A modified robust multiple signal classification (MUSIC) algorithm for direction-of-arrival (DOA) estimation of coherent source signals is devised in this work. Classical and subspace-based methods require large antenna elements and huge computations for the estimation of intended signals. It also deviates from its performance in low signal-to-noise ratio (SNR) conditions. Hence efficient and robust DOA estimators are required to tackle the real-time problems in wireless communication applications. To overcome these problems, the classical MUSIC algorithm is modified by assimilating Jordon canonical matrix in the covariance matrix for the reconstruction of data. With this modification, it is possible to make an accurate estimation of coherent sources even under an extremely low SNR environment. Furthermore, the proposed method requires fewer antenna elements, fewer snapshots, and less computation as compared to the classical MUSIC algorithm. The experimental results signify the effectiveness of the new method.

在这项工作中设计了一种改进的鲁棒多信号分类（MUSIC）算法，用于相干源信号的到达方向（DOA）估计。经典的和基于子空间的方法需要大的天线单元和大量的计算来估计预期信号。它还偏离了其在低信噪比（SNR）条件下的性能。因此，需要有效且健壮的DOA估计器来解决无线通信应用中的实时问题。为了克服这些问题，经典的MUSIC算法通过在协方差矩阵中吸收Jordon正则矩阵进行了修改，以重建数据。通过这种修改，即使在极低的SNR环境下，也可以准确估计相干源。此外，与经典的MUSIC算法相比，所提出的方法需要更少的天线元件，更少的快照和更少的计算。实验结果表明了该方法的有效性。