时间差估计是局部放电定位的重要一环,现有算法受限于采样设备采样率,会产生无法忽略的系统误差,进而使定位误差过大。为了解决上述问题,该文提出了超分辨率最小均方广义互相关(super resolution least mean square generalized cross c...时间差估计是局部放电定位的重要一环,现有算法受限于采样设备采样率,会产生无法忽略的系统误差,进而使定位误差过大。为了解决上述问题,该文提出了超分辨率最小均方广义互相关(super resolution least mean square generalized cross correlation,SR-LMS-GCC)时间差估计算法,使时间差估计的结果突破采样率的限制,能更精确地估算两信号之间的时间差。首先对离散时间信号的广义互相关进行改进,通过频率调整扩展了频谱,能够有效提高时间差估计的时间分辨率。为解决真实时间差溢出时间差估计区间的问题,提出了多级交叉互相关器的框架,并与自适应广义互相关时间差估计方法结合起来,提出了SR-LMS-GCC算法,并通过仿真讨论了算法参数的设置规则。最后通过实验验证,SR-LMS-GCC算法在时间差估计和定位准确度方面的比传统的受分辨率限制的算法均提升了85%以上。展开更多
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
The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduce...The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.展开更多
文摘时间差估计是局部放电定位的重要一环,现有算法受限于采样设备采样率,会产生无法忽略的系统误差,进而使定位误差过大。为了解决上述问题,该文提出了超分辨率最小均方广义互相关(super resolution least mean square generalized cross correlation,SR-LMS-GCC)时间差估计算法,使时间差估计的结果突破采样率的限制,能更精确地估算两信号之间的时间差。首先对离散时间信号的广义互相关进行改进,通过频率调整扩展了频谱,能够有效提高时间差估计的时间分辨率。为解决真实时间差溢出时间差估计区间的问题,提出了多级交叉互相关器的框架,并与自适应广义互相关时间差估计方法结合起来,提出了SR-LMS-GCC算法,并通过仿真讨论了算法参数的设置规则。最后通过实验验证,SR-LMS-GCC算法在时间差估计和定位准确度方面的比传统的受分辨率限制的算法均提升了85%以上。
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Project(08Y29-7)supported by the Transportation Science and Research Program of Jiangsu Province,ChinaProject(201103051)supported by the Major Infrastructure Program of the Health Monitoring System Hardware Platform Based on Sensor Network Node,China+1 种基金Project(61100111)supported by the National Natural Science Foundation of ChinaProject(BE2011169)supported by the Scientific and Technical Supporting Program of Jiangsu Province,China
文摘The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.
