A Novel DOA Estimation Method for a Far-Field Narrow-Band Point Source via the Conventional Beamformer

Far-field narrow-band Direction-of-Arrival (DOA) estimation is a practical challenge in passive and active sonar applications. While the Conventional Beamformer (CBF) is a robust Maximum Likelihood Estimator (MLE), its precision is inherently constrained by the discrete scanning interval. To overcome this limitation, this paper proposes a novel Model Solution Algorithm (MSA estimator that leverages the exact theoretical beam pattern of the array to resolve the DOA. Unlike the classical Parabolic Interpolation Algorithm (PIA) estimator, which exhibits significant estimation bias due to polynomial approximation errors, the proposed MSA estimator numerically solves the deterministic beam pattern equation to eliminate such model mismatch. Quantitative simulation results demonstrate that the MSA estimator approaches the Cramér-Rao Lower Bound (CRLB) with a stable RMSE of approximately 0.12° under sensor position errors and a frequency-invariant precision of ~0.23°, significantly outperforming the PIA estimator, which suffers from systematic errors reaching 1.1° and 0.75°, respectively. Furthermore, the proposed method exhibits superior noise resilience by extending the operational range to −24 dB, surpassing the −15 dB breakdown threshold of Multiple Signal Classification (MUSIC). Additionally, complexity analysis and geometric evaluations confirm that the method retains a low computational burden suitable for real-time deployment and can be effectively generalized to arbitrary array geometries without accuracy loss.