In the field of array signal processing,direction of arrival (DOA)estimation is a hotspot problem.Classical DOA estimation methods usually require the number of sensor should be larger than the source signals’(which the so-called over-determined case is).However, what we encounter in practice is always the underdetermined case in which the number of source signal is larger than the sensors’.To solve the problem,a multiple signal classification (MUSIC)extension algorithm based on spatial time-frequency distribution was proposed to achieve the underdetermined DOA estimation by expanding the dimension of the spatial time-frequency distributions matrices.Compared with the existing time-frequency MUSIC,the proposed algorithm can be applied to both the over-determined and the underdetermined cases.The proposed algorithm also has advantages over the existing underdetermined DOA estimation methods for it guarantees the estimation precision,relaxes the requirements for source signal sparseness and lowers standards of the number of snapshots.Simulation results confirm the validity and high performance of the proposed algorithm.%波达方向估计是阵列信号处理领域的热点问题，但经典的波达方向估计方法通常要求阵元数大于源信号个数，即满足超定条件，而在实际中往往面临的是源信号个数大于阵元数的欠定条件。基于此，提出了一种基于空间时频分布的多重信号分类扩展算法，通过将空间时频分布矩阵进行扩展，实现了欠定条件下的波达方向估计。相比时频多重信号分类算法，所提算法能同时适应超定和欠定条件；相比已有的欠定波达方向估计方法，其不但保证了波达方向估计的精度，而且放宽了对源信号稀疏性的要求，同时还降低了对快拍数的要求。仿真实验结果证明了该方法的有效性。
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