A Raman amplifier having an optical pump configured to generate pump bands, each of which is spectrally aligned with a respective wavelength channel of a frequency grid in a manner that enables the pump bands to coexist in an optical fiber with data-carrying signals of other wavelength channels of the frequency grid without causing unworkable levels of inter-channel interference. In an example embodiment, the optical pump comprises a laser whose single-mode output is modulated to sufficiently suppresses stimulated Brillouin scattering in the optical fiber while still keeping the optical power of each of the resulting pump bands spectrally compact, e.g., substantially contained within the slot width of the respective wavelength channel. In some embodiments, at least some pump bands can be spectrally interleaved with some of the data-carrying signals to increase the data-throughput capacity of the corresponding optical transport system.

The present invention relates to a device (1) for characterizing an interface of a structure (6), said structure (6) comprising a solid first material and a second material, the materials being separated by said interface. The device (1) comprises: means (2) for generating a first mechanical wave; means (2) for forming Brillouin oscillations; means (10) for detecting time variation of the Brillouin oscillations; means (12) for responding to the time variation of the Brillouin oscillations to identify reflection of said first mechanical wave by said interface or transmission through said interface of a second mechanical wave interfering with the first mechanical wave; and means (13) for determining the variation in amplitude of the Brillouin oscillations before and after reflection or transmission by said interface. The invention also relates to a corresponding method of characterization.

A system includes a detector array having a plurality of level detectors to monitor an optical input signal. Each level detector of the detector array operates in a different operating range, and each operating range for each level detector has a different saturation level and a different cutoff level based on a power level of the optical input signal. A controller monitors the plurality of level detectors of the detector array to detect a present power level for the optical input signal by selecting the operating range that is associated with the level detector operating between its saturation level and its cutoff level.

A system includes a detector array having a plurality of level detectors to monitor an optical input signal. Each level detector of the detector array operates in a different operating range, and each operating range for each level detector has a different saturation level and a different cutoff level based on a power level of the optical input signal. A controller monitors the plurality of level detectors of the detector array to detect a present power level for the optical input signal by selecting the operating range that is associated with the level detector operating between its saturation level and its cutoff level.

A system includes a detector array having a plurality of level detectors to monitor an optical input signal. Each level detector of the detector array operates in a different operating range, and each operating range for each level detector has a different saturation level and a different cutoff level based on a power level of the optical input signal. A controller monitors the plurality of level detectors of the detector array to detect a present power level for the optical input signal by selecting the operating range that is associated with the level detector operating between its saturation level and its cutoff level.

A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

Aspects of the present disclosure are directed to systems, methods, and structures providing for the accurate measurement of guided acoustic-wave Brillouin scattering in optical fiber transmission systems and facilities.

Aspects of the present disclosure are directed to systems, methods, and structures providing for the accurate measurement of guided acoustic-wave Brillouin scattering in optical fiber transmission systems and facilities.

The present disclosure provides a method and system of identifying macro-bends in at least one test fiber. The method includes generation of modulated optical pulses and scrambling the state of polarization of the modulated optical pulses to random states of polarization. The method includes injection of the modulated optical pulses in at least one test fiber and reception of backscattered optical pulses and splitting of the backscattered optical pulses to a first optical component and a second component. The method includes measurement of a first power of the first optical component and a second power of the second optical component of the backscattered optical pulses. The method includes calculation of discrete values of polarization dependent loss as a function of distance and identification of the macro-bends by analysis of peaks in one or more plots of one or more traces of the discrete values of the polarization dependent loss.