一种新的相干信源互耦自校正算法

针对互耦效应下相干信源的波达方向（direction of arrival，DOA）估计问题，提出一种基于阵列接收数据一阶统计量的解相干及互耦自校正算法.算法利用阵元接收数据的一阶统计量构造伪协方差矩阵，理论推导证明，互耦系数已从理想导向矢量中剥离，且该矩阵的秩与信源相关性无关，仅与信源个数相等，即实现了信源的解相干及互耦自校正，因此通过对重构矩阵进行一次特征分解即可实现DOA估计.此外，对算法的子空间估计性能及由互耦系数导致的测角模糊性进行了分析，结果表明该算法实现过程简单，计算量小，在低信噪比和短快拍数时仍具有很高的估计性能.仿真结果验证了算法的有效性. 

A Novel Self-Calibration Algorithm for Coherent Signal Sources

To estimate direction of arrival (DOA) for coherent signal sources in the presence of mutual coupling, a novel self-calibration and decorrelation method was presented based on the first order statistics of array received data. A pseudo covariance matrix was constructed by the first order statistics. Theoretical analysis proves that, the rank of the matrix was determined by the number of signals, without any relation with the coherency of signals. The mutual coupling coefficients have already been isolated from the ideal steering vectors. This shows that DOA estimation can be achieved by performing once decomposition to the reconstructed matrix. Moreover, the performance of subspace estimation and the fuzziness of DOA estimation caused by mutual coupling coefficients were analyzed respectively. Results show that, the proposed method has high performance under scenarios of low SNR and snapshot deficiency with simple implementation and low computational complexity. Simulations present the effectiveness of the method.