Improved waveform reconstruction and parameter accuracy retrieval for hyperspectral lidar data

Ilinca Julian; Kaasalainen Sanna; Malkamaki Tuomo; Hakala Teemu

摘要

In this paper, we aim to provide a solution for choosing an optimized digitization frequency for full-waveform reconstruction of narrow FWHM laser pulses to improve the performance accuracy required for recognition and characterization of a wide range of materials with distinctive reflectance features. This type of analysis, for the first time, to the best of our knowledge, gives an assessment of the absolute accuracy with which waveform peak intensity and spatiotemporal peak location can be detected using multi- or hyperspectral lidar instrumentation. Different full-waveform reconstruction algorithms with varying characteristics are implemented on simulated Gaussian laser pulse data sets obtained with varying sampling frequencies ranging between 1 GHz and 5 GHz. The data sets are analyzed, and an optimized digitization frequency is found based on observation of algorithmic parameter retrieval accuracy. The accuracy of the full-waveform retrieval in relation to the type of algorithm used and its robustness related to the digitization frequency are also discussed. We find that optimizing the algorithmic processing of multi-wavelength sampled radiance data recorded by multispectral and hyperspectral lidar instruments significantly improves the accuracy of reflectance retrieval and target material characterization capabilities of the instrument. (C) 2019 Optical Society of America

机译：在本文中，我们的目的是提供一种选择用于为窄FWHM激光脉冲的全波形重建选择优化的数字化频率的解决方案，以提高具有独特反射率特征的各种材料所需的性能精度。这种类型的分析是，首次据我们所知，可以使用多或高光谱激光仪仪器检测波形峰强度和时空峰值位置的绝对精度评估。具有不同特性的不同的全波形重建算法在以1GHz和5GHz之间的不同采样频率获得的模拟高斯激光脉冲数据集实现。分析数据集，基于对算法参数检索精度的观察找到优化的数字化频率。还讨论了与与数字化频率相关的算法类型相关的全波形检索的准确性。我们发现，优化由多光谱和超光线激光乐仪记录的多波长采样辐射数据的算法处理显着提高了仪器反射率检索和目标材料表征能力的准确性。（c）2019年光学学会

Improved waveform reconstruction and parameter accuracy retrieval for hyperspectral lidar data

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