Polynomial rooting-based DOA estimation algorithm for vector-sensor arrays using quaternions

• Published in: Multidimensional systems and signal processing Vol. 33; no. 4; pp. 1221 - 1235
• Main Authors: Jamshidpour, Sadegh, Sakhaei, Sayed Mahmoud
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2022; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Circuits and Systems; Criteria; Direction of arrival; Eigenvectors; Electrical Engineering; Engineering; Linear arrays; Orthogonality; Polynomials; Quaternions; Sensor arrays; Signal,Image and Speech Processing; Steering; Vector-sensors; Polynomial rooting; Quaternions; Direction-of-arrival (DOA)estimation
• ISSN: 0923-6082; 1573-0824
• DOI: 10.1007/s11045-022-00841-z

This paper considers the problem of direction-of-arrival (DOA) estimation using uniform linear arrays (ULAs) composed of two-component electromagnetic vector-sensors. Quaternions are utilized as a primitive tool for our design. Using the elegant quaternion modeling of the received data, a useful orthogonality criterion between the noise subspace eigenvectors and the spatial steering vector of the array is derived. This criterion enables us to utilize the Vandermonde structure of the spatial steering vector of a ULA to develop a polynomial rooting-based DOA estimation algorithm, denoted by Q-Root-MUSIC. The proposed method replaces the need for a search procedure over the DOA and the polarization parameters with a polynomial rooting procedure which significantly reduces the computational burden of the method. Simulations are conducted to demonstrate the performance of the proposed method. The simulation results show that the proposed method provides improved resolution capabilities for closely-spaced sources in the low signal-to-noise ratios with dramatically lower computational complexity.