In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reco...In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reconstruction problem can be reduced to a calculation of Green function corresponding to the background medium. In addition, we use an explicit formulation of Green function in the MUSIC algorithm to simplify the calculation when the cross-section of sample is a half-disc. Numerical experiments are included to demonstrate the feasibility of this method.展开更多
On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC alg...On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC algorithm is improved.The algorithm combines the idea of spatial smoothing,constructs a new covariance matrix using the covariance information of the measurement data,and constructs a weighted value using the modified noise eigenvalues to weight the traditional estimation spectrum.Simulation results show that the improved algorithm has steeper spectral peaks and better time delay resolution under the condition of inaccurate path number estimation.The time delay estimation accuracy of this algorithm is higher than that of the traditional MUSIC algorithm and the improved SSMUSIC algorithm under the conditions of small sampling data and low SNR.展开更多
In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can b...In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.展开更多
准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式...准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。展开更多
实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(g...实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。展开更多
针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用...针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用大、运行时间长的问题,提出了一种基于极化MUSIC算法的四维参数联合估计FPGA实现架构。该架构包括信号协方差矩阵计算模块、Jacobi旋转模块、噪声子空间提取模块、两级空间谱搜索模块和极化参数计算模块。Jacobi旋转模块被拆分为多个可复用模块,并采用查找表模块生成旋转矩阵。一级空间谱搜索模块通过二维DOA搜索初步确定信源的角度信息。二级空间谱搜索模块根据一级搜索的角度结果确定二级搜索区域各点的极化信息,并计算该区域的四维空间谱,区域内最小值对应的四维参数信息即为最终估计的信源方向角、俯仰角、极化辅助角和极化相位角。仿真结果表明,与传统极化MUSIC算法的四维搜索算法相比,该架构避免了大量四维空间谱计算,同时保证了四维参数估计的精度,显著减少了运行时间和硬件资源消耗。展开更多
In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers f...In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers for large-scale training to produce recommendation results, which may result in the inability to achieve music recommendation in some areas due to substandard hardware conditions. This study evaluates the adaptability of four popular machine learning algorithms (K-means clustering, fuzzy C-means (FCM) clustering, hierarchical clustering, and self-organizing map (SOM)) on low-computing servers. Our comparative analysis highlights that while K-means and FCM are robust in high-performance settings, they underperform in low-power scenarios where SOM excels, delivering fast and reliable recommendations with minimal computational overhead. This research addresses a gap in the literature by providing a detailed comparative analysis of MRS algorithms, offering practical insights for implementing adaptive MRS in technologically diverse environments. We conclude with strategic recommendations for emerging streaming services in resource-constrained settings, emphasizing the need for scalable solutions that balance cost and performance. This study advocates an adaptive selection of recommendation algorithms to manage operational costs effectively and accommodate growth.展开更多
针对永磁电机电磁噪声定位问题,提出一种基于声源波达方位估计的电磁噪声诊断方法。该方法在电机由变频器供电的运行工况下进行多信道噪声采样,通过先验频率数据识别各噪声信道中的电机电磁噪声源特征,结合DBSCAN聚类算法和能量门限,有...针对永磁电机电磁噪声定位问题,提出一种基于声源波达方位估计的电磁噪声诊断方法。该方法在电机由变频器供电的运行工况下进行多信道噪声采样,通过先验频率数据识别各噪声信道中的电机电磁噪声源特征,结合DBSCAN聚类算法和能量门限,有效提取窄带信号。采用改进的噪声子空间重构算法——MCT-IRNSMUSIC对窄带信号进行波达方位(direction of arrival,DOA)估计,并通过自适应加权得到最终DOA估计结果。该算法拓展了阵列孔径,实现了针对多相干信号源的有效方位角估计,提高了混响环境下的准确性。仿真对比和实验结果表明,相较于传统算法,该方法具有更高的准确性和鲁棒性,其噪声源定位准确率可达96.2%,在工程应用中具有参考价值。展开更多
为设计更有效的声源定位方法,深入研究了传统MUSIC算法,并针对其分辨率低且在麦克风数目较少时波达方向(direction of arrival,DOA)估计精度较差等问题,对传统MUSIC算法进行了优化,利用广义互相关算法估计出声源信号到达各麦克风之间的...为设计更有效的声源定位方法,深入研究了传统MUSIC算法,并针对其分辨率低且在麦克风数目较少时波达方向(direction of arrival,DOA)估计精度较差等问题,对传统MUSIC算法进行了优化,利用广义互相关算法估计出声源信号到达各麦克风之间的时间差,并据此构建出对应的矢量信号,最后通过计算谱函数确定DOA估计值。仿真和实验结果表明,优化后的MUSIC算法可以得到更加尖锐的指向性波束,更低的旁瓣,并且能使方位角的定位精度达到±4°,俯仰角的定位精度达到±5°。展开更多
针对传统波达方向(Direction of Arrival,DOA)估计方法通过空间平滑对相干信号进行处理损失阵列孔径的问题,文章提出了一种基于协方差矩阵托普利兹(Toeplitz)矩阵重构的多重信号分类(Multiple Signal Classification,MUSIC)算法的波达...针对传统波达方向(Direction of Arrival,DOA)估计方法通过空间平滑对相干信号进行处理损失阵列孔径的问题,文章提出了一种基于协方差矩阵托普利兹(Toeplitz)矩阵重构的多重信号分类(Multiple Signal Classification,MUSIC)算法的波达方位估计方法。该方法首先根据阵列接收数据的协方差矩阵及其翻转矩阵来构造新协方差矩阵,并利用新协方差矩阵构造Toeplitz矩阵,然后对其进行特征值分解,得到Toeplitz矩阵的噪声子空间,利用噪声子空间求出信号空间谱,通过谱峰搜索估计入射信号的方位角。文中方法拓展了阵列孔径,增加了可估计相干信号的数量,提升了方位估计的性能,提高了阵列的空间分辨率。仿真和湖上实验数据处理结果表明,文中方法可估计出更多的相干信号,而且在低信噪比、少快拍以及信号入射角度间隔较小时仍然具有良好的方位估计性能。展开更多
基金supported by the National Natural Science Foundation of China (10971083, 10801063)the School of Mathematical Sciences Foundation of Jilin University
摘要In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reconstruction problem can be reduced to a calculation of Green function corresponding to the background medium. In addition, we use an explicit formulation of Green function in the MUSIC algorithm to simplify the calculation when the cross-section of sample is a half-disc. Numerical experiments are included to demonstrate the feasibility of this method.
摘要On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC algorithm is improved.The algorithm combines the idea of spatial smoothing,constructs a new covariance matrix using the covariance information of the measurement data,and constructs a weighted value using the modified noise eigenvalues to weight the traditional estimation spectrum.Simulation results show that the improved algorithm has steeper spectral peaks and better time delay resolution under the condition of inaccurate path number estimation.The time delay estimation accuracy of this algorithm is higher than that of the traditional MUSIC algorithm and the improved SSMUSIC algorithm under the conditions of small sampling data and low SNR.
摘要In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.
摘要准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。
摘要实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。
摘要针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用大、运行时间长的问题,提出了一种基于极化MUSIC算法的四维参数联合估计FPGA实现架构。该架构包括信号协方差矩阵计算模块、Jacobi旋转模块、噪声子空间提取模块、两级空间谱搜索模块和极化参数计算模块。Jacobi旋转模块被拆分为多个可复用模块,并采用查找表模块生成旋转矩阵。一级空间谱搜索模块通过二维DOA搜索初步确定信源的角度信息。二级空间谱搜索模块根据一级搜索的角度结果确定二级搜索区域各点的极化信息,并计算该区域的四维空间谱,区域内最小值对应的四维参数信息即为最终估计的信源方向角、俯仰角、极化辅助角和极化相位角。仿真结果表明,与传统极化MUSIC算法的四维搜索算法相比,该架构避免了大量四维空间谱计算,同时保证了四维参数估计的精度,显著减少了运行时间和硬件资源消耗。
摘要In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers for large-scale training to produce recommendation results, which may result in the inability to achieve music recommendation in some areas due to substandard hardware conditions. This study evaluates the adaptability of four popular machine learning algorithms (K-means clustering, fuzzy C-means (FCM) clustering, hierarchical clustering, and self-organizing map (SOM)) on low-computing servers. Our comparative analysis highlights that while K-means and FCM are robust in high-performance settings, they underperform in low-power scenarios where SOM excels, delivering fast and reliable recommendations with minimal computational overhead. This research addresses a gap in the literature by providing a detailed comparative analysis of MRS algorithms, offering practical insights for implementing adaptive MRS in technologically diverse environments. We conclude with strategic recommendations for emerging streaming services in resource-constrained settings, emphasizing the need for scalable solutions that balance cost and performance. This study advocates an adaptive selection of recommendation algorithms to manage operational costs effectively and accommodate growth.
摘要针对永磁电机电磁噪声定位问题,提出一种基于声源波达方位估计的电磁噪声诊断方法。该方法在电机由变频器供电的运行工况下进行多信道噪声采样,通过先验频率数据识别各噪声信道中的电机电磁噪声源特征,结合DBSCAN聚类算法和能量门限,有效提取窄带信号。采用改进的噪声子空间重构算法——MCT-IRNSMUSIC对窄带信号进行波达方位(direction of arrival,DOA)估计,并通过自适应加权得到最终DOA估计结果。该算法拓展了阵列孔径,实现了针对多相干信号源的有效方位角估计,提高了混响环境下的准确性。仿真对比和实验结果表明,相较于传统算法,该方法具有更高的准确性和鲁棒性,其噪声源定位准确率可达96.2%,在工程应用中具有参考价值。
摘要为设计更有效的声源定位方法,深入研究了传统MUSIC算法,并针对其分辨率低且在麦克风数目较少时波达方向(direction of arrival,DOA)估计精度较差等问题,对传统MUSIC算法进行了优化,利用广义互相关算法估计出声源信号到达各麦克风之间的时间差,并据此构建出对应的矢量信号,最后通过计算谱函数确定DOA估计值。仿真和实验结果表明,优化后的MUSIC算法可以得到更加尖锐的指向性波束,更低的旁瓣,并且能使方位角的定位精度达到±4°,俯仰角的定位精度达到±5°。
摘要针对传统波达方向(Direction of Arrival,DOA)估计方法通过空间平滑对相干信号进行处理损失阵列孔径的问题,文章提出了一种基于协方差矩阵托普利兹(Toeplitz)矩阵重构的多重信号分类(Multiple Signal Classification,MUSIC)算法的波达方位估计方法。该方法首先根据阵列接收数据的协方差矩阵及其翻转矩阵来构造新协方差矩阵,并利用新协方差矩阵构造Toeplitz矩阵,然后对其进行特征值分解,得到Toeplitz矩阵的噪声子空间,利用噪声子空间求出信号空间谱,通过谱峰搜索估计入射信号的方位角。文中方法拓展了阵列孔径,增加了可估计相干信号的数量,提升了方位估计的性能,提高了阵列的空间分辨率。仿真和湖上实验数据处理结果表明,文中方法可估计出更多的相干信号,而且在低信噪比、少快拍以及信号入射角度间隔较小时仍然具有良好的方位估计性能。