Direction Of Arrival (DOA) estimation in Frequency Modulated Continuous Wave (FMCW) radar systems is critical for structural health monitoring, but is often compromised by phase-corrupted snapshots caused by clock jitter or Phase-Locked Loop (PLL) drift. Existing robust DOA methods suffer from high computational complexity or sensitivity to outliers, limiting their real-time applicability. In this paper, we propose the first decentralized Trust Game (TG) mechanism for snapshot selection, which leverages inter-snapshot coherence to identify and exclude anomalies with provable complexity bounds. Combined with a Toeplitz-accelerated reiterative super-resolution estimator that exploits uniform linear array structure for near-linear computational cost, our approach achieves robust and high-resolution DOA estimation. Throughout this work, the anomalous snapshots are not caused by target motion but by hardware-induced data corruption (e.g., clock jitter and PLL drift) in an otherwise static scene. Experimental results demonstrate that the proposed method outperforms state-of-the-art techniques in both outlier robustness and execution speed, offering a practical solution for real-time monitoring under hardware constraints.
Cheng et al. (Sun,) studied this question.