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Coastal high-frequency (HF) radars are widely used in operational oceanography to provide continuous, wide-area observations of surface currents, waves, and maritime targets. Operating in the 3–30 MHz frequency band, HF radars can achieve observation ranges exceeding 200 km, making them essential tools for coastal monitoring and exclusive economic zone (EEZ) surveillance.Accurate target positioning in HF radar observations critically depends on the reliability of direction-of-arrival (DOA) estimation. Angular errors introduce significant uncertainty in target localization and propagate into radial velocity retrievals and tracking consistency, particularly under low signal-to-noise ratio (SNR) conditions commonly encountered in real coastal environments. Conventional Fourier beamforming suffers from high sidelobe levels that lead to angular ambiguity, while the Capon beamformer is highly sensitive to covariance estimation and often becomes unstable at low SNR.This study evaluates a norm-constrained Capon (NC-Capon) beamforming approach as a strategy to enhance the robustness of spatial filtering in operational HF radar observations. By combining a norm constraint with diagonal loading, NC-Capon beamforming stabilizes spatial filtering and suppresses sidelobe leakage, resulting in more robust DOA estimation under noisy conditions. Field experiments were conducted using two operational coastal HF radar stations in northern Taiwan. A dedicated experimental vessel followed controlled trajectories at nearshore ranges of approximately 1–3 km, while a fixed offshore unloading platform served as a stable reference target. Radar-derived target positions obtained using Fourier, Capon, and NC-Capon beamforming were systematically compared with Automatic Identification System (AIS) data to quantify angular uncertainty under different azimuthal conditions and its impact on target localization results.Results show a slight discrepancy between radar measurements and AIS target locations, particularly under low SNR conditions and at large azimuthal angles. Moreover, systematic bias occurs in one of the coastal radar observations, which is suspected to be related to the configuration of the radar system. These findings underscore the importance of enhancing spatial filtering robustness to improve the reliability of target localization using coastal HF radar.