针对物联网的节点定位问题,本文提出一种低复杂度的参数估计及单站定位算法,包括一种基于矩阵幂的矩阵束(Power-based Matrix Pencil,PMP)算法与非线性拟合(Non-Linear Fitting,NLF)技术。算法利用联合到达时间(Time of Arrival,TOA)/...针对物联网的节点定位问题,本文提出一种低复杂度的参数估计及单站定位算法,包括一种基于矩阵幂的矩阵束(Power-based Matrix Pencil,PMP)算法与非线性拟合(Non-Linear Fitting,NLF)技术。算法利用联合到达时间(Time of Arrival,TOA)/到达角度(Angle of Arrival,AOA)参数估计进行定位运算,通过单个锚节点的测距信息即可完成定位。该算法首先通过矩阵幂运算近似求解接收矩阵的信号子空间,并基于此近似提出PMP算法估计多径AOA,然后利用OFDM子载波的频率分集特性,通过NLF进行TOA的高分辨率估计,有效降低了计算复杂度。仿真结果表明,该算法的时间开销远低于传统的二维矩阵束算法,并且在高带宽和多阵元情况下具有较好的定位性能。展开更多
为提高图像配准精度和稳定性,降低复杂度,提出一种基于最大后验概率耦合互信息的精确图像配准算法。引入图像最大后验概率(posterior A maximum,MAP),利用MAP抑制待匹配区域特征中的背景干扰因素,根据图像退化过程的差异,引入权重因子,...为提高图像配准精度和稳定性,降低复杂度,提出一种基于最大后验概率耦合互信息的精确图像配准算法。引入图像最大后验概率(posterior A maximum,MAP),利用MAP抑制待匹配区域特征中的背景干扰因素,根据图像退化过程的差异,引入权重因子,通过特征之间对应关系的最小二乘估计,准确提取图像特征;定义最大互信息(mutual information,MI)准则,建立图像特征之间的对应关系,利用高分辨率图像估计对配准参数进行微调。实验结果表明,与当前常用配准算法相比,所提算法能够较准确地从背景中提取目标特征,完成配准,其具有更高的配准精度与更低的复杂度。展开更多
This study investigates the wind energy input, an important source of mechanical energy, in the coastal seas east of China. Using the wind field from the high-resolution sea surface meteorology dataset in the Bohai Se...This study investigates the wind energy input, an important source of mechanical energy, in the coastal seas east of China. Using the wind field from the high-resolution sea surface meteorology dataset in the Bohai Sea, Yellow Sea, and East China Sea, we studied the wind energy input through surface ageostrophic currents and surface waves. Using a simple analytical formula for the Ekman Spiral with time- dependent wind, the wind energy input through ageostrophic currents was estimated at -22 GW averaged from 1960 to 2007, and through use of an empirical formula, the wind energy input through surface waves was estimated at -169 GW. We also examined the seasonal variation and long-term tendency of mechanical energy from wind stress, and found that the wind energy input to the East China Sea decreased before the 1980s, and then subsequently increased, which is contrary to what has been found for the Bohai Sea and Yellow Sea. More complicated physical processes and varying diffusivity need to be taken into account in future studies.展开更多
Based on spatial interpolation rainfall of the ground gauge measurement,we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales:0.25...Based on spatial interpolation rainfall of the ground gauge measurement,we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales:0.25°×0.25° grid scale,sub-catchment scale and the whole basin scale.Using this method,we evaluated the accuracy of six high-resolution monthly SREs (TRMM 3B42 V6,3B42RT V6,CMORPH,GSMaP MWR+,GSMaP MVK+ and PERSIANN) and revealed the spatio-temporal variation of the SRE accuracy based on spatial interpolated rainfall from a dense network of 325 gauges during 2003-2009 over the Ganjiang River Basin in the Southeast China.The results showed that ground gauge-calibrated 3B42 had the highest accuracy with slight overestimation,whereas the other five uncalibrated SREs had severe underestimation.The accuracy of the six SREs in wet seasons was remarkably higher than that in the dry seasons.When the time scale was expanded,the accuracy of SRE,particularly 3B42,increased.Furthermore,the accuracy of SREs was relatively low in the western mountains and northern piedmont areas,while it was relatively high in the central and southeastern hills and basins of the Ganjiang River Basin.When the space scale was expanded,the accuracy of the six SREs gradually increased.This study provided an example for of SRE accuracy validation in other regions,and a direct basis for further study of SRE-based hydrological process.展开更多
文摘针对物联网的节点定位问题,本文提出一种低复杂度的参数估计及单站定位算法,包括一种基于矩阵幂的矩阵束(Power-based Matrix Pencil,PMP)算法与非线性拟合(Non-Linear Fitting,NLF)技术。算法利用联合到达时间(Time of Arrival,TOA)/到达角度(Angle of Arrival,AOA)参数估计进行定位运算,通过单个锚节点的测距信息即可完成定位。该算法首先通过矩阵幂运算近似求解接收矩阵的信号子空间,并基于此近似提出PMP算法估计多径AOA,然后利用OFDM子载波的频率分集特性,通过NLF进行TOA的高分辨率估计,有效降低了计算复杂度。仿真结果表明,该算法的时间开销远低于传统的二维矩阵束算法,并且在高带宽和多阵元情况下具有较好的定位性能。
文摘为提高图像配准精度和稳定性,降低复杂度,提出一种基于最大后验概率耦合互信息的精确图像配准算法。引入图像最大后验概率(posterior A maximum,MAP),利用MAP抑制待匹配区域特征中的背景干扰因素,根据图像退化过程的差异,引入权重因子,通过特征之间对应关系的最小二乘估计,准确提取图像特征;定义最大互信息(mutual information,MI)准则,建立图像特征之间的对应关系,利用高分辨率图像估计对配准参数进行微调。实验结果表明,与当前常用配准算法相比,所提算法能够较准确地从背景中提取目标特征,完成配准,其具有更高的配准精度与更低的复杂度。
基金Supported by the National 111 Project of China(No.B07036)the National Natural Science Foundation of China(Nos.40930844,40976004)the Research Fund for the Doctoral Program of Higher Education of China(No.20110132130001)
文摘This study investigates the wind energy input, an important source of mechanical energy, in the coastal seas east of China. Using the wind field from the high-resolution sea surface meteorology dataset in the Bohai Sea, Yellow Sea, and East China Sea, we studied the wind energy input through surface ageostrophic currents and surface waves. Using a simple analytical formula for the Ekman Spiral with time- dependent wind, the wind energy input through ageostrophic currents was estimated at -22 GW averaged from 1960 to 2007, and through use of an empirical formula, the wind energy input through surface waves was estimated at -169 GW. We also examined the seasonal variation and long-term tendency of mechanical energy from wind stress, and found that the wind energy input to the East China Sea decreased before the 1980s, and then subsequently increased, which is contrary to what has been found for the Bohai Sea and Yellow Sea. More complicated physical processes and varying diffusivity need to be taken into account in future studies.
基金supported by the National Natural Science Foundation of China (Grant No. 51109136)the Commonweal Science Research Project of Ministry of Water Resources of China (Grant Nos. 201001002,201101004)the Science and Technology Development Fund,Ministry of Water Resources of China (Grant No. TG1109)
文摘Based on spatial interpolation rainfall of the ground gauge measurement,we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales:0.25°×0.25° grid scale,sub-catchment scale and the whole basin scale.Using this method,we evaluated the accuracy of six high-resolution monthly SREs (TRMM 3B42 V6,3B42RT V6,CMORPH,GSMaP MWR+,GSMaP MVK+ and PERSIANN) and revealed the spatio-temporal variation of the SRE accuracy based on spatial interpolated rainfall from a dense network of 325 gauges during 2003-2009 over the Ganjiang River Basin in the Southeast China.The results showed that ground gauge-calibrated 3B42 had the highest accuracy with slight overestimation,whereas the other five uncalibrated SREs had severe underestimation.The accuracy of the six SREs in wet seasons was remarkably higher than that in the dry seasons.When the time scale was expanded,the accuracy of SRE,particularly 3B42,increased.Furthermore,the accuracy of SREs was relatively low in the western mountains and northern piedmont areas,while it was relatively high in the central and southeastern hills and basins of the Ganjiang River Basin.When the space scale was expanded,the accuracy of the six SREs gradually increased.This study provided an example for of SRE accuracy validation in other regions,and a direct basis for further study of SRE-based hydrological process.
