Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction

Brady R. Bickel; Eric R. Rotthoff; Gage S. Walters; Timothy J. Kane; Shane D. Mayor

doi:10.1117/12.2223932

20 April 2016 Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction

Brady R. Bickel, Eric R. Rotthoff, Gage S. Walters, Timothy J. Kane, Shane D. Mayor

Proceedings Volume 9845, Optical Pattern Recognition XXVII; 98450A (2016) https://doi.org/10.1117/12.2223932
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

The tracking of winds and atmospheric features has many applications, from predicting and analyzing weather patterns in the upper and lower atmosphere to monitoring air movement from pig and chicken farms. Doppler LIDAR systems exist to quantify the underlying wind speeds, but cost of these systems can sometimes be relatively high, and processing limitations exist. The alternative is using an incoherent LIDAR system to analyze aerosol backscatter. Improving the detection and analysis of wind information from aerosol backscatter LIDAR systems will allow for the adoption of these relatively low cost instruments in environments where the size, complexity, and cost of other options are prohibitive. Using data from a simple aerosol backscatter LIDAR system, we attempt to extend the processing capabilities by calculating wind vectors through image correlation techniques to improve the detection of wind features.

Citation Download Citation

Brady R. Bickel, Eric R. Rotthoff, Gage S. Walters, Timothy J. Kane, and Shane D. Mayor "Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction", Proc. SPIE 9845, Optical Pattern Recognition XXVII, 98450A (20 April 2016); https://doi.org/10.1117/12.2223932

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