Li Rui, Yang Jianchao, Dai Zheng, Lu Xingyu, Tan Ke, Su Weimin
School of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.
Sensors (Basel). 2024 Sep 13;24(18):5936. doi: 10.3390/s24185936.
In recent years, one-bit quantization has attracted widespread attention in the field of direction-of-arrival (DOA) estimation as a low-cost and low-power solution. Many researchers have proposed various estimation algorithms for one-bit DOA estimation, among which atomic norm minimization algorithms exhibit particularly attractive performance as gridless estimation algorithms. However, current one-bit DOA algorithms with atomic norm minimization typically rely on approximating the trace function, which is not the optimal approximation and introduces errors, along with resolution limitations. To date, there have been few studies on how to enhance resolution under the framework of one-bit DOA estimation. This paper aims to improve the resolution constraints of one-bit DOA estimation. The log-det heuristic is applied to approximate and solve the atomic norm minimization problem. In particular, a reweighted binary atomic norm minimization with noise assumption constraints is proposed to achieve high-resolution and robust one-bit DOA estimation. Finally, the alternating direction method of multipliers algorithm is employed to solve the established optimization problem. Simulations are conducted to demonstrate that the proposed algorithm can effectively enhance the resolution.
近年来,一位量化作为一种低成本、低功耗的解决方案,在到达方向(DOA)估计领域引起了广泛关注。许多研究人员针对一位DOA估计提出了各种估计算法,其中原子范数最小化算法作为无网格估计算法表现出特别有吸引力的性能。然而,当前具有原子范数最小化的一位DOA算法通常依赖于对迹函数的近似,这不是最优近似,会引入误差,同时存在分辨率限制。迄今为止,关于如何在一位DOA估计框架下提高分辨率的研究很少。本文旨在改善一位DOA估计的分辨率约束。应用对数行列式启发式方法来近似和解决原子范数最小化问题。特别地,提出了一种具有噪声假设约束的加权二进制原子范数最小化方法,以实现高分辨率和鲁棒的一位DOA估计。最后,采用交替方向乘子算法来解决所建立的优化问题。进行了仿真以证明所提出的算法可以有效地提高分辨率。