In this paper, a one-step method is proposed for the classification and estimation of the parameters in the scenario of mixed near-field and far-field stationary sources. By constructing several temporal-spatial cumulant matrices, utilizing the stationary property of sources, and introducing a mechanism for controlling the rank, a parameters estimation matrix is formed. This matrix contains electric angles and signals information. By introducing a method based on the rotational invariant technique and using the estimation signal parameter, the direction-of-arrival of all sources' signals and the range of the near-field sources (NFSs) are estimated. Also, a reasonable classification of the signals types is provided. Unlike conventional methods, the proposed method does not require any spectral search stage, so it reduces the computational complexity to a great extent. The proposed algorithm prevents the array aperture loss, has no need to know the number of NFSs or field-field sources, and does not require any extra stage to pair the parameters. Mathematical analysis and simulation results validate the good performance of parameters estimation and sources classification in the proposed method.

本文提出了一种近场和远场混合固定源情景下参数的分类和估计的单步方法。通过构造几个时空累积量矩阵，利用源的平稳特性，并引入控制等级的机制，形成参数估计矩阵。该矩阵包含电角度和信号信息。通过引入一种基于旋转不变技术的方法并使用估计信号参数，可以估计所有源信号的到达方向和近场源（NFS）的范围。而且，提供了信号类型的合理分类。与传统方法不同，该方法不需要任何频谱搜索阶段，这样就大大降低了计算复杂度。所提出的算法可以防止阵列孔径损失，不需要知道NFS或场源的数量，并且不需要任何额外的阶段来配对参数。数学分析和仿真结果验证了该方法在参数估计和源分类方面的良好性能。