基于特征空间MUSIC算法的相干信号波达方向空间平滑估计

发布时间：2018-04-30 10:30

  本文选题：信息处理技术 + 波达方向估计　； 参考：《吉林大学学报(工学版)》2017年01期

【摘要】：为了高效、准确地估计相干信号的波达方向(DOA),提出了一种基于特征空间多重信号分类(MUSIC)算法的空间平滑估计方法。首先对相干信号进行空间平滑处理,然后对其应用特征空间MUSIC算法进行DOA的精确估计,使其最大限度地利用信号子空间和噪声子空间的信息。本文方法并不影响非相关信号存在时DOA的估计,且还可以对信号源功率进行有效的估计,以提高对小能量信号的成功估计概率。与传统空间平滑算法及修正MUSIC算法相比,本文方法具有更低的信噪比门限和更高的估计精度及分辨力。最后的仿真实验验证了本文方法的有效性和鲁棒性。
[Abstract]:In order to estimate the DOA of coherent signals efficiently and accurately, a spatial smoothing estimation method based on feature space multi-multiple signal classification algorithm (MUSIC-based) is proposed. Firstly, the coherent signal is processed by spatial smoothing, and then the DOA is estimated accurately by using the eigenspace MUSIC algorithm to maximize the use of the information of the signal subspace and the noise subspace. The proposed method does not affect the estimation of DOA in the presence of non-correlated signals, and it can also effectively estimate the power of the signal source so as to improve the probability of successful estimation of small energy signals. Compared with the traditional spatial smoothing algorithm and the modified MUSIC algorithm, the proposed method has lower SNR threshold, higher estimation accuracy and higher resolution. Finally, the simulation results show the effectiveness and robustness of the proposed method.
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本文编号：1824203