非均匀噪声背景下混合信号DOA估计算法

针对非均匀噪声背景下非相关信源与相干信源并存时波达方向(DOA)估计问题,提出了基于迭代最小二乘和空间差分平滑的混合信号DOA估计算法。首先,该算法利用迭代最小二乘方法得到噪声协方差矩阵估计,然后对数据协方差矩阵进行"去噪"处理,利用子空间旋转不变技术实现非相关信源DOA估计;其次,基于空间差分法消除非相关信号并构造新矩阵进行前后向空间平滑,利用求根MUSIC算法估计相干信源DOA。相比于传统算法,该算法能估计更多的信源数,在低信噪比情况下DOA估计性能更优越。仿真实验结果验证了该算法的有效性。

The algorithm for direction-of-arrival for uncorrelated and coherent signals estimation in the presence of unknown nonuniform noise fields

A novel directions of arrival(DOA) estimation method is developed when uncorrelated and coherent sources coexist in nonuniform noise. Its implementation is based on an iterative procedure which includes least squares(LS) problem with respect to the signal subspace and noise nuisance parameters. In our methods, the noise covariance matrix is first iteratively calculated from the array covariance matrix. Then the noise component in the array covariance matrix is eliminated to achieve a noise-free array covariance matrix. The rotational invariance techniques(ESPRIT) can be employed to achieve DOA estimation of the uncorrelated signals. Secondly, the uncorrelated signals are eliminated and a new matrix is constructed based on the spatial difference method. Next, the forward spatial smoothing can be used to realize the covariance matrix rank recovery. Finally, the signal and noise subspaces are achieved by eigendecomposing the noise free covariance matrix, traditional subspace-based DOA estimation root-MUSIC algorithms can be applied directly. The proposed methods can resolve more signals than the conventional method with better performance. Simulation results demonstrate the effectiveness of the proposed method.