1. Sponsors: National Aeronautics and Space Administration (NASA) NASA Goddard Space Flight Center (GSFC) NASA Goddard Institute for Space Studies (GISS) NASA New York City Research Initiative (NYCRI) National Science Foundation – Research Experience for Undergraduates (NSF-REU) The City College of New York (CCNY) Acknowledgements: Dr. Reginald Blake, Dr. Shakila Merchant, Dr. Reza Khanbilvardi, Dr. Fred Moshary, Shinedu Chukuigwe Contributors: Lowell Brazin, High School Student, Abdul Jalloh, Undergraduate, Tristan Schwartzman, undergraduate, Dr. Mark Arend, Sameh Abdelazim, David Santoro Grant No: ATM-0755686 Future Research Compare our results to locations around New York City Expand system to be mobile and multi-directional Fully analyze wind speed and aerosol density References Abstract Coherent pulsed LIDAR is receiving increasing attention as a method for detecting aerosol concentration in the air and detecting wind speed. Wind speed detection, in particular, is essential to modeling air flow patterns to analyze pollution transmission and determine optimal locations for wind turbines. City College of New York is currently developing a mobile coherent Doppler LIDAR station to detect wind speed. In Doppler sounding with coherent LIDAR, pulses are transmitted into the atmosphere. These pulses reflect off aerosol particles in the sky and return to the system. The motion of these aerosols can be measured based on the Doppler shift of the wavelengths transmitted. With a mobile system, it is possible to point at the same location from three or more different directions, and thus to calculate an accurate vector wind speed for the area. The station in development at City College of New York uses a 1.54 μm near-infrared pulsed beam. This wavelength is safe to the eye and provides an efficient balance of back-scattering and absorption. Signal analysis and detection is accomplished using heterodyne detection. In this process, two signals of slightly different frequency are created. Shifting can then be detected by comparing the initial modified frequency to the return frequency. Finally, a basic wedge prism i0073c is used to control the zenith angle of the beam as it is transmitted to the atmosphere. This will enable data to be taken from a variety of directions. Materials - LIDAR Comparison Coherent Doppler LIDAR System Overview Results LIDAR is short for Light Detection and Ranging. Uses pulsed infrared light to image objects including aerosols The wavelengths help detect aerosol particles….. Typically light is reflected via backscattering Conclusion Comparative Wind Speed Through Doppler Sounding with Pulsed Infrared LIDAR Tristan Schwartzman, Abdul Jalloh, Lowell Brazin Power spectrum from backscattering by gate ~50 meters per gate Best accuracy between 600 and 1100 meters for this case Peaks are added and FFT is used to calculate wind velocity Noise is removed based on distant gates Best estimate for wind speed is found by calculating a Gaussian Curve for each gate 2-D wind speed, with negative sign showing that wind is moving toward the LIDAR In the next step, mobile LIDAR will enable multiple locations and angles, and thus 3-D results From the NYC MetNet Website, provided by a station near CCNY Morning of May 6, 2011, from 5:00 am – 10:00 am Shows average wind direction at ground level Analysis of data from wind profile Wind Rose from Met Life Building Wind Profile – Met Life Building FFT derived Power Spectrum – May 6, 2011 Comparison: According to the wind profile from the MetLife Building, the northerly wind velocity vector at 10:00 am is approximately 15 mph. Readings with our LIDAR found an average northerly wind velocity of 9 mph. This suggests that the system is measuring wind speed. However, the test is highly uncertain, do to the limited vector nature of the comparison and the significant difference in locations. Full analysis will be possible after the LIDAR is tested using multiple directions from the mobile station. DC Bias and FFT: According to our Fast Fourier Transform Test on DC biasing, we found out that it is unnecessary to subtract the DC bias before computing the FFT of a signal. The top graph shows the frequency domain of a random signal with two different frequency components(4Hz and 9Hz) with a Trend and a DC value. The middle graph shows the frequency domain of the same signal but the Trend and DC value removed. The bottom graph shows a plot when the two signals are subtracted from one another. Abdelazim, S., Santoro, D., Arend M., Moshary, F., Ahmed, S. “All-fiber Coherent Doppler LIDAR for Wind Sensing.” Abdelazim, S., Santoro, D., Arend M., Moshary, F., Ahmed, S. “Wind velocity estimate and signal to noise ratio analysis of an all fiber coherent Doppler Lidar system,” 16 th Coherent Laser Radar Conference. Cariou, J., Boquet, M. “LEOSPHERE Pulsed Lidar Principles,” UpWind WP6 on Remote Sensing Devices, http://www.upwind.eu/media/576/D6.1.1.pdf. Ostaszewski, M., Harford, S., Doughty, N., Hoffman, C., Sanchez, M., Gutow, D., Pierce, R. “Risley Prism Beam Pointer,” Free-Space Laser Communications VI, 2006. http://nycmetnet.ccny.cuny.edu/Upper-Air-Measurements_Wind-Profiler-Display.asp/