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.

Date Published: 21 May 2015
PDF: 7 pages
Proc. SPIE 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV, 94741B (21 May 2015); doi: 10.1117/12.2176897

Published in SPIE Proceedings Vol. 9474:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV
Ivan Kadar, Editor(s)