论文部分内容阅读
提出了一种用于近场窄带信源频率、二维到达角及距离四维参数联合估计的新算法.该方法将通常在数据域和子空间域应用的平行因子分析模型扩展至高阶累积量域,利用计算的5个高阶累积量矩阵构造三面阵,分析了该三面阵低秩分解的唯一性,并从其分解得到的5个对角阵中联合估计信源参数.与现有方法相比,该算法有效减小了阵列的孔径损失,无须参数配对.此外,该算法还可用于远场和近场混合源的参数估计.仿真结果表明该算法是有效的.
A new algorithm for joint estimation of near-field narrow-band source frequency, two-dimensional angle of arrival and four-dimensional parameters of distance is proposed, which extends the parallel factor analysis model usually applied in data and subspace to higher order cumulant domain, Based on the calculated five higher-order cumulant matrices, the three-plane array is constructed and the uniqueness of the low-rank decomposition of the three-plane array is analyzed and the parameters of the source parameters are jointly estimated from the five diagonal arrays obtained by the decomposition. Compared with the existing methods The proposed algorithm can effectively reduce the aperture loss of the array and does not require pairing of parameters.In addition, the proposed algorithm can also be used to estimate the parameters of far-field and near-field hybrid sources.The simulation results show that this algorithm is effective.