将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signa...将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signal parameters via rotational invariancetechnique,ESPRIT),应用模拟转子故障的定子电流信号测试其频率分辨力、精度等性能,结果表明:即使对于短时信号,二者仍具高频率分辨力,可以准确地分辨定子电流信号中转子故障特征分量、主频分量之频率;但对其幅值、初相角,仅能提供"粗糙"估计。为此,尝试以优化算法——模拟退火算法(simulated annealing algorithm,SAA)与模式搜索算法(pattern search algorithm,PSA)确定各分量的幅值与初相角。同时,分别对MUSIC与ESPRIT、SAA与PSA做了性能对比,遴选优者并应用于转子故障检测。最后,针对转子断条故障进行实验,结果表明:基于高频率分辨力谱估计技术与优化算法的异步电动机转子故障检测方法有效、可行,即使在负载波动、噪声等干扰严重情况下仍然适用。展开更多
针对强信号背景下弱信号波达方向(direction of arriaval,DOA)估计问题,提出了一种基于噪声子空间扩展的弱信号DOA估计算法。该算法提出并使用了噪声子空间扩充的思想,其先将强信号导向矢量所在空间纳入噪声子空间进而构造出扩展噪声子...针对强信号背景下弱信号波达方向(direction of arriaval,DOA)估计问题,提出了一种基于噪声子空间扩展的弱信号DOA估计算法。该算法提出并使用了噪声子空间扩充的思想,其先将强信号导向矢量所在空间纳入噪声子空间进而构造出扩展噪声子空间,再在该扩展噪声子空间基础上利用常规多信号分类(multiple signalclassification,MUSIC)算法得到弱信号的DOA估计。通过噪声子空间的扩充有效地抑制了强信号谱峰,算法无需已知强信号方向及导向矢量,运算量与常规MUSIC相当。理论分析表明该算法对弱信号DOA估计性能不劣于对应的强信号阻塞类算法,仿真实验证实了其有效性和可行性。展开更多
提出了一种基于传感器线阵的多重信号分类(Multiple Signal Classification,MUSIC)损伤成像方法用于航空复合材料的损伤监测。该方法采用MUSIC阵列信号处理方法,通过对传感器阵列信号进行协方差特征值分解,在结构上进行方向扫描并构建...提出了一种基于传感器线阵的多重信号分类(Multiple Signal Classification,MUSIC)损伤成像方法用于航空复合材料的损伤监测。该方法采用MUSIC阵列信号处理方法,通过对传感器阵列信号进行协方差特征值分解,在结构上进行方向扫描并构建监测区域的空间谱,从而实现对结构损伤的成像,具有一维传感器阵列易于布置的优点。所提出的方法在变厚度航空复合材料油箱结构上进行了验证,结果表明,该方法能够准确实现航空复合材料结构上的损伤成像,定位误差小于2cm。展开更多
To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the ge...To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the geometry of the RLA is formulated and analysed.According to its geometry,the intercepted noncoherent signals in multiple interception intervals are modeled.Correspondingly,the Multiple SIgnal Classification(MUSIC)based noncoherent DPD approach is proposed.Secondly,the synchronous coherent pulse signals are individually considered and formulated.And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals.Besides,we also derive the constrained Cramer-Rao Lower Bound(CRLB)expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known.At last,computer simulations are included to examine the performance of the proposed approach.The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation.In addition,coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.展开更多
传统的MUSIC超分辨时延估计技术是直接基于测量数据,其性能往往只对宽带且频谱近似平坦的信号较优,而对窄带信号估计性能较差。针对上述问题,本文通过利用谐波频率估计模型和DOA(Direction of Arrival)估计模型之间的等价性,将时延估计...传统的MUSIC超分辨时延估计技术是直接基于测量数据,其性能往往只对宽带且频谱近似平坦的信号较优,而对窄带信号估计性能较差。针对上述问题,本文通过利用谐波频率估计模型和DOA(Direction of Arrival)估计模型之间的等价性,将时延估计问题转化为谐波频率估计问题,提出了一种改进SSMUSIC(Signal Subspace Scaled Multiple Signal Classification)超分辨多径时延估计算法。改进后的算法采用平滑的思想和SSMUSIC算法的思想构造协方差矩阵和MUSIC谱,实现了对多径时延的超分辨估计。仿真表明,该算法能够实现对窄带信号多径时延超分辨估计且具有DP(Direct-Path)不模糊和谱峰陡峭的特点,估计性能优于传统的超分辨算法。展开更多
The performance of multiple signal classification （MUSIC） algorithm with regard to solving closely spaced direction of arrivals （DOAs） depends strongly upon the signal-to-noise ratio （SNR） and snapshots. In orde...The performance of multiple signal classification （MUSIC） algorithm with regard to solving closely spaced direction of arrivals （DOAs） depends strongly upon the signal-to-noise ratio （SNR） and snapshots. In order to solve this problem, a method by reconstructing the spatial spectrum function with both noise subspace and signal subspace is presented in this paper. The key idea is to apply the full information contained in covariance matrix and change the projection weights of steering vector on the noise and signal subspace by their revised eigenvalues, respectively. Comparing with the MUSIC algorithm, it does not increase any computational complexity either, and remarkably, it has the advantages of simultaneously reducing noise and keeping the high-resolution ability under low SNR and small sample sized scenarios. Simulation and experiment results are included to demonstrate the superior performance of the proposed algorithm.展开更多
准确的相速度频散图像是主动源面波勘探方法反演近地表横波速度的基础。提出了一种基于频率-速度域多重信号分类(multiple signal classification in frequency-velocity domain)的面波高分辨率频散成像方法(简称fv-MUSIC方法)。该方法...准确的相速度频散图像是主动源面波勘探方法反演近地表横波速度的基础。提出了一种基于频率-速度域多重信号分类(multiple signal classification in frequency-velocity domain)的面波高分辨率频散成像方法(简称fv-MUSIC方法)。该方法首先将传统的频率-波数域波束形成器改造成频率-速度域形式,然后引入多重信号分类算法将空间谱相关矩阵分解为信号子空间和噪声子空间两个部分,最后利用噪声子空间部分生成最终的面波频散图像。理论数据和实际数据应用结果表明,该方法能产生较高精度的相速度图像,并且使用方便,计算效率高,尤其当接收排列较短时,该方法依然能保持较高的相速度分辨率,有利于提高主动源面波方法的横向速度分辨能力。展开更多
在实际通信环境中,由于传播环境的复杂性使空间中存在大量的相干信号,从而导致信源协方差矩阵的秩亏缺。为使得矩阵的秩恢复到等于信号源数并解决相干信源波达方向(direction of arrival,DOA)估计问题,提出了一种混合型MUSIC算法。该算...在实际通信环境中,由于传播环境的复杂性使空间中存在大量的相干信号,从而导致信源协方差矩阵的秩亏缺。为使得矩阵的秩恢复到等于信号源数并解决相干信源波达方向(direction of arrival,DOA)估计问题,提出了一种混合型MUSIC算法。该算法通过前后向空间平滑技术对天线阵列进行预处理,并将得到的新协方差矢量矩阵应用于改进的IMUSIC算法进行信号数据处理分析,得到相干信号的DOA角度估计。仿真结果表明,在信噪比低的情况下,信号间隔很小且存在相关信号时,混合型MUSIC算法能准确地估计出信源的DOA,验证了该算法的高分辨率和高性能。展开更多
文摘将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signal parameters via rotational invariancetechnique,ESPRIT),应用模拟转子故障的定子电流信号测试其频率分辨力、精度等性能,结果表明:即使对于短时信号,二者仍具高频率分辨力,可以准确地分辨定子电流信号中转子故障特征分量、主频分量之频率;但对其幅值、初相角,仅能提供"粗糙"估计。为此,尝试以优化算法——模拟退火算法(simulated annealing algorithm,SAA)与模式搜索算法(pattern search algorithm,PSA)确定各分量的幅值与初相角。同时,分别对MUSIC与ESPRIT、SAA与PSA做了性能对比,遴选优者并应用于转子故障检测。最后,针对转子断条故障进行实验,结果表明:基于高频率分辨力谱估计技术与优化算法的异步电动机转子故障检测方法有效、可行,即使在负载波动、噪声等干扰严重情况下仍然适用。
文摘针对强信号背景下弱信号波达方向(direction of arriaval,DOA)估计问题,提出了一种基于噪声子空间扩展的弱信号DOA估计算法。该算法提出并使用了噪声子空间扩充的思想,其先将强信号导向矢量所在空间纳入噪声子空间进而构造出扩展噪声子空间,再在该扩展噪声子空间基础上利用常规多信号分类(multiple signalclassification,MUSIC)算法得到弱信号的DOA估计。通过噪声子空间的扩充有效地抑制了强信号谱峰,算法无需已知强信号方向及导向矢量,运算量与常规MUSIC相当。理论分析表明该算法对弱信号DOA估计性能不劣于对应的强信号阻塞类算法,仿真实验证实了其有效性和可行性。
文摘提出了一种基于传感器线阵的多重信号分类(Multiple Signal Classification,MUSIC)损伤成像方法用于航空复合材料的损伤监测。该方法采用MUSIC阵列信号处理方法,通过对传感器阵列信号进行协方差特征值分解,在结构上进行方向扫描并构建监测区域的空间谱,从而实现对结构损伤的成像,具有一维传感器阵列易于布置的优点。所提出的方法在变厚度航空复合材料油箱结构上进行了验证,结果表明,该方法能够准确实现航空复合材料结构上的损伤成像,定位误差小于2cm。
基金funded by the National Defence Science and Technology Project Fund of China(No.3101140)the Shanghai Aerospace Science and Technology Innovation Fund of China(No.SAST2015028)the Equipment Prophecy Fund of China(No.9140A21040115KG01001).
文摘To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the geometry of the RLA is formulated and analysed.According to its geometry,the intercepted noncoherent signals in multiple interception intervals are modeled.Correspondingly,the Multiple SIgnal Classification(MUSIC)based noncoherent DPD approach is proposed.Secondly,the synchronous coherent pulse signals are individually considered and formulated.And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals.Besides,we also derive the constrained Cramer-Rao Lower Bound(CRLB)expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known.At last,computer simulations are included to examine the performance of the proposed approach.The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation.In addition,coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.
文摘传统的MUSIC超分辨时延估计技术是直接基于测量数据,其性能往往只对宽带且频谱近似平坦的信号较优,而对窄带信号估计性能较差。针对上述问题,本文通过利用谐波频率估计模型和DOA(Direction of Arrival)估计模型之间的等价性,将时延估计问题转化为谐波频率估计问题,提出了一种改进SSMUSIC(Signal Subspace Scaled Multiple Signal Classification)超分辨多径时延估计算法。改进后的算法采用平滑的思想和SSMUSIC算法的思想构造协方差矩阵和MUSIC谱,实现了对多径时延的超分辨估计。仿真表明,该算法能够实现对窄带信号多径时延超分辨估计且具有DP(Direct-Path)不模糊和谱峰陡峭的特点,估计性能优于传统的超分辨算法。
基金supported by the National Basic Research Program of China (61393010101-1)
文摘The performance of multiple signal classification （MUSIC） algorithm with regard to solving closely spaced direction of arrivals （DOAs） depends strongly upon the signal-to-noise ratio （SNR） and snapshots. In order to solve this problem, a method by reconstructing the spatial spectrum function with both noise subspace and signal subspace is presented in this paper. The key idea is to apply the full information contained in covariance matrix and change the projection weights of steering vector on the noise and signal subspace by their revised eigenvalues, respectively. Comparing with the MUSIC algorithm, it does not increase any computational complexity either, and remarkably, it has the advantages of simultaneously reducing noise and keeping the high-resolution ability under low SNR and small sample sized scenarios. Simulation and experiment results are included to demonstrate the superior performance of the proposed algorithm.
文摘准确的相速度频散图像是主动源面波勘探方法反演近地表横波速度的基础。提出了一种基于频率-速度域多重信号分类(multiple signal classification in frequency-velocity domain)的面波高分辨率频散成像方法(简称fv-MUSIC方法)。该方法首先将传统的频率-波数域波束形成器改造成频率-速度域形式,然后引入多重信号分类算法将空间谱相关矩阵分解为信号子空间和噪声子空间两个部分,最后利用噪声子空间部分生成最终的面波频散图像。理论数据和实际数据应用结果表明,该方法能产生较高精度的相速度图像,并且使用方便,计算效率高,尤其当接收排列较短时,该方法依然能保持较高的相速度分辨率,有利于提高主动源面波方法的横向速度分辨能力。
文摘在实际通信环境中,由于传播环境的复杂性使空间中存在大量的相干信号,从而导致信源协方差矩阵的秩亏缺。为使得矩阵的秩恢复到等于信号源数并解决相干信源波达方向(direction of arrival,DOA)估计问题,提出了一种混合型MUSIC算法。该算法通过前后向空间平滑技术对天线阵列进行预处理,并将得到的新协方差矢量矩阵应用于改进的IMUSIC算法进行信号数据处理分析,得到相干信号的DOA角度估计。仿真结果表明,在信噪比低的情况下,信号间隔很小且存在相关信号时,混合型MUSIC算法能准确地估计出信源的DOA,验证了该算法的高分辨率和高性能。
