| 引用本文: | 张晓威,牛晓红,翟广锐.改进的Prony算法在多正弦信号频率估计中的应用研究[J].电力系统保护与控制,2017,45(15):140-145.[点击复制] |
| ZHANG Xiaowei,NIU Xiaohong,ZHAI Guangrui.Application research of the improved Prony algorithm in the multiple sinusoidal signal frequency estimation[J].Power System Protection and Control,2017,45(15):140-145[点击复制] |
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| 摘要: |
| 针对噪声背景下经典Prony算法对多正弦信号频率估计受限的问题，提出一种抗噪性强的改进Prony算法。通过建立一种新的累积关系，提出的算法可以在低信噪比情况下，仅利用适当数量的新序列值线性重构稀疏和，从而较为精确地估计出信号的频率。对提出的算法与经典Prony算法的性能作出仿真实验对比。实验结果表明，在信号中嵌入噪声时，经典Prony算法在估计信号频率时失去效用，而新算法依旧可以有效估计信号频率。所以，提出的算法抗噪能力较强，性能相对稳定，精度较高，在多正弦信号频率估计中表现出更好的实用性。 |
| 关键词: Prony算法 频率估计 线性重构 稀疏和 信噪比 |
| DOI：10.7667/PSPC160987 |
| 投稿时间：2016-07-01修订日期：2016-08-18 |
| 基金项目: |
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| Application research of the improved Prony algorithm in the multiple sinusoidal signal frequency estimation |
| ZHANG Xiaowei,NIU Xiaohong,ZHAI Guangrui |
| (College of Science, Harbin Engineering University, Harbin 150001, China) |
| Abstract: |
| For the problem that estimating multiple sinusoidal signal frequency is insufficient by using the classical Prony algorithm under the noise background, this paper proposes an improved Prony algorithm with strong antinoise ability. Through establishing a new accumulation relationship, the proposed algorithm can only use appropriate new sequence values to reconstruct the sparse sums linearly under the condition of low SNR, so as to more accurately estimate signal frequency. It compares the proposed algorithm with the classical Prony algorithm by making the simulation experiment. And the experimental results show that as the signal embedded in the noise, the classical Prony algorithm loses effectiveness for the signal frequency estimation, and while the new algorithm can still effectively estimate signal frequency. So, the proposed algorithm has strong antinoise ability, relative stable performance and high precision advantages and shows better practicability in the multiple sinusoidal signal frequency estimation. |
| Key words: Prony algorithm frequency estimation linear reconstruction sparse sums SNR |
