为得到更为精细的三维重构, 提出一种基于信赖域法高斯拟合的峰值探测法, 对每帧图像单时间通道的回波进行高斯建模, 建模结果可有效减小噪声干扰, 具有唯一峰值, 该结果作为新的回波波形, 再对其进行峰值探测, 并基于空中目标实验数据对本文方法进行验证.实验结果表明, 基于高斯拟合的峰值探测法可将特征数据的提取误差降至10%以内; 利用该方法提取特征数据进行目标三维重构, 可实现探测深度方向上最小30 cm的空间分辨力, 提高了条纹管激光雷达的三维成像精度.

In order to get a more precise 3-D reconstruction, a peak detection method based on Gaussian fitting of trust region has been proposed in this work. Gaussian modeling is performed on the returned wave of single time channel of each frame, then the modeling result which can effectively reduce the noise interference and possesses a unique peak could be taken as the new returned waveform, lastly extracting its feature data by peak detection. The experimental data of aerial target is for verifying this method. This work concludes that the peak detection method based on Gaussian fitting reduces the extraction error of the feature data to less than 10%; ultilizing this method to extract the feature data and reconstruct the target makes it possible to realize the spatial resolution with a minimum 30 cm in the depth direction, and improve the 3-D imaging accuracy of the Streak tube imaging lidar concurrently.