发表机构
Hubei Longzhong Laboratory; National Engineering Research Center of Fiber Optic Sensing Technology and Networks, Wuhan University of Technology; School of Information Engineering, Wuhan University of Technology; State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology（湖北隆中实验室; 武汉理工大学光纤传感技术国家工程研究中心; 武汉理工大学信息工程学院; 武汉理工大学材料合成与加工先进技术国家重点实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对水下声学网络柔性阵列的几何变形问题，提出BOGE策略，结合贝叶斯优化与物理信息模型，在SWellEx-96数据集及湖试中均表现出更优的几何校准性能。
AI 中文摘要
柔性传感阵列广泛应用于水下声学网络，但会受不可预测的几何变形抑制。现有阵列形状自校准方法常单独估计各阵元位置，导致长阵列的优化问题维度很高。针对该问题，本文提出一种贝叶斯优化辅助的几何估计（BOGE）策略，其采用分层优化过程与物理信息参数模型来校正阵列几何。BOGE将阵列形状自校准建模为优化问题，其中候选几何由噪声子空间残差评估。我们执行贝叶斯优化以配置物理信息参数模型，随后通过数值优化细化所选几何。实验结果表明，在宽噪声水平范围内，BOGE的几何均方根误差（RMSE）低于基准方法；在公开SWellEx-96数据集上，BOGE在166赫兹时的几何RMSE为0.659米；湖试进一步显示，BOGE的固定声源定位与移动目标跟踪性能可与对比方法相媲美。
英文摘要
Flexible sensing arrays are commonly used in underwater acoustic networks, but suppressed by unpredictable geometric deformations. Existing array shape self-calibration methods often estimate individual element positions separately, leading to a high dimensional optimization problem over long arrays. To address this problem, this paper proposes a Bayesian Optimization-assisted Geometry Estimation (BOGE) strategy operating with a hierarchical optimization process and a physics-informed parametric model for array geometry correction. BOGE formulates array shape self-calibration as an optimization problem, where candidate geometries are evaluated by the noise subspace residual. We perform Bayesian optimization to configure the physics-informed parametric model and then refine the selected geometry through numerical optimization. Empirical results show that BOGE achieves lower mean geometric root mean square error (RMSE) than the benchmark methods across a wide range of noise levels. On the public SWellEx-96 dataset, BOGE achieves a geometric RMSE of $0.659$ meters at $166$ Hz. A lake trial further shows that BOGE provides fixed source localization and moving target tracking performance comparable to the comparison methods.
Comments13 pages, 12 figures, submitted to an IEEE journal
