多径干扰是超宽带(ultra-wideband,UWB)定位误差的主要来源之一,超宽带信号的非视距传播会导致通信和定位精度的可靠性降低。因此,准确识别定位过程中的非视距(non line of sight,NLOS)传播信号是提高定位精度的重要措施。针对超宽带信...多径干扰是超宽带(ultra-wideband,UWB)定位误差的主要来源之一,超宽带信号的非视距传播会导致通信和定位精度的可靠性降低。因此,准确识别定位过程中的非视距(non line of sight,NLOS)传播信号是提高定位精度的重要措施。针对超宽带信号的非视距传播识别问题,该文提出一种新的基于信道冲激响应(channel impulse response,CIR)特征参量—上升时间与峰值时间和(sum of rise time and peak time,Sum_T)与未检测到峰值(undetected peak,UD-P)联合的NLOS识别方法。实验结果表明,典型室内办公环境下NLOS信号的识别率可以达到95.75%,该方法在定位系统中的使用将有助于提升定位精度。展开更多
针对在医院室内非视距环境中,多径现象明显、测距误差较大的问题,本文基于超宽带技术(Ultra-wideband,UWB)功耗低、多径分辨率高、测距精度高等优点,研究了位置指纹法的定位原理与NN指纹定位法及其改进算法。实验采用基于飞行时间(Time ...针对在医院室内非视距环境中,多径现象明显、测距误差较大的问题,本文基于超宽带技术(Ultra-wideband,UWB)功耗低、多径分辨率高、测距精度高等优点,研究了位置指纹法的定位原理与NN指纹定位法及其改进算法。实验采用基于飞行时间(Time of Fight,TOF)测距数据作为指纹建立数据库,分别研究了NN算法和WKNN的定位性能,并进行误差分析。结果表明两种算法均能达到厘米级的定位精度,且WKNN算法相对NN算法的定位误差改善了18.09%,提高了在非视距环境中定位的精确度和稳健性。展开更多
The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioni...The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioning in hazardous multipath environments through three versatile super resolution techniques: time domain Multiple Signal Classification (TD-MUSIC), frequency domain MUSIC (FD-MUSIC) algorithms, and frequency domain Eigen value (FD-EV) method. The advantage of using these super resolution techniques is twofold. First for Line-of-Sight (LoS) conditions this provides the most accurate means of determining the time delay estimate from transmitter to receiver for any wireless sensor network. The high noise immunity and resolvability of these methods makes them ideal for cost-effective wireless sensor networks operating in indoor channels. Second for non-LoS conditions the resultant pseudo-spectrum generated by these methods provides the means to construct the ideal location based fingerprint. We provide an in depth analysis of limitation as well as advantages inherent in all of these methods through a detailed behavioral analysis under constrained environments. Hence, the bandwidth versatility, higher resolution capability and higher noise immunity of the TD-MUSIC algorithm and the FD-EV method’s ability to resurface submerged signal peaks when the signal subspace dimensions are underestimated are all presented in detail.展开更多
根据超宽带无线电技术的电磁波定位原理,提出了一种超宽带空间谱定位算法,结合多重信号分类(Multiple Signal Classification,MUSIC)算法并利用超宽带信号源的频带分割获取多频下的时反算子.仿真结果有效地验证了本文所采用的方法具有...根据超宽带无线电技术的电磁波定位原理,提出了一种超宽带空间谱定位算法,结合多重信号分类(Multiple Signal Classification,MUSIC)算法并利用超宽带信号源的频带分割获取多频下的时反算子.仿真结果有效地验证了本文所采用的方法具有良好的定位成像能力.展开更多
针对室内环境影响定位精度的非视距传播(non-line-of-sight,NLOS)问题,在对基于到达时间差(time differ-ence of arrival,TDOA)的超宽带(ultra wideband,UWB)室内定位模型和算法进行分析研究的基础上,提出了质心-Taylor混合定位算法。...针对室内环境影响定位精度的非视距传播(non-line-of-sight,NLOS)问题,在对基于到达时间差(time differ-ence of arrival,TDOA)的超宽带(ultra wideband,UWB)室内定位模型和算法进行分析研究的基础上,提出了质心-Taylor混合定位算法。该算法利用对测距误差不敏感的质心算法对目标进行初始粗定位,然后将其作为Taylor级数展开法的迭代初值进行二次精细定位,并动态地将前期定位完毕的节点转化为后续定位过程的参考节点,最大限度地利用不断增加的已知信息,在提高Taylor初值质量的前提下减少预设参考节点数目,降低系统硬件成本。采用MATLAB软件进行了模拟仿真。仿真结果表明,该算法定位性能优越,尤其在NLOS测距误差较大的环境下能有效地提高系统的定位精度。展开更多
文摘多径干扰是超宽带(ultra-wideband,UWB)定位误差的主要来源之一,超宽带信号的非视距传播会导致通信和定位精度的可靠性降低。因此,准确识别定位过程中的非视距(non line of sight,NLOS)传播信号是提高定位精度的重要措施。针对超宽带信号的非视距传播识别问题,该文提出一种新的基于信道冲激响应(channel impulse response,CIR)特征参量—上升时间与峰值时间和(sum of rise time and peak time,Sum_T)与未检测到峰值(undetected peak,UD-P)联合的NLOS识别方法。实验结果表明,典型室内办公环境下NLOS信号的识别率可以达到95.75%,该方法在定位系统中的使用将有助于提升定位精度。
文摘针对在医院室内非视距环境中,多径现象明显、测距误差较大的问题,本文基于超宽带技术(Ultra-wideband,UWB)功耗低、多径分辨率高、测距精度高等优点,研究了位置指纹法的定位原理与NN指纹定位法及其改进算法。实验采用基于飞行时间(Time of Fight,TOF)测距数据作为指纹建立数据库,分别研究了NN算法和WKNN的定位性能,并进行误差分析。结果表明两种算法均能达到厘米级的定位精度,且WKNN算法相对NN算法的定位误差改善了18.09%,提高了在非视距环境中定位的精确度和稳健性。
文摘The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioning in hazardous multipath environments through three versatile super resolution techniques: time domain Multiple Signal Classification (TD-MUSIC), frequency domain MUSIC (FD-MUSIC) algorithms, and frequency domain Eigen value (FD-EV) method. The advantage of using these super resolution techniques is twofold. First for Line-of-Sight (LoS) conditions this provides the most accurate means of determining the time delay estimate from transmitter to receiver for any wireless sensor network. The high noise immunity and resolvability of these methods makes them ideal for cost-effective wireless sensor networks operating in indoor channels. Second for non-LoS conditions the resultant pseudo-spectrum generated by these methods provides the means to construct the ideal location based fingerprint. We provide an in depth analysis of limitation as well as advantages inherent in all of these methods through a detailed behavioral analysis under constrained environments. Hence, the bandwidth versatility, higher resolution capability and higher noise immunity of the TD-MUSIC algorithm and the FD-EV method’s ability to resurface submerged signal peaks when the signal subspace dimensions are underestimated are all presented in detail.
文摘针对室内环境影响定位精度的非视距传播(non-line-of-sight,NLOS)问题,在对基于到达时间差(time differ-ence of arrival,TDOA)的超宽带(ultra wideband,UWB)室内定位模型和算法进行分析研究的基础上,提出了质心-Taylor混合定位算法。该算法利用对测距误差不敏感的质心算法对目标进行初始粗定位,然后将其作为Taylor级数展开法的迭代初值进行二次精细定位,并动态地将前期定位完毕的节点转化为后续定位过程的参考节点,最大限度地利用不断增加的已知信息,在提高Taylor初值质量的前提下减少预设参考节点数目,降低系统硬件成本。采用MATLAB软件进行了模拟仿真。仿真结果表明,该算法定位性能优越,尤其在NLOS测距误差较大的环境下能有效地提高系统的定位精度。
