单快照下实现高精度无网格二维波达方向估计
Single-Snapshot Gridless 2D-DoA Estimation for UCAs: A Joint Optimization Approach
- 联合优化流形变换矩阵与源方位角/仰角对
- 无需半定规划，计算高效且结果稳定
- 适合低信噪比、单快照等严苛场景
本文针对单快照条件下均匀圆形阵列（UCA）的无网格二维波达方向（2D-DoA）估计难题，提出一种新框架。传统无网格方法在此场景常因计算开销过大或鲁棒性不足而失效。本文通过将流形变换矩阵与源方位角-仰角对的联合估计纳入统一优化问题，并采用非精确增广拉格朗日法（iALM）求解，完全避免了半定规划。该方法同时兼顾数据保真度与变换鲁棒性，在单快照条件下实现高分辨率、稳定的无网格2D-DoA估计。仿真结果验证了所提iALM框架在复杂阵列信号处理任务中的有效性。
原文摘要 · Abstract (English)
This paper tackles the challenging problem of gridless two-dimensional (2D) direction-of-arrival (DOA) estimation for a uniform circular array (UCA) from a single snapshot of data. Conventional gridless methods often fail in this scenario due to prohibitive computational costs or a lack of robustness. We propose a novel framework that overcomes these limitations by jointly estimating a manifold transformation matrix and the source azimuth-elevation pairs within a single, unified optimization problem. This problem is solved efficiently using an inexact Augmented Lagrangian Method (iALM), which completely circumvents the need for semidefinite programming. By unifying the objectives of data fidelity and transformation robustness, our approach is uniquely suited for the demanding single-snapshot case. Simulation results confirm that the proposed iALM framework provides robust and high-resolution, gridless 2D-DOA estimates, establishing its efficacy for challenging array signal processing applications.
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