强信号背景下基于噪声子空间扩充的弱信号DOA估计方法

DOA estimation based on extended noise subspace in the presence of strong signals

针对强信号背景下弱信号波达方向(direction of arriaval,DOA)估计问题,提出了一种基于噪声子空间扩展的弱信号DOA估计算法。该算法提出并使用了噪声子空间扩充的思想,其先将强信号导向矢量所在空间纳入噪声子空间进而构造出扩展噪声子空间,再在该扩展噪声子空间基础上利用常规多信号分类(multiple signalclassification,MUSIC)算法得到弱信号的DOA估计。通过噪声子空间的扩充有效地抑制了强信号谱峰,算法无需已知强信号方向及导向矢量,运算量与常规MUSIC相当。理论分析表明该算法对弱信号DOA估计性能不劣于对应的强信号阻塞类算法,仿真实验证实了其有效性和可行性。

When strong jamming or signal is presented, its peak in the spatial spectral will submerge the peak of signals with lower power. For signal direction-of-arrival （DOA） estimation in the presence of strong jamming or signals, an idea of modifying the noise subspace and then a new method is presented. First, to form the extended noise subspace, the traditional noise subspace is modified by adding the space composed of the steering vectors of strong signals into it, then conventional （multiple signal classification, MUSIC） is applied to this extended noise subspace and the DOAs of low SNR（signal-to-noise ratio） signals are obtained. The peaks of strong signals in spatial spectrum are attenuated significantly and effectively by extending the noise subspace and it does not require either the angle of incidence of strong signals or the steering vectors of them as preknowledge and has less computation burden compared with the other algorithms. Theoretic analysis shows the DOA estimation performance of this new algorithm is not less than its corresponding blocking algorithms, and computer simulation demonstrates its effectiveness and feasibility.