基于数据矩阵分解的相干源方向估计新方法

提出一种相干源存在情况下的波达方向估计新算法。利用阵列快拍数据构造数据矩阵,相关去噪后,通过奇异值分解获得低维信号子空间的估计,然后运用ESPRIT思想估计出波达方向。无论是否存在相干源,新算法均能有效估计出波达方向,并且无需角度搜索,运算量小。该算法虽基于一维线阵,但可直接推广到具有线性性质的二维平面阵,如L形阵、十字阵、双平行线阵等。计算机仿真验证了算法的有效性

Direction finding in the presence of coherent signals based on data matrix decomposition

A new algorithm for direction finding in the presence of coherent signals is presented. By arranging the sampled data, a special data matrix is constructed. By using correlation vectors to eliminate the noise's influence, the signal subspace estimation is obtained by singular value decomposition (SVD) of the data matrix, then the direction parameters are estimated based on the ESPRIT method. Without spectral peak search and complex computation, the algorithm provides estimates of the directions of arrival (DOA), no matter there are coherent signals or not. The performance of the algorithm is illustrated by computer simulations.