Signal processing wind-lidar performance assessment (NEPTUNE) and synergetic-instrument ABL and WV-retrieval

The research activity deals with the participation of RSLAB in NEPTUNE project and tackles analysis and cross-examination of sea-motion effects in horizontal wind speed, horizontal wind direction, and vertical wind speed when measured from the lidar-instrumented buoy. Towards this aim, two different test campaigns are considered: One at LIM (Lab. Maritime Engineering)/UPC premises in Campus Nord and another at their premises at El Pont del Petroli pier. In both cases two lidars are used, one moving (the “floating” lidar) and non-moving one (the “fixed” lidar). In the first campaign, a lab-based motion-simulation platform is used to emulate pitch-and-roll sea movements while in the second campaign the “floating” lidar is assembled on a provisional buoy 40-m offshore. Different angular, position, and navigation sensors are used to cross-examine wind-retrieved data from the floating lidar against the fixed one (Fig. 1).

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Fig. 1 NEPTUNE project. (Left) Calibration/validation (cal/val) of two Doppler lidars co-located at RSLAB premises (UPC, Campus Nord, Oct. 12, 2012). (Central) Horizontal Wind Speed scatter plot from the cal/val of the two lidars, 1-s resolution. (Right) El Pont del Petroli (PdP) campaign (May 22 to Jul. 12, 2013, WP2 partners: LIM, SWE, IREC, and RSLAB). The “floating” is the lidar buoy (yellow), the “fixed” lidar is on PdP pier on land.


Concerning ABL retrieval, A solution based on a Kalman filter to trace the evolution of the Atmospheric Boundary Layer (ABL) sensed by a ground-based elastic-backscatter tropospheric lidar is studied. The Extended Kalman Filter (EKF) enables to retrieve and track the ABL parameters based on simplified statistics of the ABL dynamics and of the observation noise present in the lidar signal. This adaptive feature permits to analyze atmospheric scenes with low signal-to-noise ratios (SNRs) without the need to resort to long time averages or range-smoothing techniques, as well as to pave the way for future automated detection solutions.


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Time-height plot of the range-corrected attenuated backscatter lidar signal (infrared channel, CL-31) showing time evolution of the ABL. (Magenta) ABL height estimated with a Kalman filter. Source: RSLAB-UMASS in TEC2012-34575 project on multi-spectral lidar observation).