Detection of Air Turbulence Using a Spectral Fitting Method for an Airborne Doppler LIDAR

Abstract

Air turbulence has become a major cause of significant injuries and aircraft damages. We are pursuing the research and development of a practical airborne Doppler LIDAR that will detect air turbulence ahead of an aircraft in-flight and give advanced warning to pilots. Although a larger measurement range could be achieved by using higher powered laser, it implies larger and heavier devices which are not favorable for airborne applications. We use a wind velocity width to detect air turbulence and introduce a spectral fitting method which reduces measurement errors of the wind velocity width and extends the measurement range. This paper describes the effect of the detection of air turbulence using the wind velocity width estimated by the spectral fitting method.

Filtering Algorithm of Airborne Doppler Lidar Measurements for Improved Wind Estimation

“…Concerning the processes to obtain wind velocity, standard deviation and SNR described above, as well as the appearance of the spectrum at each range-bin, please also refer to Asahara et al 9,10) The detection of a spectrum peak is critically important to obtain correct wind velocity. The peak detection from spectrum data fails in distant measurement ranges because the backscattered signal level becomes smaller than the measured noise level.…”