Super-Resolution Harmonic Retrieval of Non-Circular Signals
Super-Resolution Harmonic Retrieval of Non-Circular Signals
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DOI：
10.1109/icassp49357.2023.10095946
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
Yu Zhang;Yue Wang;Zhi Tian;G. Leus;Gong Zhang
中科院分区：
文献类型：
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作者：
Yu Zhang;Yue Wang;Zhi Tian;G. Leus;Gong Zhang
本文提出了一种不相关的不相关的非圆形信号的超分辨率谐波检索方法，其协方差和伪稳定性分别呈现toeplitz和Hankel结构。因此，由协方差和伪共同矩阵构建的增强协方差矩阵不仅是低等级，而且是共同的toeplitz-hankel结构。为了有效利用这种所需的结构来提高高估计精度，我们开发了在增强的协方差矩阵上采用的低级别toeplitz-hankel协方差重建（LRTHCR）解决方案。此外，我们设计了一个拟合错误限制，以灵活地实现LRTHCR算法而不知道噪声统计信息。此外，在实际环境中为拟议的LRTHCR提供了性能分析。仿真结果表明，LRTHCR在较低的估计误差方面优于基准方法。
This paper proposes a super-resolution harmonic retrieval method for uncorrelated strictly non-circular signals, whose covariance and pseudo-covariance present Toeplitz and Hankel structures, respectively. Accordingly, the augmented covariance matrix constructed by the covariance and pseudo-covariance matrices is not only low rank but also jointly Toeplitz-Hankel structured. To efficiently exploit such a desired structure for high estimation accuracy, we develop a low-rank Toeplitz-Hankel covariance reconstruction (LRTHCR) solution employed over the augmented covariance matrix. Further, we design a fitting error constraint to flexibly implement the LRTHCR algorithm without knowing the noise statistics. In addition, performance analysis is provided for the proposed LRTHCR in practical settings. Simulation results reveal that the LRTHCR outperforms the benchmark methods in terms of lower estimation errors.