Single-Snapshot Direction of Arrival Estimation Method Based on Hyperbolic Tangent Kernel Correntropy

Direction of Arrival (DOA) estimation constitutes a foundational problem within array signal processing. Current single-snapshot DOA estimation techniques often fall short in complex electromagnetic settings, showing limited robustness against low signal-to-noise ratios (SNR) and intense impulsive noise. This paper introduces a new single-snapshot DOA estimation approach that leverages Hyperbolic Tangent Kernel Correntropy combined with a Fibonacci Quantum Grasshopper Optimization Algorithm (QFGOA-SMCE-WSF) to improve robustness. The technique builds a cross-correntropy covariance matrix using the hyperbolic tangent kernel, producing a weighted signal subspace fitting formulation tailored for single-snapshot scenarios. This enables reliable DOA estimation even under low SNR and significant impulsive noise. The proposed Fibonacci quantum grasshopper search method lowers computational demands while enhancing solution precision and stability, leading to more resilient DOA estimates. Simulation outcomes demonstrate that QFGOA-SMCE-WSF achieves high estimation accuracy for both coherent and independent sources across Gaussian, mild impulsive, and severe impulsive noise conditions, proving effective even at low generalized SNRs.