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Structural-Guided Weighted Deconvolution for High-resolution DOA Estimation
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DOI：10.1109/lsp.2026.3744292.png)
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Abstract
En 中文
Conventional beamforming (CBF) suffers from broad mainlobes, sidelobe leakage, and background fluctuations in low-frequency acoustic detection, which limits the resolution of closely spaced sources. This letter proposes a structure-guided weighted deconvolution method for high-resolution direction-of-arrival (DOA) estimation. A positive direction-dependent structural weight is constructed from the normalized CBF spectrum by exploiting amplitude concentration and symmetric-gradient information, thereby emphasizing candidate source-related angular structures and improving the peak-to-valley contrast before deconvolution. The weighting parameters are determined offline through Bayesian optimization and then fixed for independent testing. The optimized weight generates a structurally refined CBF spectrum while keeping the steering-manifold-based point spread function (PSF) matrix unchanged, allowing the weighted spectrum to be used with different PSF-based deconvolution solvers. Weighted DAMAS and weighted Richardson–Lucy (RL) deconvolution are developed under this framework. Simulation results show that the proposed methods achieve higher resolution probability while maintaining accurate DOA estimation for closely spaced sources under low-SNR conditions.
Keywords:
Direction-of-arrival estimation
deconvolution beamforming
structural prior
weighted deconvolution
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