Abstract
In this paper, the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation with parallel linear arrays is addressed. Two array manifold matching (AMM) approaches, in this work, are developed for the incoherent and coherent signals, respectively. The proposed AMM methods estimate the azimuth angle only with the assumption that the elevation angles are known or estimated. The proposed methods are time efficient since they do not require eigenvalue decomposition (EVD) or peak searching. In addition, the complexity analysis shows the proposed AMM approaches have lower computational complexity than many current state-of-the-art algorithms. The estimated azimuth angles produced by the AMM approaches are automatically paired with the elevation angles. More importantly, for estimating the azimuth angles of coherent signals, the aperture loss issue is avoided since a decorrelation procedure is not required for the proposed AMM method. Numerical studies demonstrate the effectiveness of the proposed approaches.
Highlights
Direction-of-arrival (DOA) estimation plays an important role in many fields such as wireless communication, multiple-input multiple-output (MIMO) radar, sonar, etc. [1,2,3]
Equations (20)–(26), we find the bilateral array manifold matching (AMM) method is suitable for incoherent signals
AMM methods are proposed for 2D DOA estimation for parallel linear arrays
Summary
Direction-of-arrival (DOA) estimation plays an important role in many fields such as wireless communication, multiple-input multiple-output (MIMO) radar, sonar, etc. [1,2,3]. Based on the assumption that the elevation and azimuth angles are independently estimated, many effective pair-matching methods were proposed [8,17,18] For those methods, computational complexity is high, since twice 1D DOA estimation algorithms are involved. In [25], fourth-order cumulants of received data from two-parallel uniform linear arrays were arranged to reconstruct two Toeplitz matrices (it is called the TMR algorithm in this paper), the rank of which is equal to the number of incoming signals This algorithm had lower complexity than many similar algorithms, it caused more serious aperture loss than the SS and BCM methods. The elevation and azimuth angles are estimated by using SVD once in BCM-AMM It demonstrates the lower complexity and the higher precision than the TMR algorithm [25].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
