面向低密度等离子体诊断的夏克-哈特曼波前传感器高精度质心定位方法

High-precision centroid localization method for Shack–Hartmann wavefront sensors in low-density plasma diagnosis

  • 摘要: 针对脉冲功率装置负载区低密度等离子体电子密度诊断需求,系统常采用长焦距夏克-哈特曼波前传感器以提高微弱相位偏折信号的探测能力,但长焦距条件下系统成像失配问题更为突出,易导致光斑质心越界、子孔径误匹配及串扰,进而造成质心定位失效并限制电子密度反演灵敏度。为此,本文提出一种基于目标检测的夏克-哈特曼波前传感器高精度质心定位方法。该方法首先利用全图特征估计实现系统全局偏移校正,随后结合目标检测网络与连续可微质心算子,实现光斑质心的亚像素级坐标回归。为验证模型性能,本文通过物理建模与激光成像实验分别构建了包含不同复杂度样本的模拟数据集与实测数据集用于网络训练与测试。结果表明,该方法在数据集上的平均质心估计误差均低于0.26像素,最低可达0.158 8像素,定位精度较传统阈值质心法提升2.8倍以上;消融实验进一步表明,各功能模块能够有效抑制复合噪声与越界干扰,使模拟与实测数据上的平均质心估计误差分别控制在0.207 3像素和0.180 0像素。该方法应用于金属丝电爆炸晕层低密度等离子体诊断实验后,成功反演得到二维电子密度分布,并使系统的线积分电子密度灵敏度提升至1×1015 cm−2,有效扩展了低密度边缘区域的探测能力。

     

    Abstract:
    Background For electron density diagnostics of low-density plasma in the load region of pulsed-power devices, Shack–Hartmann wavefront sensors with long-focal-length microlens arrays are commonly employed to enhance the detection sensitivity to weak phase-deflection signals. However, long-focal-length configurations make system imaging mismatch more pronounced. This may cause centroid boundary crossing, sub-aperture mismatch, and crosstalk, thereby degrading centroid localization accuracy and limiting the sensitivity of electron density inversion.
    Purpose This study proposes a high-precision centroid localization method for Shack–Hartmann wavefront sensors based on object detection, aiming to achieve robust and accurate centroid coordinate regression under strong noise and large spot displacement conditions.
    Methods A global offset correction mechanism based on full-field feature estimation was first established to correct the global spot-array offset caused by system imaging mismatch. Subsequently, an object detection framework performing localized sub-aperture detection was integrated with a continuous differentiable centroid operator to achieve sub-pixel centroid coordinate regression. To evaluate the proposed method, simulated and experimental datasets with varying complexity levels were constructed through physical modeling and laser imaging experiments for network training and validation.
    Results The proposed method achieved mean centroid estimation errors below 0.26 pixels across all simulated and experimental datasets, with the minimum mean centroid estimation error reaching 0.158 8 pixels. Compared with the traditional threshold center-of-gravity method, the localization accuracy was improved by more than 2.8-fold. Ablation experiments further demonstrated that the introduced localized detection and differentiable centroid modules effectively suppressed compound noise and cross-boundary interference, reducing the mean centroid estimation errors on simulated and experimental datasets to 0.207 3 pixels and 0.180 0 pixels, respectively. When applied to low-density plasma diagnostics in electrical wire explosion corona experiments, the proposed method successfully reconstructed two-dimensional electron density distributions and improved the line-integrated electron density sensitivity of the system to 1×1015 cm−2.
    Conclusions The proposed method improves the localization accuracy and robustness of long-focal-length Shack–Hartmann wavefront sensor systems under strong noise and large displacement conditions. It significantly enhances the diagnostic capability for low-density edge plasma and provides a reliable approach for high-sensitivity electron density measurements in pulsed-power experiments.

     

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