Empirical and experimental results are provided, proving the successful application of sub-Nyquist sampling to wide-bandwidth linear frequency modulated waveforms commonly used in ranging applications. The wide bandwidth nature of these waveforms traditionally dictate the need for high speed digitizers and matched filtering in order to determine the range to an object. We propose that a sub-Nyquist rate digitizer, along with the notions of sparse recovery, can be used to significantly reduce the rate and number of samples necessary to detect the range to an object, thereby reducing overall system cost. Specifically, the application of these concepts to a laser based ranging system is explored, and properties of the sensing matrix are investigated as well as possible sparse recovery performance.

Date Published: 4 May 2016
PDF: 9 pages
Proc. SPIE 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics, 985702 (4 May 2016); doi: 10.1117/12.2223231

Published in SPIE Proceedings Vol. 9857:
Compressive Sensing V: From Diverse Modalities to Big Data Analytics
Fauzia Ahmad, Editor(s)