Chinese Journal of Lasers, Volume. 47, Issue 8, 810004(2020)
Wind Vector Estimation of Coherent Doppler Wind Lidar Based on Genetic Algorithm
Figures & Tables(8)
Fig. 1. Spectrograms of 64 scanning positions at low signal-to-noise ratio (SNR) for coherent Doppler wind measurement lidar. (a) Original spectrogram; (b) result of frequency spectrum estimation algorithm (dashed line)
Fig. 2. Population fitness of traditional genetic algorithm and genetic algorithms after different improvements varying with iterations. (a) Traditional genetic algorithm; (b) optimization for initialization scheme; (c) optimization for selection operation; (d) improved genetic algorithm
Fig. 4. Comparison of wind speed and wind direction between coherent Doppler wind lidar and sounding balloons. (a) Comparison of wind speed profiles; (b) comparison of wind direction profiles; (c) comparison of statistical results of wind speed; (d) comparison of statistical results of wind direction
Fig. 5. Comparison of wind profiles obtained by genetic algorithm based frequency spectrum estimation method and least squares method. (a)(e) 2018-08-10T20:55; (b)(f) 2018-08-10T21:22; (c)(g) 2018-08-10T21:41; (d)(h) 2018-08-10T21:49
Table 1. Simulation results
View tableTable 1. Simulation results
Signal-to-noise ratio /dB Parameter Nonlinear least squares method Frequency spectrum estimation method based on genetic algorithm Mean deviation Standard deviation Mean deviation Standard deviation 10 Wind speed /(m·s-1) 0.01 0.23 0.11 0.38 Wind direction /(°) -0.07 1.40 0.29 1.48 5 Wind speed /(m·s-1) 0.10 0.47 -0.01 0.32 Wind direction /(°) 0.43 3.77 -0.07 5.23 4.5 Wind speed /(m·s-1) 0.28 0.40 -0.22 0.41 Wind direction /(°) -0.79 3.47 -0.66 3.11 4 Wind speed /(m·s-1) 0.13 1.12 -0.06 0.38 Wind direction /(°) -31.83 93.11 0.36 4.57 3.5 Wind speed /(m·s-1) 1.17 2.46 -0.04 0.66 Wind direction /(°) -10.81 32.15 -0.40 1.48 3 Wind speed /(m·s-1) 1.42 4.99 -0.40 0.88 Wind direction /(°) -41.54 91.72 0.15 4.00 2 Wind speed /(m·s-1) 4.81 6.30 -0.16 0.95 Wind direction /(°) -147.10 110.13 1.23 5.70 1.5 Wind speed /(m·s-1) 7.39 6.10 -0.40 1.23 Wind direction /(°) -140.41 124.01 -1.87 5.08
Table 2. Results after 1000 times running of traditional genetic algorithm and genetic algorithms after different improvements
View tableTable 2. Results after 1000 times running of traditional genetic algorithm and genetic algorithms after different improvements
Method Number of convergence results Number of achieved high-quality solutions Average iterations of convergence Traditional genetic algorithm 439 102 42.53 Limit range of initial wind speed 575 870 39.73 Update selection operation 989 289 45.84 Improved genetic algorithm 1000 1000 23.82
Table 3. Main parameters of all-fiber coherent Doppler wind lidar system[19]
View tableTable 3. Main parameters of all-fiber coherent Doppler wind lidar system[19]
Parameter Specification Operating wavelength /nm 1540 Pulse energy /μJ 300 Pulse repetition rate /kHz 10 Pulse width /ns 400 Power of LO /mW 0.8 Range gate /m 30 Telescope aperture /mm Ф100 Scanner aperture /mm Ф100 Zenith angle /(°) 20 Intermediate frequency /MHz 160 Sampling rate of AD converter /(Sa·s-1) 1 Resolution of AD converter /bit 10 Number of accumulated pulses 10000
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Yuan Lucheng, Liu Heng, Liu Jiqiao, Zhu Xiaopeng, Hu Guyu, Chen Weibiao. Wind Vector Estimation of Coherent Doppler Wind Lidar Based on Genetic Algorithm[J]. Chinese Journal of Lasers, 2020, 47(8): 810004
Paper Information
Category: remote sensing and sensor
Received: Feb. 27, 2020
Accepted: --
Published Online: Aug. 17, 2020
The Author Email: Jiqiao Liu (liujiqiao@siom.ac.cn)
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