Chinese Journal of Lasers, Volume. 46, Issue 10, 1010001(2019)
Method for Solving Echo Time of Pulse Laser Ranging Based on Deep Learning
Fig. 2. Comparison of raw signal waveform and digitized signal waveform. (a) Saturated signal; (b) unsaturated signal
Fig. 3. Signal waveforms from lidar. (a) Main signal and echo signal; (b) main signal detail; (c)-(i) echo signal details
Fig. 4. Sample echoes obtained by theoretical simulation calculation. (a) Ideal echo; (b) small signal with large noise; (c) saturated signal with large noise; (d) small asymmetry; (e) large asymmetry; (f) very small signal
Fig. 6. Trends of classification accuracy and loss in training. (a) Classification accuracy versus training batch; (b) classification loss versus training batch; (c) classification accuracy versus training epoch; (d) classification loss versus training epoch
Fig. 7. Echo signal parameter distributions. (a) Signal amplitude histogram; (b) signal width histogram
Fig. 10. Plane fitting residual distribution histograms. (a) Gaussian fitting method; (b) deep learning method
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Shanjiang Hu, Yan He, Jiayong Yu, Deliang Lü, Chunhe Hou, Weibiao Chen. Method for Solving Echo Time of Pulse Laser Ranging Based on Deep Learning[J]. Chinese Journal of Lasers, 2019, 46(10): 1010001
Category: remote sensing and sensor
Received: Apr. 3, 2019
Accepted: May. 21, 2019
Published Online: Oct. 25, 2019
The Author Email: Chen Weibiao (wbchen@mail.shcnc.ac.cn)