In this paper, we present two signal processing algorithms implemented using the FPGA. The first algorithm involves explicate time gating of received signals that correspond to a desired spatial resolution, performing a Fast Fourier Transform (FFT) calculation on each individual time gate, taking the square modulus of the FFT to form a power spectrum and then accumulating these power spectra for 10k return signals. The second algorithm involves calculating the autocorrelation of the backscattered signals and then accumulating the autocorrelation for 10k pulses. Efficient implementation of each of these two signal processing algorithms on an FPGA is challenging because it requires there to be tradeoffs between retaining the full data word width, managing the amount of on chip memory used and respecting the constraints imposed by the data width of the FPGA. A description of the approach used to manage these tradeoffs for each of the two signal processing algorithms are presented and explained in this article. Results of atmospheric measurements obtained through these two embedded programming techniques are also presented.
KEYWORDS: Signal processing, Field programmable gate arrays, LIDAR, Doppler effect, Wind measurement, Data acquisition, Signal detection, Remote sensing, Bragg cells, Digital signal processing
A field deployable all-fiber eye-safe Coherent Doppler LIDAR is being developed at the Optical Remote Sensing
Lab at the City College of New York (CCNY) and is designed to monitor wind fields autonomously and
continuously in urban settings. Data acquisition is accomplished by sampling lidar return signals at 400 MHz and
performing onboard processing using field programmable gate arrays (FPGAs). The FPGA is programmed to
accumulate signal information that is used to calculate the power spectrum of the atmospherically back scattered
signal. The advantage of using FPGA is that signal processing will be performed at the hardware level, reducing the
load on the host computer and allowing for 100% return signal processing. An experimental setup measured wind
speeds at ranges of up to 3 km.
A compact coherent wind lidar system has been developed and is being tested in an urban environment. We use
polarization maintaining fiber throughout the system to improve the stability of the heterodyne detected return signal.
The 1.54 micron transmitter is designed using a master oscillator and pulsed power amplifier configuration. The
receiver is operated in a coaxial arrangement and balanced detection is employed to reduce the effects of relative
intensity noise, allowing for operation in the shot noise limited regime. Development and verification of the lidar system
is enhanced by taking advantage of a set of ground based sodar, radar wind profiler and building top anemometers that
are part of the New York City Meteorological Network. Operation in a coastal urban environment with a complex
terrain such as New York City requires that the system be flexible enough to allow for adjustable operating conditions,
tunable signal processing algorithms and user defined data products, so that the optimal performance can be chosen with
a variety of practical applications in mind.
The Department of Homeland Security (DHS) sponsored Urban Dispersion Program (UDP) resulted in the strategic
placement of weather instruments in New York City (NYC) and the transition of some instruments to the City College of
New York (CCNY) operated NYC MetNet to provide timely and accurate information on "skimming field" winds above
city building tops. In order to extend the observational capabilities of the NYC MetNet, a cost effective portable eye
safe fiber optic based coherent wind lidar system is currently under development in CCNY laboratories. Wind lidar
measurements, coupled with the continuous observations from the NYC MetNet, should support the initialization,
feedback and development of plume models that would be used after an initial detection of airborne toxins. An
overview of the lidar system design and the NYC MetNet will be given.
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