| 最小二乘法分离频率相近的正弦信号 |
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| 引用本文： | 王哲英,马明旭,朴凤贤,王哲锋.最小二乘法分离频率相近的正弦信号[J].电子与信息学报,2006,28(1):60-65. |
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| 作者姓名： | 王哲英 马明旭 朴凤贤 王哲锋 |
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| 作者单位： | 沈阳工业大学材料科学与工程学院成型教研室,沈阳,110023;中国科学院沈阳自动化研究所,沈阳,110016;沈阳航空工业学院,沈阳,110034;东北大学材料与冶金学院,沈阳,110004 |
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| 摘 要： | 传统的快速傅里叶变换(FFT)可以有效地对正弦信号进行分析，但对于分析频率相近的正弦信号却存在很大的误差。该文提出了采用最小二乘法来分析该问题。该算法在观测矩阵的基础上，利用2范数最小的终止准则，通过求解超定方程组，辨识频率相近信号组成的特征参数。仿真结果表明，该方法可以精确地分析频率相近信号各组成部分，有效地抑制噪声的干扰，具有较好的噪声稳定性和频域分析能力，从而提高信号处理的效率与精度。
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| 关 键 词： | 信号处理 FFT 最小二乘法 |
| 文章编号： | 1009-5896（2006）01-0060-06 |
| 收稿时间： | 2004-06-15 |
| 修稿时间： | 2005-05-16 |
The Separation of Similar Frequency Sinusoidal Signal Based on the Least Square Method |
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| Wang Zhe-ying,Ma Ming-xu,Piao Feng-xian,Wang Zhe-feng.The Separation of Similar Frequency Sinusoidal Signal Based on the Least Square Method[J].Journal of Electronics & Information Technology,2006,28(1):60-65. |
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| Authors: | Wang Zhe-ying Ma Ming-xu Piao Feng-xian Wang Zhe-feng |
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| Affiliation: | Metal Forming Research Office, Shenyang University of Technology, Shenyang 110023, China; Shenyang Institute of Automation, Chinese Academy of Sciences,Shenyang 110016, China;Shenyang Institute of Aeronautical Engineering, Shenyang 110034, China;Material & Metallurgy Academic, Northeastern University, Shenyang , 110004 , China |
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| Abstract: | Traditional FFT can effectively analyze the sinusoidal signal, but the very big error exists for analyzing the similar frequency sinusoidal signal. In this article, adopting Least Square (LS) method which can separate similar frequency sinusoidal signal is put forward. Characteristic parameters of separating similar frequency sinusoidal signal can be identified by satisfying termination criterion of 2-norm minimum and solving overdetermined equations on observation matrix. The simulation result shows that each component of similar frequency signal such as amplitude, phase angle can be separated from original signal, the interference of noise can effectively be restrained, noise stability and the frequency domain analysis ability become better, so the efficiency and precision of signal processing can be raised. |
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| Keywords: | FFT |
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