为实现简单而精确的定位,提出了一种基于阵列天线的超宽带（ultra-wideband,UWB）定位方案。在定位源末端设置4根阵元天线,用于检测未知节点发射的UWB信号,各天线接收的信号经统一的中央处理单元,只需单个定位源就能完成未知节点的三维...为实现简单而精确的定位,提出了一种基于阵列天线的超宽带（ultra-wideband,UWB）定位方案。在定位源末端设置4根阵元天线,用于检测未知节点发射的UWB信号,各天线接收的信号经统一的中央处理单元,只需单个定位源就能完成未知节点的三维定位。通过UWB多径信号检测算法进行到达时间差（time differ-ence of arrival,TDOA）估计,无需收发两端时钟同步,且避免了使用复杂的波束赋形技术。同时,提出了一种UWB多径信号检测算法,在分析误差模型对定位精度影响的基础上,以IEEE 802.15.4a信道模型的CM1~CM8为依据,对方案进行了误差性能仿真实验。结果表明,所提方案可实现精确定位,误差达厘米级。展开更多
基于到达时间差(Time difference of arrival,TDOA)估计的方法是声源波达方向(Direction of arrival,DOA)估计中的一类重要方法。其中由TDOA到DOA的映射是该类方法的关键步骤。本文提出了一种基于多核聚类最小二乘支持向量回归(Least-sq...基于到达时间差(Time difference of arrival,TDOA)估计的方法是声源波达方向(Direction of arrival,DOA)估计中的一类重要方法。其中由TDOA到DOA的映射是该类方法的关键步骤。本文提出了一种基于多核聚类最小二乘支持向量回归(Least-squares support vector regression,LS-SVR)的TDOA-DOA映射方法,并且分析了其稀疏化处理后的性能。为了提高混响噪声环境下的TDOA-DOA映射性能,本文还给出了一种基于归一化中值滤波的TDOA估计离群值消除方法。仿真结果表明,本文提出的方法要优于现有的最小二乘方法以及单核LS-SVR方法。展开更多
This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadc...This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.展开更多
文摘为实现简单而精确的定位,提出了一种基于阵列天线的超宽带（ultra-wideband,UWB）定位方案。在定位源末端设置4根阵元天线,用于检测未知节点发射的UWB信号,各天线接收的信号经统一的中央处理单元,只需单个定位源就能完成未知节点的三维定位。通过UWB多径信号检测算法进行到达时间差（time differ-ence of arrival,TDOA）估计,无需收发两端时钟同步,且避免了使用复杂的波束赋形技术。同时,提出了一种UWB多径信号检测算法,在分析误差模型对定位精度影响的基础上,以IEEE 802.15.4a信道模型的CM1~CM8为依据,对方案进行了误差性能仿真实验。结果表明,所提方案可实现精确定位,误差达厘米级。
文摘基于到达时间差(Time difference of arrival,TDOA)估计的方法是声源波达方向(Direction of arrival,DOA)估计中的一类重要方法。其中由TDOA到DOA的映射是该类方法的关键步骤。本文提出了一种基于多核聚类最小二乘支持向量回归(Least-squares support vector regression,LS-SVR)的TDOA-DOA映射方法,并且分析了其稀疏化处理后的性能。为了提高混响噪声环境下的TDOA-DOA映射性能,本文还给出了一种基于归一化中值滤波的TDOA估计离群值消除方法。仿真结果表明,本文提出的方法要优于现有的最小二乘方法以及单核LS-SVR方法。
基金supported by the National Natural Science Foundation of China under Grant No.61571452 and No.61201331
文摘This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.
