Two-Dimensional DOA Estimation for Incoherently Distributed Sources with Uniform Rectangular Arrays

• Main Authors: Tao Wu, Zhenghong Deng, Yiwen Li, Yijie Huang
• Format: Article
• Language: English
• Published: MDPI AG 2018-10-01
• Series: Sensors
• Subjects: incoherently distributed sources; generalized steering matrix; generalized signal vector; rotational invariance relations; angle matching
• Online Access: https://www.mdpi.com/1424-8220/18/11/3600

Aiming at the two-dimensional (2D) incoherently distributed (ID) sources, we explore a direction-of-arrival (DOA) estimation algorithm based on uniform rectangular arrays (URA). By means of Taylor series expansion of steering vector, rotational invariance relations with regard to nominal azimuth and nominal elevation between subarrays are deduced under the assumption of small angular spreads and small sensors distance firstly; then received signal vectors can be described by generalized steering matrices and generalized signal vectors; thus, an estimation of signal parameters via rotational invariance techniques (ESPRIT) like algorithm is proposed to estimate nominal elevation and nominal azimuth respectively using covariance matrices of constructed subarrays. Angle matching method is proposed by virtue of Capon principle lastly. The proposed method can estimate multiple 2D ID sources without spectral searching and without information of angular power distribution function of sources. Investigating different <i>SNR,</i> sources with different angular power density functions, sources in boundary region, distance between sensors and number of sources, simulations are conducted to investigate the effectiveness of the proposed method.