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A single source location method based on a independent doublet array is proposed. It is considered that the source is located at the far-field of each doublet and the near-field of the array. The presented method realises direction of arrival estimation by an ESPRIT-like technique, and the range of the source by array geometry successively. It provides a simple and search-free estimation method for single near-field source location. Simulation results are presented that verify the effectiveness of the method.Introduction: Near-field source location requires the simultaneous estimation of bearing and range. Estimation algorithms [1-3] usually involve single dimensional or multidimensional search. Besides, most near-field source location algorithms are based on the Fresnel approximate model [4]. However, the data model of a near-field source introduces a systemic error [4,5] in algorithms. In this Letter, we present a new algorithm based on a special array geometry to avoid searching for parameters estimation and model systemic error. The array consists of several independent doublet sensors, where the sensors of each doublet share the same local oscillation and the sensors between doublets apply different local oscillations. According to this point, all doublets of sensors can be placed at great spacing for good resolution.

Abstract-In this paper, a new decoupled Unitary ESPRIT algorithm for two-dimensional (2-D) direction-of-arrival (DOA) estimation is presented. By exploiting the centro-symmetric array configurations of two parallel uniform linear arrays (TP-ULAs) and utilizing the via rotational invariance techniques, the proposed algorithm has advantages as listed below. First, the algorithm enables decoupling the estimation problem into a two-step estimation problem and obtains the automatically matched 2-D DOAs. Second, employing the elements of the array fully, the algorithm can estimate 2-D DOAs up to 2(M − 1), where 2M is the sensor number of the array. Besides, the computational complexity of the proposed algorithm is lower than other representative 2-D DOA estimation methods. Simulation results are presented to show the effectiveness of the proposed method.