Implementation of a Novel Hardware Reflectometry System Employing Compressed Sensing for Efficient Cable Diagnostics

This paper presents the design and experimental validation of a novel hardware reflectometry architecture based on the Compressed Sensing (CS) paradigm. By integrating an Analog-to-Information Converter operating at a lower sampling rate than conventional high-speed Analog-to-Digital Converters, the proposed approach reduces cost, power consumption, and memory requirements. Building on previous simulation studies that validated the feasibility of combining CS with a Chirp Orthogonal Multitone Time-Domain Reflectometry (Chirp-OMTDR) signal, this work delivers a complete hardware implementation. Experimental results from our prototype, tested on coaxial cables, confirm the system's ability to detect and locate both hard faults and temperature-induced impedance variations at a compression factor of 2, without degrading fault detection or localization accuracy. These findings validate the feasibility and robustness of the proposed CS-based reflectometry solution for practical cable diagnostics.