Time–frequency (TF) approaches are frequently employed for source localization at low signal to noise ratio. However, TF approaches fail to achieve the desired performance for sparsely sampled signals or signals corrupted by heavy noise in an under-determined scenario when sources are not TF separable. In this study, we propose a new TF method for direction of arrival (DOA) estimation of sources with closely spaced and overlapping TF signature. The proposed method uses a combination of a high-resolution time–frequency distribution and instantaneous frequency estimation method for extraction of sources with intersecting and closely spaced time–frequency signatures. Once sources are extracted, their DOAs are estimated using a well known multiple signal classification (MUSIC) algorithm. Experimental results demonstrate that the proposed source localization method achieves better performance as compared to the conventional time–frequency MUSIC algorithm.

中文翻译：

---

使用中频估计和 MUSIC 算法相结合的时频域相交信号源的到达方向估计

时频 (TF) 方法经常用于低信噪比的源定位。然而，当源不可 TF 分离时，TF 方法无法在不确定的情况下为稀疏采样的信号或被重噪声破坏的信号实现所需的性能。在这项研究中，我们提出了一种新的 TF 方法，用于估计具有紧密间隔和重叠 TF 特征的源的到达方向（DOA）。所提出的方法结合使用高分辨率时频分布和瞬时频率估计方法来提取具有相交且间隔很近的时频特征的源。提取源后，使用众所周知的多信号分类 (MUSIC) 算法估计其 DOA。