difference of arrival,TDOA)和到达角度(angle of arrival,AOA)融合定位。其次,把具体定位算法融入到定位架构里,基于边缘计算快速获取室内对应移动目标的位置信息。在进行TDOA定位过程中,MEC端的定位服务器结合压缩感知进行信道估计,并在分段正交匹配追踪(stagewise orthogonal matching pursuit,StOMP)算法的基础上加入奇异值进行降噪处理。在进行AOA定位过程中,先利用改进的波束空间变换技术构造矩阵进行降维,为保证降维过程中信息不损失,提出对附加角度误差进行分析处理,然后,采用多重信号分类(multiple signal classification,MUSIC)算法进行定位。最后,5GC核心网服务器利用Chan-Taylor算法进行TDOA/AOA融合定位。仿真结果证明了所提出的定位方法能够实现对移动目标的精准定位。
文摘方面级情感分类是一种细粒度的情感分析任务,旨在分析出文本不同方面的情感.针对方面级情感分类模型存在分类精度低、泛化性弱等问题,提出基于对抗学习的AOA-BERT方面级情感分类模型(Attention-Over-Attention-BERT for aspect-level sentiment classification model based on adversarial learning,AOA-BERT).首先,将文本和方面词单独建模,通过BERT编码提取隐含层特征.其次,将隐含层特征放入AOA(Attention-Over-Attention)网络提取权重向量.最后,将权重向量与建模后的文本特征向量相乘,并做交叉熵损失、回传参数.此外,通过对抗学习算法生成和学习对抗样本,作为一种文本数据增强方法,优化决策边界.实验结果表明,和大多数深度神经网络情感分类模型相比,AOA-BERT能提升情感分类的准确性.同时,通过消融实验,证明了AOA-BERT结构设计的合理性.
基金supported by the National Natural Science Foundation of China (Grant No. 40775023)
文摘This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile. The estimation of the refractivity is organized as an optimization problem and a genetic Mgorithm is used to search for the optimal solution from various trial refractivity profiles. Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters. Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.
文摘Based on the modified spectrum, the analytic expressions for the variance and normalized covariance of angleof-arrival （AOA） fluctuations are presented, which are applicable to the weak and strong regimes. The experimental data of AOA fluctuations validate the new derived expressions in weak and strong regimes. The results show that the receiving aperture D, outer scale and cell scale larger than the scattering disc S contribute significantly to the AOA fluctuations, and contributions from the small-scale turbulence are negligible. For the case of 4S/D 〈〈 1, the receiving aperture dominates low-pass filtering effects and the new displacement variances are in good agreement with the results from the old weak-fluctuation theory. For the case of 4S/D 〉〉 1, the scattering disc dominates the low-pass filtering effects and the new displacement variances depart from the results from the old weak-fluctuation theory.
文摘设计了基于到达角度法(Angle of Arrival,AOA)的蓝牙定位系统,并搭建了基于CC2652R1蓝牙开发板和STM32单片机的低功耗蓝牙定位系统。现场测试实验结果表明,本系统能够在室内复杂环境下获取亚米级精度的定位信息,精度可达20 cm,适用于电力智慧运维、智慧工厂、商城导引、仓储物流等场景。
基金Supported by the Foundation of National Key Laboratory.
文摘Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the Sample Covariance Matrix (SCM), thus the fast algorithm has lower computational complexity with insignificant performance degradation when comparing with conventional subspace approaches. Furthermore, the proposed algorithm has no performance degradation. Finally, computer simulations verify the effectiveness of the proposed algorithm.
文摘As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates.
