Xampling and chaotic compressive sensing signal acquisition and reconstruction system

In this work, we present a software and hardware implementation in a PSoC (Programmable System-on-Chip) of a signal acquisition and reconstruction system. The design combines two novel techniques: data compression in the analog domain (Xampling) and compressed sensing (CS). The developed system allows an efficient reconstruction of signals from a smaller number of samples than the required by the Shannon-Nyquist sampling theorem. A critical point in CS technique is the choice of the sampling matrix, which is classically constructed using random sequences. These sequences are computationally expensive to generate, so in this work, we study the usage of chaotic sequences. In addition to that, we propose performance quantifiers to evaluate the modeled system. Finally, we conclude that the system implemented with chaos have a similar behavior compared to the conventional system.