Abstract
A signal processing technique utilizing autocorrelation of backscattered signals was designed and implemented in a 1.5 µm all-fiber wind sensing Coherent Doppler Lidar (CDL) system to preprocess atmospheric signals. The signal processing algorithm’s design and implementation are presented. The system employs a 20 kHz pulse repetition frequency (PRF) transmitter and samples the return signals at 400 MHz. The logic design of the autocorrelation algorithm was developed and programmed into a field programmable gate array (FPGA) located on a data acquisition board. The design generates and accumulates real time correlograms representing average autocorrelations of the Doppler shifted echo from a series of adjustable range gates. Accumulated correlograms are streamed to a host computer for subsequent processing to yield a line of sight wind velocity. Wind velocity estimates can be obtained under nominal aerosol loading and nominal atmospheric turbulence conditions for ranges up to 3 km.
Highlights
The utilized LIDAR technique is based on the detection and analysis of backscattered light resulting from a laser beam’s interaction with aerosol particles and constituents
The The velocity usefultotocharacterize characterizeand andbaseline baselinethis this change with operation of the useful to characterize andpower baseline this change with thecurve operation of the twoitsLidar systems
Increasing range gate size allows for integrating more signal power, which results in in Cramer Rao Lower Bound (CRLB) on the variance of wind velocity estimates
Summary
The utilized LIDAR technique is based on the detection and analysis of backscattered light resulting from a laser beam’s interaction with aerosol particles and constituents. An alternative technique to the estimation of periodograms was presented previously [11] This alternative technique involves the calculation of the autocorrelation of backscattered time-domain received signals’ correlograms, for a number of lags. Mixing the received signals (oscillating at 84 MHz +/− Doppler shift) with an 84 MHz cosine and sine signals produces two output signals, a high frequency (sum of Fourier transform (power spectrum). Mixing the received signals (oscillating at 84 MHz +/− Doppler shift) with an 84 MHz cosine and sine signals produces two output signals, a high frequency (sum of thethe two frequencies) component and a low frequency (difference of of thethe two frequencies) component. We find the power spectrum of that range gate’s signals by calculating the FFT of the constructed complex autocorrelation vector
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