Real-Valued 2D MUSIC Algorithm Based on Modified Forward/Backward Averaging Using an Arbitrary Centrosymmetric Polarization Sensitive Array

• Published in: Sensors (Basel, Switzerland) Vol. 17; no. 10; p. 2241
• Main Authors: Si, Weijian, Wang, Yan, Hou, Changbo, Wang, Hong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 29-09-2017; MDPI
• Subjects: 2D DOA estimation; Algorithms; Complexity; Computation; Computer simulation; Cramer-Rao bound; Cramer-Rao bounds; dimension reduction; Direction of arrival; forward/backward averaging; MUSIC; Parameter estimation; polarization sensitive array; real-valued operations; Search process; Two dimensional models; MUSIC; real-valued operations; forward/backward averaging; Cramer-Rao bound; 2D DOA estimation; polarization sensitive array; dimension reduction
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s17102241

Two-dimensional multiple signal classification (MUSIC) algorithm based on polarization sensitive array (PSA) has excellent performance. However, it suffers a high computational complexity due to a multitude of complex operations. In this paper, we propose a real-valued two-dimensional MUSIC algorithm based on conjugate centrosymmetric signal model, which is applicable to arbitrary centrosymmetric polarization sensitive array. The modified forward/backward averaging, which can be applied to the PSA, is presented. Hence, the eigen-decomposition analysis process and spectrum function computation are converted into real domain, prominently reducing the computational complexity. Then, the direction-of-arrival (DOA) estimation is decoupled from the polarization parameter estimation so that the four-dimensional spectral peak search process is avoided. The theoretical computational complexity is discussed and the Cramer-Rao bound (CRB) of DOA estimation is derived in this paper. The simulation results indicate that the proposed algorithm achieves superior accuracy in DOA estimation and has low computational complexity.