Opto-Electronic Engineering, Volume. 52, Issue 6, 250066(2025)
Simulation system for measuring multiple environmental elements in the ocean based on direct scattering spectrum
Figures & Tables(25)
![Imaging principle of spectral measurement method based on Fizeau interferometer and multi-channel PMT[15]](/Images/icon/loading.gif){kind=icon}
Fig. 3. Imaging principle of spectral measurement method based on Fizeau interferometer and multi-channel PMT[15]
Fig. 6. Simulation flowchart of optical receiving and spectral measurement system
Fig. 9. Software interface design. (a) System display interface; (b) System working interface
Fig. 10. Spectral simulation results. (a) Laser spectrum; (b) Scattering spectra; (c) Laser broadening spectra; (d) Laser induced scattering spectra; (e) Fizeau frequency discrimination spectra; (f) PMT receiving spectra
Fig. 11. Error distribution of 1000 repeated measurements. (a) Temperature measurement errors distribution; (b) Distribution of measurement errors in salinity
Fig. 13. Detection accuracy results. (a) Multi temperature simulation results; (b) Multi salinity simulation results
Table 1. Parameter design of laser emission system
View tableView in ArticleTable 1. Parameter design of laser emission system
Parameter name Typical value Incident wavelength/nm 532 Laser energy/J 0.02 Pulse width/GHz 0.1 Frequency range/GHz 12
Table 2. Parameter design of seawater channel system
View tableView in ArticleTable 2. Parameter design of seawater channel system
Parameter name Typical value Theoretical temperature/℃ 25 (0~30) Water attenuation coefficient 0.08 Backscatter coefficient 0.00024 Scattering energy ratio 0.04 Theoretical salinity/‰ 15 (0~35) Water reflectance 1.33 Underwater detection depth/m 27 Underwater noise coefficient 2
Table 3. Parameter design of optical reception and spectral measurement system
View tableView in ArticleTable 3. Parameter design of optical reception and spectral measurement system
Parameter name Typical value Integral number 1000 Receiver height/m 100 Fiber efficiency 0.4 Fizeau wedge angle/rad 1.6835×10−5 Medium refractive index 1 Channel width/m 0.0008 Telescope radius/m 0.05 Detection efficiency 0.13 Plate length/mm 0.006 Planar reflectance 0.9 Channel gap/m 0.0002 Dark current noise/W 10−10
Table 4. Parameter design of signal processing system
View tableView in ArticleTable 4. Parameter design of signal processing system
Parameter name Typical value Initial conditions/GHz 7.670, 0.617, and 0.150 Minimum feature value/GHz 7.2, 0.2, and 0.1 Maximum feature value/GHz 7.8, 0.8, and 0.3 Tolerance 1×10−20
Table 5. Experimental results of spectral line feature extraction
View tableView in ArticleTable 5. Experimental results of spectral line feature extraction
Spectral parameter Measurement value Theoretical value Error Brillouin linewidth/GHz 0.7273 0.7321 −0.0048 Brillouin shift/GHz 7.5305 7.5318 −0.0013 Rayleigh linewidth/GHz 0.2365 0.1500 0.0865
Table 6. Model retrieval results
View tableView in ArticleTable 6. Model retrieval results
Environmental factor Measurement value Theoretical value Error Temperature/℃ 15.1273 15 0.1273 Salinity/‰ 24.5235 25 −0.4765
Table 7. Analysis results of error distribution
View tableView in ArticleTable 7. Analysis results of error distribution
Error category Confidence level Confidence interval Fitting error Temperature 95% [−0.409, 0.422] 0.041 Salinity 95% [−0.776, 0.857] 0.043
Table 8. Error distribution of temperature and salt measurement results under different integration times
View tableView in ArticleTable 8. Error distribution of temperature and salt measurement results under different integration times
Integral number Error category Confidence level Confidence interval 1 Temperature 95% [−4.561, 4.643] Salinity 95% [−5.332, 5.421] 100 Temperature 95% [−1.331, 1.413] Salinity 95% [−2.112, 2.168] 1000 Temperature 95% [−0.409, 0.422] Salinity 95% [−0.776, 0.857]
Table 9. System parameters of the LiDAR
View tableView in ArticleTable 9. System parameters of the LiDAR
Parameter name Value Temperature/℃ 19.1, 20.8, 24.5, 25.1, and 29.8 Pulse time/ns 7.5 Telescope focus/mm 100 Depth/m 0.36 Repetitive frequency/Hz 100 Laser power/mJ 20 Refractive index/‰ 0.1, 2.1, 6.2, 5.1, and 24.1 Wavelength/nm 532 Optical efficiency/% 17.6 Incident angle/(°) 179.5 PMT array SPCM-02-L16 System efficiency/% 80
Table 10. Comparison between simulation results and real experimental results
View tableView in ArticleTable 10. Comparison between simulation results and real experimental results
Category Actual measurement data Simulation measurement data Relative error Temperature accuracy 0.13 0.12 7.7% Salinity accuracy 0.16 0.15 6.3%
Table 11. Actual experimental conditions for laser remote sensing
View tableView in ArticleTable 11. Actual experimental conditions for laser remote sensing
Parameter name Value Integral number 1000 Pulse time/ns 10 Telescope radius/m 0.05 Height/m 2.45 Repetitive frequency/Hz 100 Laser power/mJ 20 Refractive index 1.33 Wavelength/nm 532 Optical efficiency/% 40 Incident angle/(°) 179 Attenuation coefficient 0.2 System efficiency/% 13
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Mengfan Liang, Sheng Chen, Yuanxin Guo, Yangrui Xu, Kun Liang. Simulation system for measuring multiple environmental elements in the ocean based on direct scattering spectrum[J]. Opto-Electronic Engineering, 2025, 52(6): 250066
Paper Information
Category: Article
Received: Mar. 6, 2025
Accepted: Apr. 30, 2025
Published Online: Sep. 3, 2025
The Author Email: Kun Liang (梁琨)
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