被动长波红外高光谱测距：透过率提取与距离对齐

中文摘要 AI 辅助

被动长波红外（LWIR）高光谱测距利用热辐射中通过大气吸收特征来实现低光照和夜间场景下的距离估计。温度、发射率和距离的联合估计计算成本高昂。参考距离联合反演还使用距离不变的等效衰减系数，这可能导致测距偏差。我们提出透过率提取与距离对齐（TEDA），将距离估计与温度-发射率反演解耦。在第一阶段，基线估计器采用对已知吸收方向不变的数据保真项，产生两个针对缓慢变化热连续谱的闭式平滑分支。观测导出的门控结合两个分支，并在对数域中减去混合基线以恢复大气透过率。第二阶段通过将恢复的透过率与针对每个候选距离重新计算的传感器域透过率模型进行匹配来估计距离。蒙特卡洛模拟表明，TEDA有效减少了由距离不变衰减系数近似引起的测距偏差。在实测场景中，TEDA的平均距离估计在两个评估补丁中均比参考距离联合反演更接近LiDAR中位数。TEDA处理完整的$256\ imes256$感兴趣区域需8.19秒，而参考距离联合反演需159.47秒，加速约20倍。

英文摘要

Passive long-wave infrared (LWIR) hyperspectral ranging enables distance estimation in low-light and nighttime scenes by exploiting atmospheric absorption features in thermal radiance received through the atmosphere.Joint estimation of temperature, emissivity, and distance is computationally expensive. Reference-range joint inversion also uses a distance-invariant effective attenuation coefficient, which can bias range estimates.We introduce transmittance extraction and distance alignment (TEDA), which decouples range estimation from temperature--emissivity inversion. In the first stage, a baseline estimator with a data-fidelity term invariant to the known absorption direction yields two closed-form smoothing branches for the slowly varying thermal continuum. An observation-derived gate combines the branches, and subtracting the blended baseline in the log domain recovers atmospheric transmittance. The second stage estimates range by matching the recovered transmittance to sensor-domain transmittance models recomputed for each candidate distance. Monte Carlo simulations show that TEDA effectively reduces the ranging bias caused by the distance-invariant attenuation coefficient approximation. In a measured scene, TEDA's mean range estimates are closer to the LiDAR medians than those of reference-range joint inversion in both evaluated patches. TEDA processes a complete $256\times256$ region of interest in 8.19~s versus 159.47~s for reference-range joint inversion, an approximately 20-fold speedup.

发表机构

• National University of Defense Technology（国防科技大学）
• Hunan University（湖南大学）

机构由 AI 辅助整理，请以论文原文为准。