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Interference due to transverse mode phase differences is the fundamental principle of multimode fiber sensors. Traditional demodulation methods based on spectral domain have limited sensitivity and accuracy due to spectral resolution constraints. To overcome this limitation, we propose a new sensing approach that maps the intermodal interference in spatial domain. We achieve this by sparsely sampling the fiber transverse mode field distribution (MFD) via a multi-core single-mode fiber (MCF), which acts as a cost-effective “fiber camera”. Additionally, spatial mode modulation was introduced to selectively excite different modes in the sensor. By switching the launching cores, different excited modes respond differently for a given environmental perturbation, resulting in a significant improvement in sensing resolution by up to 20 times. Multiplexing of sensor head offers a solution to cross-sensitivity by leveraging different core excitations. The discrimination of temperature and refractive index was demonstrated by use of a deep learning algorithm. Our spatial mode demodulation scheme presents exciting possibilities for low-cost, highly sensitive, and fast MMI sensors.

This study presents a novel approach for extracting perturbations in phase-sensitive optical time domain reflectometry (Φ-OTDR) under challenging ultra-low signal-to-noise ratio (SNR) conditions. To effectively enhance the SNR of Φ-OTDR signals, a block-matching and 3-D (BM3D) based denoising scheme was proposed. 1-D Φ-OTDR traces are converted to 2-D images that encapsulate both temporal and spatial information, enabling the utilization of the data correlation in both domains through BM3D to reduce the signal noise. This approach effectively preserves intricate details of Rayleigh signals while mitigating the impact of noise. Moreover, an adaptive parameter selection method tailored to the characteristics of reflected backscattered signals is developed to facilitate a more convenient and robust implementation of the denoising algorithm. Experimental validation is accomplished by performing distributed vibration sensing over an 80 km optical fiber with a spatial resolution of 10 m. Results show a substantial enhancement in SNR from 1.77 dB to 40.6 dB at the end of the test fiber. We firmly believe that the proposed approach holds significant potential for widespread application in long-distance distributed sensing scenarios operating under low SNR conditions.

Using coding in phase sensitive optical time domain reflectometry (ϕ-OTDR) system has long been pursued. However, since no single sequence with ideal aperiodic autocorrelation has been found, sidelobes of aperiodic autocorrelation induce crosstalk among sensors. Finding coding schemes with as low crosstalk as possible is very meaningful. In this paper, a novel ϕ-OTDR scheme with coding using polyphase unimodular sequence is proposed. Theoretical analysis of crosstalk due to coding sequence is presented at first. It shows that crosstalk is upper-bounded by sidelobes of aperiodic autocorrelation which is also an effective indicator of crosstalk level. Polyphase unimodular sequence with very low aperiodic autocorrelation sidelobes has then been searched through optimization of the Frank sequence using gradient descent algorithm. The merit factor (MF) of the obtained sequence is more than 2 times of that of the original Frank sequence. Compared to the pseudorandom binary sequence (PRBS), the MF of the obtained sequence is more than 10 dB higher. The evolution of MF of the obtained sequence at various stages and different transmission distance in a ϕ-OTDR system is demonstrated, which confirms that the sequence can support long-range sensing even though phases of the sequence are densely spaced. A ϕ-OTDR system with a weak fiber Bragg grating (WFBG) array is then set up to quantify crosstalk due to the polyphase unimodular sequence. In comparison to PRBS, experiment results confirm that the polyphase unimodular sequence has much lower crosstalk level and enhance the crosstalk rejection ratio by more than 10 dB.

Interference fading problem is an inevitable challenge in distributed acoustic sensing (DAS) system, and the uncertainty of the dynamic external environment further increases the difficulty of denoising. Based on the conventional single-domain fading suppression methods, we propose the concept of integrated fading suppression (IFS) algorithm set, which provides four denoising approaches and each of them is composed of at least two independent techniques. The combination of multiple single-domain denoising methods enhances the reliability of the proposed method. In an experiment involving 30 sets of data, the IFS algorithm set succeeded in completely eliminating all fading noise. In addition, the demodulation results show that compared to only applying a bandpass filter, these four IFS algorithms could improve the intensity signal-to-noise ratio by an average of 5.82 dB, while decreasing the amplitude fluctuation range by 31.84 dB on average. Benefiting from its powerful fading suppression capability, the average strain noise of the demodulated results obtained by the proposed algorithm set goes down to 0.47 nϵ. It is worth noting that the IFS algorithm set with four denoising methods is highly flexible and could meet different requirements and preferences. With the proposed IFS algorithm set, it is expected that the DAS system could be thoroughly free from the influence of interference fading.

Distributed acoustic sensing (DAS) is an attractive technology that can turn existing fibre optic networks to real-time distributed vibration sensors. However, it encounters great challenges in handling the transmission, storage, and processing of voluminous data streams which are orders of magnitude larger than that collected from point sensors. The gap between intensive data generated by φ-OTDR and modern computing system with limited reading/writing speed and storage capacity leads to restrictions on many applications. Compressive sensing (CS) is a revolutionary signal acquisition method that allows a signal to be acquired and reconstructed with significantly fewer samples than that required by Nyquist-Shannon theorem. The data size is greatly reduced in the sampling stage, but the reconstruction of the compressed data is still time and computation consuming. To address this challenge, we propose to map the feature extractor from Nyquist-domain to compressed-domain and therefore vibration detection and classification can be directly implemented in compressed-domain. The measured results show that our method can be used to reduce the transmitted data size by 70% while achieves a true positive rate (TPR) of 99.4% and a false positive rate (FPR) of 0.04% of positioning along 5-km-long sensing fibre and a classification accuracy of 95.05% on a 5-class classification task.

Characterized by the rapid advancement of artificial intelligence, an abundance of data translates into an expanse of potentialities. Consequently, the challenge of storing large amount of data generated by the long-term operation of the distributed acoustic sensing (DAS) system cannot be ignored in practical applications. Leveraging the nonuniform distribution of quantized spectrum values extracted from the Rayleigh backscattering (RBS) signal, this article introduces a data compression solution for DAS system with a compression ratio of 19.53 (corresponding to a space saving ratio of 94.88%). The proposed method not only achieves a high compression ratio but also offers two significant advantages: demodulation of the compressed data enables concurrent acquisition of amplitude and phase information, all while preserving a high density of sensing channels within the DAS system. These advantages facilitate the cost-effective storage of raw acoustic signals with intricate details. Possessing such data enables a more granular analysis of the sensing scene, subsequently enhancing the DAS system’s capacity to interpret events. Furthermore, this enhancement significantly contributes to the advancement and profound development within pertinent application domains.

A multimode fiber (MMF) speckle pattern is proposed to demodulate a distributed Bragg reflector (DBR) fiber laser sensor. DBR light source emits a highly coherent laser, and the speckle pattern is caused by intermodal interference in the MMF. The speckle change induced by salinity and temperature is identified using the image correlation algorithm through the alteration of the speckle pattern. Zero mean normalized cross correlation (ZNCC) is used to process the speckle data, and the test range was extended by adjusting the reference speckle. In the temperature range of 25 °C–75 °C and 75 °C–100 °C, the speckle sensitivity is −0.0150/°C and −0.0148/°C, respectively. The salinity sensitivity is −0.0158/ ‰, compared with nearly no spectrum shift in the optical spectrum analyzer (OSA) under the same conditions. The proposed sensor can be applied in environmental monitoring and other fields.

We propose and demonstrate a novel light detection and ranging (LiDAR) system for 3-D imaging, combined with laser feedback interferometry (LFI) and frequency-modulated continuous-wave (FMCW). Compared with the conventional FMCW method, the intracavity interference between the echo signal and local oscillator enhances the amplitude of the generated beat signal effectively, which improves the sensitivity in weak-signal detection with low photon consumption. The improvement is still effective even with frequency modulation nonlinearity. Besides, the system inherits the advantages of FMCW, possessing the capacity to measure position and velocity simultaneously. In experiments, the validity of distance and velocity measurement is demonstrated, and 3-D imaging is realized by employing a pair of beam scanners. With a less than $200 \mu \text{W}$ probe beam, the system achieves imaging over 65 m away in various scenes with good fidelity, and the distance resolution is better than 1 mm. A portable prototype is also designed and fabricated. Overall, the proposed system possesses high echo-signal sensitivity, simple structure, and dynamic information availability, which provides a new idea for FMCW-LiDAR optimization for practical applications.

In this paper, a dual-mode interferometric sensor based on a subwavelength grating (SWG) waveguide is proposed. The design operates at the dispersion turning point (DTP) of the two dispersive TE modes in the periodic structure, exhibiting a group velocity difference of almost zero, to improve the performance of refractive index (RI) sensors. The necessary conditions for realizing DTP in SWG are analyzed. Moreover, the interference spectrum characteristics and the influence of structural parameters on gas RI sensing performance are further studied. The results show that the sensitivity value of the proposed sensor can reach ∼38,000nm/RIU. The proposed structure can also achieve a gas pressure sensitivity of ∼105nm/MPa. The proposed sensors provide a potential platform for highly sensitive RI sensors.

Lead-free double perovskite phosphors are promising alternatives to lead halide perovskites for wide uses in optoelectronic applications, but suffer from a low quantum efficiency. Here, we propose to enhance the quantum efficiency of orange-emitting Cs2Ag0.4Na0.6InCl6:Bi via a codoping strategy. The internal quantum efficiency of Cs2Ag0.4Na0.6InCl6:1% Bi phosphor was increased from 89.9% to the record 98.4 and 98.6% by codoping with 1% Ni and 1% Ce, respectively. High-level density functional theory calculations have revealed that the enhanced efficiency is ascribed to the formation of shallow trap states by codoping with Ce, while codoping with Mn can create delocalized deep traps that decrease the quantum efficiency. By applying the (Bi,Ce)-codoped sample together with a blue BaMgAl10O17:Eu2+phosphor, a white light-emitting diode with an excellent color rendering index of 95.7 and a correlated color temperature of 4430 K has been demonstrated. The developed Cs2Ag0.4Na0.6InCl6:Bi,Ce phosphor shows a great potential as down-conversion luminescent material in solid-state lighting for general illumination.

We demonstrate a novel fiber tip Fabry–Perot (FP) interferometer with a chirped spectral characteristic. The FP interferometer is formed by an etched chirped fiber Bragg grating (FBG) and the fiber tip broadband end-face mirror, and the etched chirped FBG is prepared by a dynamic chemical etching process, shaping the taper and reducing the size from 125 μm to just a few micrometers. Due to the spectral characteristic of the etched chirped FBG, the different resonance wavelengths correspond to different gating positions which give rise to the gradient cavity length in the chirped fiber tip FP interferometer; thus, this FP interferometer possesses a chirped interference spectrum. Subsequently, the FP interferometer is fabricated, and the temperature response is investigated by measuring the wavelength shift of the resonance dips in the reflection spectrum. Significantly, because of its special interference principle and configuration, we experimentally demonstrate that this FP interferometer can be used for the spatial localization of the external temperature perturbations.

In this work, we mainly focus on the investigation of the feasibility of production of high-temperature stable fiber Bragg grating (FBG) based on reduplicative alternate annealing and hydrogen loading. The experimental results also can demonstrate the significance of the presence of hydrogen to the thermal regeneration of FBGs. The gratings are characterized and variations are compared after each stage, including UV fabrication, annealing, and reduplicative hydrogen-preloaded annealing. In different stages, the spectral and annealing responses of FBG are, respectively, investigated, as temperature increases, the Bragg wavelength consistently shifts to longer wavelengths; nevertheless, the reflection variations are distinctly discrepant. After reduplicative alternate annealing and hydrogen loading, the thermal stability is tremendously improved, and a reborn, stable grating is formed.

The characteristics of a frequency-modulated (FM) actively mode-locked fiber optical parametric oscillator have been demonstrated experimentally. In particular, the effects of pump power and modulation frequency on the features of the generated pulses (e.g., output power, RMS timing jitter, pulse width, and time-bandwidth product) are analyzed. Moreover, a stable pulse train of 37 ps with a RMS timing jitter of around 2.51 ps and a repetition rate of 10 GHz are generated. The results show that pulse trains with narrow pulse width and low RMS timing jitter are achievable when the modulation frequency increases. The corresponding time-bandwidth products at different pump powers are 0.61–0.66. In addition, stable optical pulses at 1567.38, 1551.92, 1544.29, and 1536.73 nm are generated simultaneously based on multiple four-wave mixing processes.

Stationary power/amplitude distributions for multiple channels of the sampled fiber Bragg grating (SFBG) along the grating length are analyzed. Unlike a uniform FBG, the SFBG has multiple channels in the reflection spectrum, not a single channel. Thus, the stationary power/amplitude distributions for these multiple channels are analyzed by using two different theoretical models. In the first model, the SFBG is regarded as a set of grating sections and non-grating sections, which are alternately stacked. A step-like distribution is obtained for the corresponding power/amplitude of each channel along the grating length. While, in the second model, the SFBG is decomposed into multiple uniform “ghost” gratings, and a continuous distribution is obtained for each ghost grating (i.e., each channel). After a comparison, the distributions obtained in the two models are identical, and the equivalence between the two models is demonstrated. In addition, the impacts of the duty cycle on the power/amplitude distributions of multiple channels of SFBG are presented.

It has great significance to monitor the oil and gas pipeline leakage to reduce economic loss and environmental pollution. In this paper, we propose a method to recognize the leakage of oil and gas pipeline based on both vibration and temperature information according to the distributed optical fiber sensor’s measurement ability. After comparing various feature values and different classifier models, we choose six temperature feature values, five vibration feature values, and the random forest model as the optimum combination for the pipeline leakage recognition. The method can accurately recognize the states of leakage, interference, and normal operation. The average recognition accuracy is 98.57%, which is higher than the traditional single-parameter judgment method, and the recognition time is only 6.79 ms.

Bio-chemical sensors are expected to offer high sensitivity and specificity towards the detection of an analyte. It has been found that optical sensors based on long period fiber gratings (LPFGs) meet most of these requirements, particularly when coated with thin and high-refractive index overlays with proper bio-functionalization. In this paper, the influence of properties of the overlay material on the sensitivity of LPFG sensors to bio-analytes is analyzed. It has been observed that the sensitivity of a particular cladding mode of LPFG can be changed drastically with the adhesion of few tens of ‘nm’ of bio-layers to the surface of LPFG. “Volume refractive index sensitivity” and “add-layer sensitivity” of a particular cladding mode, dynamic range, and limit of detection of the sensors have been investigated in the context of overlay materials, bio-functionalization steps, and surrounding buffer medium. The selection criteria of the thin-film deposition technique are discussed with the aim of designing highly sensitive sensors for biological and chemical applications. Concept of optimum overlay thickness has been redefined and an effective case-specific design methodology is proposed.