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Enhanced Super-Resolution DOA Estimation via Aperture Extrapolation in RIS Technology for ITS Applications
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DOI：10.1109/TIM.2025.3596985.png)
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Abstract
En 中文
The reconfigurable intelligent surface (RIS) technology offers transformative potential for wireless communications, sensing, and vehicle localization within intelligent transportation systems (ITSs). Accurate direction-of-arrival (DOA) estimation, especially for resolving closely spaced vehicles, is critical for safe autonomous driving. This article introduces aperture extrapolation for RIS-based DOA estimation (APEX-RIS), a high-resolution DOA estimation technique that integrates 2-D linear prediction with 2-D unitary Estimation of signal parameters via rotational invariance technique (ESPRIT) to virtually extend uniform rectangular arrays (URAs). This virtual aperture extrapolation (APEX) significantly enhances the spatial resolution beyond conventional methods without requiring physical array expansion. APEX-RIS performance is validated through extensive simulations across varying signal-to-noise ratios (SNRs), snapshot counts, and angle separations. Results demonstrate substantial improvements in probability of resolution (PR) and root-mean-square error (RMSE), particularly in low-SNR and global positioning system (GPS)-denied environments. The method exhibits superior accuracy in resolving closely spaced sources while maintaining the computational efficiency for real-time ITS applications. While increasing extrapolation gain boosts performance, it also raises computational complexity. APEX-RIS represents a significant advancement in RIS-assisted DOA estimation, supporting safer, more efficient autonomous vehicle (AV) deployment and robust ITS infrastructure.
Keywords:
2-D estimation of signal parameters via rotational invariance technique (ESPRIT)
2-D linear prediction
direction-of-arrival (DOA) estimation
intelligent transportation system (ITS)
probability of resolution (PR)
reconfigurable intelligent surface (RIS)
root-mean-square error (RMSE)
uniform rectangular array (URA)
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