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DOA Estimation via Distributionally Robust Optimization With Gain-Phase Errors
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DOI：10.1109/LSP.2026.3667071.png)
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Abstract
En 中文
Direction-of-arrival (DOA) estimation is highly sensitive to receiving gain–phase mismatches, which distort the array response and degrade estimation accuracy. To ensure reliable performance without assuming a known error distribution, this letter proposes a distributionally robust optimization (DRO) framework that models receive-chain uncertainty via an ambiguity set explicitly bounding gain and phase errors. Under this construction, we prove an equivalence that reformulates the robust DOA estimator as a tractable convex program. Unlike self-calibration methods, the proposed approach does not impose structural constraints and thus applies to arbitrary linear array configurations. Simulations verify consistent improvements over representative state-of-the-art techniques, while other imperfections (e.g., mutual coupling and sensor position errors) are beyond the scope of this work.
Keywords:
Robust DOA estimation
gain and phase error
arbitrary linear array
distributionally robust optimization