Remote Sensing Applications and Decision Support

Horizontal wind velocity retrieval using a Levenberg–Marquardt algorithm for an airborne wind lidar

[+] Author Affiliations
Jinshan Zhu

Shandong University of Science and Technology, College of Geomatics, No. 579 Qianwangang Road, Qingdao 266590, China

Key Laboratory of Surveying and Mapping Technology on Island and Reef, National Administration of Surveying, Mapping and Geoinformation of China, No. 579 Qianwangang Road, Qingdao 266590, China

Zhigang Li

Ludong University, School of Physics and Optoelectronic Engineering, No. 186 Middle Hongqi Road, Yantai 264025, China

Zhishen Liu

Ocean University of China, Ocean Remote Sensing Institute, No. 5 Yushan Road, Qingdao 266003, China

J. Appl. Remote Sens. 10(2), 026009 (Apr 25, 2016). doi:10.1117/1.JRS.10.026009
History: Received September 9, 2015; Accepted March 25, 2016
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Abstract.  We established a model for an airborne wind lidar. Numerical optimization algorithms should be used to solve this nonlinear model. We designed a Levenberg–Marquardt (L–M) algorithm and tested it with the modeled data. The retrieved velocity and the true velocity agree very well, and the adjusted R2 is 0.99947. We have carried out an airborne coherent wind lidar experiment in January 2015, and we used the model and the L–M algorithm to process the wind lidar experiment data, and compared the retrieved results with the radiosonde wind profile. The consistency is very good, especially at an altitude above 1.8 km. We may speculate that when the atmosphere flows are not so dramatic, the lidar and the radiosonde measurements are strictly synchronous, it is possible to retrieve horizontal wind speeds and directions consistently with the radiosonde using our wind lidar model and the L–M algorithm.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Jinshan Zhu ; Zhigang Li and Zhishen Liu
"Horizontal wind velocity retrieval using a Levenberg–Marquardt algorithm for an airborne wind lidar", J. Appl. Remote Sens. 10(2), 026009 (Apr 25, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.026009


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