DOA Estimation from One-Bit Magnitude-Only Measurements via Sign-Consistency Optimization
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Abstract (arXiv)
The direction-of-arrival (DOA) estimation problem using one-bit quantized magnitude-only measurements is studied, where magnitude-only measurements offer robustness against phase errors, thereby avoiding the need for array calibration, while one-bit quantization significantly reduces hardware cost and system complexity. As their direct combination results in meaningless constant measurements, we formulate a sign-consistency optimization problem using a smooth logistic surrogate with ell_2,1-norm regularization to promote joint sparsity. To solve this problem, a proximal-gradient algorithm is developed with guaranteed convergence to a critical point. Numerical results demonstrate that the proposed method achieves accuracy comparable to coherent one-bit baselines under ideal conditions, while maintaining robust performance under severe phase errors that substantially impair coherent methods.
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References · 4
- 2014Phase Retrieval via Wirtinger Flow: Theory and Algorithmscited by 125
- 2022One-Bit Phase Retrieval: More Samples Means Less Complexity?cited by 6
- 2019One-Bit MUSICcited by 5
- 2019A New Atomic Norm for DOA Estimation With Gain-Phase Errorscited by 2
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- 2023One-Bit-Aided Modulo Sampling for DOA Estimation
- 2025Model-Based Learning for DOA Estimation with One-Bit Single-Snapshot Sparse Arrays
- 2026Low-Complexity Gridless Single-Snapshot DoA Estimation via Truncated Hankel Newton-MUSIC ↗
- 2024Deep Learning-Enabled One-Bit DoA Estimation
- 2024Enhancing Off-Grid One-Bit DOA Estimation with Learning-Based Sparse Bayesian Approach for Non-Uniform Sparse Array
- 2023TransMUSIC: A Transformer-Aided Subspace Method for DOA Estimation with Low-Resolution ADCs
- 2024CRB Analysis for Mixed-ADC Based DOA Estimation
- 2023One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility