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Radiometric Calibration of an Inexpensive LED-Based Lidar Sensor

机译:廉价的基于LED的LIDAR传感器的辐射校准

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摘要

Radiometric calibration of laser-based, topographic lidar sensors that measure range via time of flight or phase difference is well established. However, inexpensive, short-range lidar sensors that utilize non-traditional ranging techniques, such as indirect time of flight, may report radiometric quantities that are not appropriate for existing calibration methods. One such lidar sensor is the TeraRanger Evo 60 m by Terabee, whose reported amplitude measurements do not vary smoothly with the amount of return signal power. We investigate the performance of a new radiometric calibration model, one based on a neural network, applied to the Evo 60 m. The proposed model is found to perform similarly to those applied to traditional lidar sensors, with root mean square errors in predicted target reflectance of no more than ±6% for non-specular surfaces. The radiometric calibration model provides a generic approach that may be applicable to other low-cost lidar sensors that report return signal amplitudes that are not smoothly proportional to target range and reflectance.
机译:基于激光的辐射校准,通过飞行时间或相位差的时间来测量范围的地形激光雷达传感器。然而,利用非传统测距技术的廉价,短距离的激光雷达传感器,例如间接飞行时间,可能报告不适合现有校准方法的辐射数量。一个这样的激光器传感器是Teraranger Evo 60米,其报道的幅度测量不会随着返回信号功率的量而变化。我们研究了新的辐射校准模型的性能,一个基于神经网络,施加到EVO 60米。发现所提出的模型与应用于传统激光雷达传感器的那些模型类似,在预测目标反射率为非镜面表面的均方根误差不超过±6%。辐射校准模型提供了一种通用方法,可以适用于其他低成本的LIDAR传感器,其报告与目标范围和反射率不平滑成比例的返回信号幅度。

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