  State-of-the-art fiber Bragg grating interrogators utilize mature concepts
and technologies like tunable lasers, optical spectrum analyzers and a
combination of time, wavelength, or spatial division demultiplexing approaches.
Here, we propose the use of computational compressed sensing (CS) techniques
for interrogation of fiber Bragg gratings, reducing interrogator complexity by
using a broadband ASE light source and single-pixel detection. We demonstrate
temperature sensing using a pre-calibration approach to achieve reconstruction
accuracy comparable to uncompressed measurements. We extend these principles
for the interrogation of sensor networks, presenting strategies for tackling
sparsity considerations. Our proof-of-principle demonstrations show how the
presented computational compressed sensing techniques can provide an
alternative for realizing low-complexity, small footprint interrogator
configurations.
