Related papers: Computational Compressed Sensing of Fiber Bragg Gr…
We present a proof-of-concept experiment aimed at increasing the sensitivity of temperature sensors implemented with Fiber Bragg gratings by making use of a weak value amplification scheme. The technique requires only linear optics elements…
Fibre Bragg grating sensors have emerged as a simple, inexpensive, accurate, sensitive and reliable platform, a viable alternative to the traditional bulkier optical sensor platforms. In this work we present an extensive theoretical…
Fiber Bragg Grating (FBG) sensors offer multiple benefits in comparison with electronic sensors due to their compactness, electromagnetic immunity as well as their resistance to harsh environments and their multiplexing capabilities.…
Sapphire optical fiber shows great promise for remote sensing in extreme environments approaching 2000 degC, by using laser-processing to form a single-mode waveguide within it. However, for practical application, longer devices with high…
Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage…
We present a computationally-efficient method for recovering sparse signals from a series of noisy observations, known as the problem of compressed sensing (CS). CS theory requires solving a convex constrained minimization problem. We…
We report a precision realization of photonic thermometry using dual-comb spectroscopy to interrogate a $\pi$-phase-shifted fiber Bragg grating. We achieve read-out stability of 7.5 mK at 1 s and resolve temperature changes of similar…
The integration of photonic sensors into microfluidic devices provides opportunities for dynamic measurement of chemical and physical properties of fluids in very small volumes. We previously reported on the use of commercially available…
Compressed sensing (CS) with prior information concerns the problem of reconstructing a sparse signal with the aid of a similar signal which is known beforehand. We consider a new approach to integrate the prior information into CS via…
In recent years, compressed sensing (CS) based image coding has become a hot topic in image processing field. However, since the bit depth required for encoding each CS sample is too large, the compression performance of this paradigm is…
In this work we report a novel technique for simultaneous high-speed and high-resolution interrogation of fiber Bragg grating (FBG) sensors. The method uses the wavelength-to-time mapping effect in a chromatic dispersive medium and a couple…
In recent years there has been considerable interest in utilizing embedded fiber optic based sensors for fabricating smart materials. One of the primary motivations is to provide real-time information on the structural integrity of the…
We show R&D results including long term stability, resolution, radiation hardness and characterization of Fiber Grating sensors used to monitor structure deformation, repositioning and surveying of silicon detector in High Energy Physics.
Fiber Bragg Grating (FBG) sensors have been so far mainly used in high energy physics (HEP) as high precision positioning and re-positioning sensors and as low cost, easy to mount, radiation hard and low space- consuming temperature and…
Compressed sensing (CS) exploits the sparsity of a signal in order to integrate acquisition and compression. CS theory enables exact reconstruction of a sparse signal from relatively few linear measurements via a suitable nonlinear…
Compressed sensing (CS) provides an elegant framework for recovering sparse signals from compressed measurements. For example, CS can exploit the structure of natural images and recover an image from only a few random measurements. CS is…
We report on the fabrication and characterization of photonic-based nanothermometers, a silicon photonic Bragg grating and photonic crystal cavity. When cladded with silicon dioxide layer the sensors have at least eight times better…
Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random…
As a paradigm to recover the sparse signal from a small set of linear measurements, compressed sensing (CS) has stimulated a great deal of interest in recent years. In order to apply the CS techniques to wireless communication systems,…
We have investigated the application of Compressive Sensing (CS) computational method to simultaneous compression and encryption of gamma spectra measured with NaI(Tl) detector during wide area search survey applications. Our numerical…