中文摘要：

OPM方法是一种简便的求解噪声子空间进而估计DOA的方法，在高信噪比时，该方法性能很好，但随着信噪比的降低，算法性能很快下降，特别是其分辨概率下降很快。其主要原因就是低信噪比和DOA相邻较近时，信号源之间的空间相关性较强。提出了一种逐次消除空间相关性并逐次搜索DOA的改进OPM方法，该方法提高了分辨概率。仿真结果证明了方法的有效性。

英文摘要：

OPM is a simple method for the estimation of noise signal subspace. At high SNR, OPM has an excellent resolution performance,but with the SNR going down, the performance became bad,especially for the probability of resolution. The main reason is that the spatial correlation among sources increase with the low SNR and close spaced sources. An improved OPM is presented by using sequential searching and searching vector updating. The probability of resolution is improved. Simulation results demonstrate the effectiveness of the method.