Chaos Raman distributed optical fiber sensing

Distributed optical fiber sensing measures strain, temperature, and vibration over long ranges with immunity to electromagnetic interference and corrosion. Spatial resolution—the smallest resolvable spatial unit—has been constrained in traditional Raman distributed optical fiber sensing (DOFS) by the pulse time-of-flight positioning principle. Because the anti-Stokes signal at a location represents a superposition of Raman scattering over the pulse-width distance, closely spaced temperature mutations within a pulse width cannot be distinguished. Thus, spatial resolution is limited by pulse width and deteriorates with increasing sensing distance to several meters or more at the fiber end. Shortening the optical pulse can improve resolution but degrades SNR, limiting sensing distance; hence, balancing SNR and spatial resolution is a bottleneck. Prior advances include single-mode and few-mode fiber pulse modulation schemes that increase coupled power and suppress nonlinearity while limiting resolution deterioration with distance (e.g., 1.0 m at 39 km; 1.13 m at 25 km). However, meter-level resolution persists. The authors previously proposed a simulation model based on chaotic and Raman signals; here they experimentally demonstrate a chaos Raman DOFS scheme achieving 10 cm resolution over ~1.5 km with a 50 ns pulse, a 50× improvement over pulse time-of-flight demodulation, and to their knowledge the first 10 cm resolution at kilometer distances.

The paper reviews limitations of traditional Raman DOFS where spatial resolution is bound by pulse width due to time-of-flight OTDR principles, leading to meter-level resolution at kilometer scales. Attempts to improve include ultrashort pulse mode-locked lasers (e.g., 10 cm resolution over only 3.0 m) and modulation schemes in single-mode fibers (e.g., genetically optimized aperiodic codes achieving 1.0 m resolution at 39.0 km) and few-mode fibers (graded-index few-mode fiber achieving 1.13 m at 25.0 km). These improve SNR and mitigate nonlinearity but do not break the meter-level resolution limit, motivating the exploration of chaotic light and correlation-based demodulation.

A chaos Raman distributed optical fiber sensing scheme is implemented using chaos differential reconstruction and a chaos double-correlation demodulation method. A 1550 nm CW laser, after passing a circulator, is converted to continuous chaotic light via a single-feedback structure (attenuator, polarization controller, fiber coupler). The chaotic light is gated by a semiconductor optical amplifier (SOA) to form chaotic pulses and amplified by an EDFA. A 1:99 coupler provides a 1% chaotic pulse as a reference for correlation and injects 99% into the sensing fiber via a WDM that separates the 1450 nm anti-Stokes Raman backscatter. The anti-Stokes signal and the chaotic reference pulse are detected by an APD and digitized by an oscilloscope. The signal processing pipeline includes: (1) chaos differential reconstruction of the Raman anti-Stokes backscatter to suppress contributions from non-mutation temperature regions and enhance temperature-modulated components in the fiber-under-test (FUT) zone; (2) first-order and second-order chaos cross-correlation between the reconstructed backscatter and the chaotic reference to produce compressed correlation peaks localized at the FUT start; (3) derivative-based localization using the first derivative zero crossing to mark the FUT start and the nearest second derivative zero crossing to mark the FUT end, yielding precise FUT length and position; and (4) temperature demodulation using the peak-to-peak correlation coefficient from the chaos second-order correlation output, which is linearly related to temperature under fixed pulse width, per a derived equation (Eq. (10) referenced in Materials and methods). Experimental configurations: FUT ring lengths of 2.0 m, 50 cm, and 10 cm placed at the fiber end; the ambient fiber at ~25 °C and FUT heated to 60.00, 70.00, 80.00, and 90.00 °C via a temperature control platform. Chaotic pulse widths: 500 ns for 2.0 m and 50 cm FUTs; 50 ns for 10 cm FUT to mitigate noise. Sensing distances in tests span ~1.0–1.5 km. WDM passes 1450 nm anti-Stokes; APD detects both anti-Stokes and reference pulses; correlation processing enhances weak signals (second-order correlation) and improves SNR for sub-meter FUTs.

• Demonstrated chaos Raman DOFS achieving 10 cm spatial resolution over a kilometer-scale sensing distance (1.4 km per abstract; experiments span 1.0–1.5 km), with spatial resolution independent of sensing distance.
• Second-order chaos correlation significantly enhances correlation peaks and reduces noise versus first-order correlation, enabling precise localization for FUT lengths below 1 m (50 cm and 10 cm), where first-order results show only trend changes.
• Derivative-based localization of correlation outputs accurately determined FUT lengths: 2.0 m, 50 cm, and 10 cm, matching ground truth.
• Temperature demodulation based on the chaos double-correlation peak-to-peak coefficient shows a linear relationship between correlation peak-peak values and temperature for all FUT lengths tested (2.0 m, 50 cm, 10 cm), validating the theoretical model (per Eq. (10)).
• Temperature accuracy can be controlled within 1.32% (from analysis and tabulated results referenced in Discussion).
• Compared with traditional pulse time-of-flight demodulation, the scheme improves spatial resolution by approximately 50× under comparable pulse-width constraints.
• Fiber dispersion may distort chaotic signals and affect correlation peak amplitude (impacting temperature accuracy/SNR), but does not shift the correlation peak positions; thus spatial resolution remains unaffected.

The study addresses the fundamental limitation of Raman DOFS spatial resolution tied to pulse width by employing chaotic light and correlation-based time-domain compression. By correlating a chaotic reference with the reconstructed Raman anti-Stokes signal, temperature-induced variations distributed over the FUT length are compressed into distinct correlation peaks at the FUT boundaries, decoupling spatial resolution from source pulse width and sensing distance. Second-order correlation and derivative analysis further improve SNR and enable precise boundary detection in sub-meter FUTs. Temperature demodulation leverages the linear mapping between correlation peak-to-peak amplitude and temperature under fixed pulse width, enabling quantitative temperature retrieval. While fiber dispersion can attenuate or broaden chaotic features affecting peak amplitudes and thus temperature accuracy/SNR, the correlation peak timing—and hence spatial localization—remains robust, preserving high spatial resolution over long distances. Overall, the findings demonstrate a practical pathway to centimeter-scale resolution at kilometer ranges without sacrificing sensing distance.

The paper introduces and experimentally validates a chaos Raman distributed optical fiber sensing scheme that overcomes the pulse-width-limited spatial resolution of traditional Raman DOFS. Using chaotic light, differential reconstruction, second-order correlation, and derivative-based localization, the method achieves 10 cm spatial resolution over kilometer-scale fibers (≈1.4–1.5 km) and shows spatial resolution independent of sensing distance. Temperature demodulation is accurate, with linear correlation between peak-peak coefficients and temperature and accuracy within ~1.32%. This represents an approximately 50× improvement over conventional time-of-flight demodulation and opens a new research direction at the intersection of optical chaos and distributed fiber sensing. Future work may further optimize temperature accuracy and SNR under fiber dispersion and explore extended sensing distances and environmental conditions.

• Incomplete mitigation of fiber dispersion: dispersion distorts chaotic waveforms, reducing correlation peak amplitudes and thereby impacting temperature accuracy and SNR, although spatial resolution (peak timing) is preserved.
• Noise sensitivity with wider chaotic pulses: increased chaos pulse width raises noise levels, necessitating shorter pulses (e.g., 50 ns for 10 cm FUT) or higher-order correlation to maintain demodulation fidelity.
• Dependence on careful calibration of the linear relationship between correlation peak-peak values and temperature (Eq. (10)), which may vary with system parameters (pulse width, gain, detection chain).
• Experimental validation focused on specific FUT lengths (2.0 m, 50 cm, 10 cm) and a ~1.0–1.5 km range; broader validation across diverse fibers, environments, and longer distances is not shown in the provided text.