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Wind retrieval for genetic algorithm-based coherent Doppler wind lidar employing airborne platform

Applied Physics B: Lasers and Optics, ISSN: 0946-2171, Vol: 129, Issue: 3
2023
  • 5
    Citations
  • 0
    Usage
  • 0
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    5
  • Mentions
    1
    • News Mentions
      1
      • 1

Most Recent News

New Mathematics Findings Has Been Reported by Investigators at Chinese Academy of Sciences (Wind Retrieval for Genetic Algorithm-based Coherent Doppler Wind Lidar Employing Airborne Platform)

2023 MAR 21 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Investigators publish new report on Mathematics. According to news

Article Description

The method of the maximum function of accumulated spectra based on the genetic algorithm is applied for the first time to three-dimensional (3D) wind field retrieval by Doppler wind lidar on an airborne platform. The algorithm can obtain the 3D wind field directly from the origin spectra of different directions regardless of the radial wind velocity inversion accuracy. To validate the reliability of this algorithm for application on an airborne platform, a 1.54-μm all-fiber airborne pulsed coherent Doppler lidar was installed on an aircraft to conduct field experiments. The measured wind fields were compared with those obtained through the sounding balloon and the ground-based lidar. For the sounding balloon, the average errors of wind speed and the wind direction are 0.539 m/s and 5.12°; while for the ground-based lidar, the average errors are 0.504 m/s and 4.18°, respectively. In addition, the two inversion results are in good consistency by comparison with the least square method. The genetic algorithm shows higher accuracy even though the detectability is low. The proposed algorithm, as an efficient and accurate calculation model, would be a good tool in the airborne platform for wind retrieval.

Bibliographic Details

Yuan Zhao; Bo Dai; Lucheng Yuan; Xiaopeng Zhu; Jiqiao Liu; Xiaolei Zhu; Weibiao Chen; Chunhui Fan; Weigang Xiao

Springer Science and Business Media LLC

Physics and Astronomy

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