High resolution adaptive estimator of sinusoidal based on covariance matrix reconstruction
High resolution adaptive estimator of sinusoidal based on covariance matrix reconstruction
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DOI：
10.1016/j.sigpro.2023.109034
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发表时间：
2023-03
期刊：
影响因子：
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通讯作者：
Xiaowei Qian;Wei Liang;Ziqiao Chen;Zexuan Zhang;Xintong Zhang;Zhong Chen;Yulan Lin
中科院分区：
文献类型：
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作者：
Xiaowei Qian;Wei Liang;Ziqiao Chen;Zexuan Zhang;Xintong Zhang;Zhong Chen;Yulan Lin
指数衰减的正弦信号在工程和研究领域中经常被观察到。在一些实际应用中，多个信号的频率相互接近。用离散傅里叶变换处理这些拥挤的信号，特别是在缺乏采样时间和信号快速衰减的情况下，将面临一项具有挑战性的任务。局域Capon估计器（LoCapE）在提高指数衰减正弦信号的分辨率方面已经证明了它的优势。但是，由于受到干扰分量的影响，LoCapE提取的各分量的幅值和频率并不准确。本文通过重构干扰加噪声协方差矩阵代替信号协方差矩阵对LoCapE方法进行了改进。在模拟和真实的指数衰减正弦数据上的实验结果表明，该方法在缺少采样点的情况下提取参数更加准确。
Exponentially decaying sinusoidal signal is often observed in engineering and research fields. In some practical applications, the frequencies of multiple signals are close to each other. It would face a challenging task to resolve these crowded signals processed by discrete Fourier transformation, especially in the case of the lack of sampling time and the fast-decaying signals. The Localised Capon estimator (LoCapE) has demonstrated its advantage in improving the resolution of exponentially decaying sinusoidal signals. However, the amplitude and the frequency of each component extracted by the LoCapE are not accurate due to the effect from interference components. Here, we improve the LoCapE method by reconstructing the interference-plus-noise covariance matrix instead of the signal covariance matrix. Experimental results on simulated and real exponentially decaying sinusoidal data show that the proposed method is more accurate in extracting parameters at the lack of sampling points.