An Enhanced Three-Dimensional Wind Retrieval Method Based on Genetic Algorithm-Particle Swarm Optimization for Coherent Doppler Wind Lidar DOI Creative Commons
Xu Zhang,

Xianqing Zang,

Yuxuan Sang

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(9), P. 1616 - 1616

Published: May 2, 2025

In this paper, a wind retrieval method based on genetic algorithm-particle swarm optimization (GA-PSO) for the coherent Doppler lidar (CDWL) is proposed. The algorithm incorporates an advanced framework that considers field spatial continuity, simultaneously enhancing accuracy and computational efficiency. Comprehensive validations of GA-PSO are conducted using 1.5 μm all-fiber CDWL through ground-based airborne experiments. experiments, extends detection range by 20%~30% compared with traditional methods. validation against meteorological tower data demonstrates excellent agreement, mean deviations better than 0.27 m/s horizontal speed 3.07° direction corresponding RMSE values 0.36 6.04°, respectively. During high-altitude experiments at 5.5 km, recovers up to 31% more information algorithms, demonstrating exceptional performance in low signal-to-noise ratio (SNR) conditions. Both simulation analysis demonstrate achieves processing speeds comparable real-time methods, establishing its suitability real-time, three-dimensional applications.

Language: Английский

An Enhanced Three-Dimensional Wind Retrieval Method Based on Genetic Algorithm-Particle Swarm Optimization for Coherent Doppler Wind Lidar DOI Creative Commons
Xu Zhang,

Xianqing Zang,

Yuxuan Sang

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(9), P. 1616 - 1616

Published: May 2, 2025

In this paper, a wind retrieval method based on genetic algorithm-particle swarm optimization (GA-PSO) for the coherent Doppler lidar (CDWL) is proposed. The algorithm incorporates an advanced framework that considers field spatial continuity, simultaneously enhancing accuracy and computational efficiency. Comprehensive validations of GA-PSO are conducted using 1.5 μm all-fiber CDWL through ground-based airborne experiments. experiments, extends detection range by 20%~30% compared with traditional methods. validation against meteorological tower data demonstrates excellent agreement, mean deviations better than 0.27 m/s horizontal speed 3.07° direction corresponding RMSE values 0.36 6.04°, respectively. During high-altitude experiments at 5.5 km, recovers up to 31% more information algorithms, demonstrating exceptional performance in low signal-to-noise ratio (SNR) conditions. Both simulation analysis demonstrate achieves processing speeds comparable real-time methods, establishing its suitability real-time, three-dimensional applications.

Language: Английский

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