By theoretically analyzing the shortage of the traditional algorithm of DOA estimation with a small subspace-based sample size, a non-parametric and least squares-based iterative algorithm is proposed for amplitude and phase estimation in array processing, which is based on the sparse signal representation. Utilizing a DAS beamformer for DOA estimation initially, this algorithm iteratively calculates the co-variance matrix until it reaches convergence. In sharp contrast with former method that needs to estimate the signals number, the proposed method can reach the aim of estimation even with few snapshots. Simulation results show that this algorithm performs better in estimation of precision and resolution.%针对传统子空间类算法在短数据测向的不足，提出一种基于稀疏信号描述的非参数最小均方迭代的幅度相位估计算法。该算法首先运用DAS波束形成对信号到达角进行初步估计，然后用最小均方误差准则及幅度相位估计算法( APES)对协方差矩阵进行迭代更新直至收敛。该方法能够在快拍数较少条件下进行DOA估计，且不需要估计信号源个数。理论分析和仿真实验表明其相对传统子空间类算法有较高的估计精度和分辨率。
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