A Novel Sparse Fourier Orthogonal Coding-Based DOA Estimation Technique Using a Hermitian Propagator and Covariance Projection
Received: 24 May 2025 | Revised: 19 June 2025 | Accepted: 6 July 2025 | Online: 29 August 2025
Corresponding author: A. N. Ashraya
Abstract
This paper presents a robust method for Direction of Arrival (DOA) estimation using Sparse Fourier Orthogonal Coding (FOC). High-precision DOA estimation in radar, sonar, and wireless systems often suffers from noise, interference, and limited resolution. To overcome these issues, this study proposes a framework that integrates Sparse FOC, Hermitian Propagator, and Sparse Toeplitz Covariance Matrix Projection, forming the Sparse Hermitian Propagator for DOA Estimation (SHP-DE). The proposed method improves estimation by decomposing received signals into orthogonal components, improving feature extraction and information diversity. The Hermitian Propagator eliminates the need for eigenvalue or singular value decomposition, reducing computational complexity without sacrificing accuracy. The Toeplitz Covariance Projection further refines the covariance structure, enhancing noise suppression and estimation stability. Simulation results demonstrate that SHP-DE achieves superior resolution and robustness, outperforming traditional algorithms, such as MUSIC and ESPRIT, in various noisy and closely spaced source scenarios. The ability of the proposed method to maintain performance under challenging conditions marks a significant step toward practical real-time DOA estimation. Thus, SHP-DE is well-suited for applications demanding reliable and accurate localization of signal sources in complex environments.
Keywords:
Direction of Arrival (DOA) estimation, sparse Fourier Orthogonal Coding (FOC), Sparse Hermitian Propagator (SHP-DE), Hermitian propagator, sparse Toeplitz covariance matrix projection, high-resolution estimation, noise suppression, computational efficiency, MUSIC, ESPRIT, signal processingDownloads
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