Development of Laser Underwater Transmission Model from Maximum Water Depth Perspective
The traditional method for the establishment of the green laser underwater transmission model is purely based on the laser transmission mechanism in waterbodies, while neglecting a few exterior conditions. This paper proposes a novel method to establish the underwater transmission model from a maxim...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/12/1982 |
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| Summary: | The traditional method for the establishment of the green laser underwater transmission model is purely based on the laser transmission mechanism in waterbodies, while neglecting a few exterior conditions. This paper proposes a novel method to establish the underwater transmission model from a maximum measurement depth perspective by refining the dynamic relationship between the effective received power <i>P<sub>A</sub></i> and the background noise power <i>P<sub>B</sub></i>. Different from the traditional empirical model of fixed <i>P<sub>A</sub>/P<sub>B</sub></i>, this method combines the sensor, flight, and environmental parameters of airborne LiDAR (ALB) to achieve the dynamic calibration of <i>P<sub>A</sub></i> and <i>P<sub>B</sub></i>. In particular, the empirical relationship between the maximum underwater measurement depth and the laser attenuation coefficient, coupled parameters, etc., is considered. The established model is verified by different types of experiments. The experimental results discovered that the errors are approximately 0.86 m and 1.28, under the same water conditions, when compared to the existing models. The validation experiments demonstrated that the errors for the maximum depth prediction were 0.38 m (indoor tank), 1.58 m (indoor swimming pool), 0.44 m (Li River, Guangxi), and 1.20 m (Beibu Gulf, Pacific Ocean). The experimental results demonstrated that the established model enables us to widely predict the maximum water depth measurable using an airborne LiDAR under different environmental conditions. |
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| ISSN: | 2072-4292 |