This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail...This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.展开更多
针对轧辊偏心信号是混杂在各种随机干扰中含有多次谐波的复杂高频周期信号,以及FFT(Fast Fourier Transform)法对轧辊偏心信号分析的局限性,研究了一种基于四阶累积量的Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的...针对轧辊偏心信号是混杂在各种随机干扰中含有多次谐波的复杂高频周期信号,以及FFT(Fast Fourier Transform)法对轧辊偏心信号分析的局限性,研究了一种基于四阶累积量的Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法.利用基于四阶累积量的Root-MUSIC法准确估计出偏心谐波的频率及谐波的个数,同时由Root-MUSIC求得的根直接使用Prony方法估计出偏心信号的各次谐波幅值和相位.仿真结果和实验结果也验证了结合方法的可行性和有效性,在信噪比较低的情况下仍具有较高的频谱分辨率和估计精度,能准确地同时估计出偏心谐波的频率、幅值及相位,尤其在频率分辨率和抗噪声上具有FFT法无法比拟的优越性.展开更多
针对轧辊偏心信号是混杂在各种随机干扰中的复杂高频周期信号,因FFT法对信号分析的局限性,提出了一种Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法。利用Root-MUSIC法准确估计出偏心谐波的频...针对轧辊偏心信号是混杂在各种随机干扰中的复杂高频周期信号,因FFT法对信号分析的局限性,提出了一种Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法。利用Root-MUSIC法准确估计出偏心谐波的频率及谐波的个数,同时使用Prony方法估计出偏心信号的各次谐波幅值和相位。仿真结果验证了可行性和有效性,在信噪比较低的情况下仍能准确地同时估计出偏心谐波的频率、幅值及相位,尤其在频率分辨率和抗噪声上比FFT法具有优越性。展开更多
文摘This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.
文摘针对轧辊偏心信号是混杂在各种随机干扰中含有多次谐波的复杂高频周期信号,以及FFT(Fast Fourier Transform)法对轧辊偏心信号分析的局限性,研究了一种基于四阶累积量的Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法.利用基于四阶累积量的Root-MUSIC法准确估计出偏心谐波的频率及谐波的个数,同时由Root-MUSIC求得的根直接使用Prony方法估计出偏心信号的各次谐波幅值和相位.仿真结果和实验结果也验证了结合方法的可行性和有效性,在信噪比较低的情况下仍具有较高的频谱分辨率和估计精度,能准确地同时估计出偏心谐波的频率、幅值及相位,尤其在频率分辨率和抗噪声上具有FFT法无法比拟的优越性.
基金Scientific and technological development plan project in Jilin Province(20150519023JH)~~
文摘针对轧辊偏心信号是混杂在各种随机干扰中的复杂高频周期信号,因FFT法对信号分析的局限性,提出了一种Root-MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法。利用Root-MUSIC法准确估计出偏心谐波的频率及谐波的个数,同时使用Prony方法估计出偏心信号的各次谐波幅值和相位。仿真结果验证了可行性和有效性,在信噪比较低的情况下仍能准确地同时估计出偏心谐波的频率、幅值及相位,尤其在频率分辨率和抗噪声上比FFT法具有优越性。
