Signal-to-noise Ratio Enhancement Research Articles

Performance enhancement of optical pulse coding phase-sensitive OTDR system with genetic-optimized code

Optical pulse coding (OPC) in phase-sensitive optical time-domain reflectometry (φ-OTDR) traditionally relies on standard coding sequences as probe pulse trains, which usually suffer the problem of distorted probe pulse caused by the gain saturation in erbium-doped fiber amplifier (EDFA). To improve the signal-to-noise ratio (SNR) and mitigate distortion caused by the EDFA gain saturation, a genetic-optimized code (Go-code) based OPC φ-OTDR (GOPC φ-OTDR) scheme is proposed in this paper. The unique Go-code sequence generated by the distributed genetic algorithm (DGA) is explored in the field of φ-OTDR for the first time, and the coding sequence was optimized to adapt to the vibration sensing requirements in φ-OTDR. Theoretical analyses focused on EDFA gain saturation effects and coding gain were conducted. The experiment of GOPC φ-OTDR demonstrated significant improvements compared with Golay φ-OTDR, achieving less distortion in decoding response and approximately 7.48 dB phase demodulation SNR enhancement within a 10-km sensing range. This research marks Go-code's pioneering exploration into φ-OTDR, demonstrating substantial advancements in optimization metrics, and opening avenues for exploring advanced OPC technologies.

Orthogonal DNA Self-Assembly-Based Expansion Microscopy Platform for Amplified, Multiplexed Biomarker Imaging.

Expansion microscopy (ExM) facilitates nanoscale imaging under conventional microscopes, but it frequently encounters challenges such as fluorescence losses, low signal-to-noise ratio (SNR), and limited detection throughput. To address these issues, a method of orthogonal DNA self-assembly-based ExM (o-DAExM) platform is developed, which employs hybridization chain reaction instead of conventional fluorescence labeling units, showcasing signal amplification efficacy, enhancement of SNR, and expandable multiplexing capability at any stage of the ExM process. In this work, o-DAExM has been applied to compare with immunofluorescence-based ExM for cellular cytoskeleton imaging, and the resolved nanoscale spatial distributions of cytoskeleton show outstanding performance and reliability of o-DAExM. Furthermore, the study demonstrates the utility of o-DAExM in accurately revealing exosome heterogeneous information and multiplexed analysis of protein targets in single cells, which provides infinite possibilities in super-resolution imaging of cells and other samples. Therefore, o-DAExM offers a straightforward expansion and signal labeling method, highlighting future prospects to study nanoscale structures and functional networks in biological systems.

Multifold enhancement of quantum SNR by using an EMCCD as a photon number resolving device

Electron multiplying charge-coupled devices (EMCCDs), owing to their high quantum efficiency and spatial resolution, are widely used to study typical quantum optical phenomena and related applications. Researchers have already developed a procedure that enables one to statistically determine whether a pixel detects a single photon, based on whether its output is higher or lower than the estimated noise level. However, these techniques are feasible at extremely low photon numbers (≈0.15 mean number of photons per pixel per exposure), allowing for at most one photon per pixel. This limitation necessitates a very large number of frames required for any study. In this work, we present a method to estimate the mean rate of photons per pixel per frame for arbitrary exposure time. Subsequently, we make a statistical estimate of the number of photons (≥ 1) incident on each pixel. This allows us to effectively use the EMCCD as a photon number resolving device. This immediately augments the acceptable light levels in the experiments, leading to significant reduction in the required experimentation time. As evidence of our approach, we quantify contrast in quantum correlation exhibited by a pair of spatially entangled photons generated by a spontaneous parametric down conversion process. In comparison with conventional methods, our method realizes an enhancement in the signal-to-noise ratio (SNR) by approximately a factor of 3 for half the data collection time. This SNR can be easily enhanced by minor modifications in experimental parameters such as exposure time, etc.

The applications of sonar and radar systems in underwater detection

The development of sonar and radar systems utilizing sound and radio waves, respectively, has evolved significantly over the past two centuries. Recent decades have witnessed remarkable progress in remote sensing using high-frequency Doppler radars for marine surface parameter analysis. Understanding animal behavior around sustainable ocean energy sources is crucial for mitigating potential risks linked to such installations. Increasing the Signal-to-Noise Ratio (SNR) enhances signal reception. A technique estimating noise in the detection coil's first half determines the transfer function between the reference and detection coils. This enables separation of the Ultra-Nuclear Magnetic Resonance signal from noise, preserving it using non-linear fitting. Sonar systems, using sound waves, detect underwater objects, map surfaces, and track marine life. Sound waves emitted by the transmitter are reflected back to calculate distances. Challenges in sonar systems include a blind zone caused by submerged transducers in shallow water. To improve, SNR enhancement is critical. Sonar's future may rely on AI-assisted signal processing. Radar systems, operating with radio waves, share features with sonar, focusing on object detection and ranging. Improvement avenues include 3D imaging and AI-enhanced signal processing. In conclusion, sonar and radar systems are crucial tools for underwater exploration and object detection. While challenges persist, innovative solutions and AI advancements promise enhanced capabilities for both systems.

Theoretical Demonstration of Improved Performance in Multi-Channel Photonic RF Signals Based on Optical Injection Locking of Optical Comb and Array Lasers

Multi-channel radio frequency (RF) signal generation, facilitated by photonic technology, offers significant potential for generating coherent signals with a high frequency and low phase noise, providing multifunctional capabilities across diverse platforms, including RF and photonic systems. Traditional methods for multi-channel photonic RF signal generation typically entail the integration of diverse optical components, such as filters and amplifiers. However, this integration often results in compromises related to power efficiency, cost-effectiveness, and implementation simplicity. To address these challenges, we propose a novel method for generating multi-channel photonic RF signals based on optical injection locking technology. This approach eliminates the necessity for traditional optical components, leading to a substantial enhancement in the performance of photonic RF signals. We present the design of an optical injection locking-based multi-channel photonic RF signal generation schematic and theoretically evaluate its Signal-to-Noise Ratio (SNR) and eye pattern performance for data modulation using the Lumerical INTERCONNECT simulator. Our results reveal a significant 1.3-dB and 3.6-dB enhancement in SNR for 30-GHz and 60-GHz signals, respectively. Furthermore, we observed an improved communication performance, as evidenced by enhanced eye patterns in 3-Gbps data transmission compared to passive photonic RF signal generation methods.

SNR enhancement for dual wavelength distributed fiber acoustic sensing system using improved recursive least squares method

In this paper, an improved recursive least squares (RLS) method has been proposed to enhance the signal-to-noise ratio (SNR) of dual wavelength distributed fiber acoustic sensing system. The raw detected signals of 1550 nm differential signal and 1310 nm interference signal are processed by wavelet decomposition and reconstruction techniques to obtain the estimation of the reference signal. The tap factor is self-iterated according to the parameters at the previous time under the corresponding evaluation metrics. The system allows detecting and locating acoustic signal at an arbitrary position on a single optical fiber without using additional sensitizing devices. Experimental results demonstrate that the SNR of the acoustic restoration and localization are substantially improved by 14.98 ∼ 20.33 dB and 19.27 ∼ 29.71 dB, respectively. The proposed system exhibits considerable potential for demodulating and reconstructing acoustic signals over long distances and in wide ranges.

Optimized derivative fast Fourier transform with high resolution and low noise from encoded time signals: Ovarian NMR spectroscopy

The unfiltered derivative fast Fourier transform (dFFT) of degrees higher than two fails flagrantly for encoded time signals. These data are always dominated by noise at larger times of encodings. Such a breakdown is due to processing the unweighted product of the time signal and the time power function. The latter is generated by the frequency derivative operator applied to the fast Fourier transform (FFT). As a result, the unfiltered dFFT cannot separate the overlapped resonances and it dramatically decreases signal-to-noise ratio (SNR) relative to the FFT. This problem is solved by a derivative-adapted optimization with the properly attenuated filters. The ensuing optimized dFFT achieves the long sought simultaneous enhancement of both resolution and SNR. It uncovers the genuine resonances hidden within overlapping peaks to enable quantitative interpretations. It does not impose any model on the input time signals nor on the output lineshape in the spectra. It is computationally expedient as it uses the Cooley-Tukey fast algorithm. The present applications deal with time signals encoded by in vitro NMR spectroscopy from human malignant ovarian cyst fluid. A remarkably successful performance of the optimized dFFT is demonstrated for reconstructed spectra of potentially added value in clinical decision-making.

Analysis of rotational Doppler shift with multi-ring vortex beams.

Vortex beams (VBs) with orbital angular momentum have shown great potential in the detection of transverse rotational motion of spatial targets which is undetectable in the classical radar scheme. However, most of the reported rotational Doppler measurements based on VBs can only be realized under ideal experimental conditions. The long-range detection is still a challenge. The detection distance based on rotational Doppler effect (RDE) is mainly limited by the scattered signal's signal-to-noise ratio (SNR). In this work, we investigated the influence of multi-ring vortex beams (MVBs) on the rotational Doppler frequency spectrum of scattered light from an object based on RDE and proposed a method of SNR enhancement of RDE signal. Firstly, different types of MVBs composed of a set of single-ring VBs with the same topological charge and different radii are designed, including multi-ring Laguerre Gaussian beam (MLGB), multi-ring perfect vortex beams (MPVB), and high-order Laguerre Gaussian beam (HLGB). Then, the influence of the number of rings and radial radius interval on the intensity profiles of MVBs and rotational Doppler frequency spectra under aligned and misaligned conditions is studied in detail. And the reasons why different types of MVBs lead to different SNR enhancement effectiveness with the increase of rings are also analyzed theoretically. Finally, proof-of-concept experiments were conducted to verify the effectiveness of the SNR enhancement method for RDE signals. The results showed that the amplitudes of the Doppler spectra generated by the MLGB and MPVB are improved substantially with the increase of rings, but the enhancement effect caused by the former is superior to the latter. The gain of HLGB on the RDE signal is the lowest. This study provides a useful reference for the optimization of rotational Doppler detection systems and may be of great application value in telemetry, long-range communication and optical imaging.

SNR improved digital-cascaded-pulse-code-modulation radio-over-fiber scheme supporting 16,777,216 QAM for mobile fronthaul

We propose a digital-cascaded-pulse-code-modulation radio-over-fiber (DCP-RoF) scheme and verify it experimentally in a coherent transmission system. The 50-Gbaud 2-order 6-bit DCP-RoF signal with a common public radio interface equivalent data rate of 279Gb/s/λ is successfully transmitted in a 10-km standard single-mode fiber link. Results show that the 2-order 6-bit DCP-RoF scheme achieves a maximum recovered signal-to-noise ratio (SNR) of 83.43 dB, which meets the requirements for 16,777,216-quadrature-amplitude-modulation (16,777,216-QAM) transmission. The DCP-RoF scheme has advantages over analog RoF and digital–analog RoF in terms of SNR improvement, as well as advantages over digital RoF (D-RoF) in spectral efficiency. Furthermore, an average SNR enhancement of 13.48 dB for each linearly increased bandwidth is achieved in the DCP-RoF scheme. Our work suggests many optimistic possibilities for the future radio access networks and mobile fronthaul.

Enhancing the brain MRI at ultra-high field systems using a meta-array structure.

The main advantage of ultra-high field (UHF) magnetic resonance neuroimaging is theincreased signal-to-noise ratio (SNR) compared with lower field strength imaging. However, the wavelength effect associated with UHF MRI results in radiofrequency (RF) inhomogeneity, compromising whole brain coverage for many commercial coils. Approaches to resolving this issue of transmit field inhomogeneity include the design of parallel transmit systems (PTx), RF pulse design, and applying passive RF shimming such as high dielectric materials. However, these methods have some drawbacks such as unstable material parameters of dielectric pads, high-cost, and complexity of PTx systems. Metasurfaces are artificial structures with a unique platform that can control the propagation of the electromagnetic (EM) waves, and they are very promising for engineering EM device. Implementation of meta-arrays enhancing MRI has been explored previously in several studies. The aim of this study was to assess the effect of new meta-array technology on enhancing the brain MRI at 7T. A meta-array based on a hybrid structure consisting of an array of broadside-coupled split-ring resonators and high-permittivity materials was designed to work at the Larmor frequency of a 7 Tesla (7T) MRI scanner. When placed behind the head and neck, this construct improves the SNR in the region of the cerebellum,brainstem and the inferior aspect of the temporal lobes. Numerical electromagnetic simulations were performed to optimize the meta-array design parameters and determine the RF circuit configuration. The resultant transmit-efficiency and signal sensitivity improvements were experimentally analyzed in phantoms followed by healthy volunteers using a 7T whole-body MRI scanner equipped with a standard one-channel transmit, 32-channel receive head coil. Efficacy was evaluated through acquisition with and without the meta-array using two basic sequences: gradient-recalled-echo (GRE) and turbo-spin-echo (TSE). Experimental phantom analysis confirmed two-fold improvement in the transmit efficiency and 1.4-fold improvement in the signal sensitivity in the target region. In vivo GRE and TSE images with the meta-array in place showed enhanced visualization in inferior regions of the brain, especially of the cerebellum, brainstem, and cervical spinal cord. Addition of the meta-array to commonly used MRI coils can enhance SNR to extend the anatomical coverage of the coil and improve overall MRI coil performance. This enhancement in SNR can be leveraged to obtain a higher resolution image over the same time slot or faster acquisition can be achieved with same resolution. Using this technique could improve the performance of existing commercial coils at 7T for whole brain and other applications.

SNR enhancement of quasi-distributed weak acoustic signal detection by elastomers and MMF integrated Φ-OTDR.

We have proposed and demonstrated a weak acoustic signal detection technology based on phase-sensitive optical time-domain reflectometry (Φ-OTDR). Non-contact acoustic signals transmitting through air gap between the sound source and the receiver are difficult to detect due to fast attenuation. In order to improve the detection ability of non-contact weak acoustic signals, we demonstrate that multi-mode fiber (MMF) is a better solution than single-mode fiber (SMF) benefiting from its larger core and higher Rayleigh backscattering (RBS) capture coefficient. The frequency signal-to-noise ratio (SNR) has been enhanced by 9.26 dB. Then, with the help of 3D printing technology, elastomers have been designed to further enhance the detection ability due to the high-sensitive response to acoustic signals. Compared with the previous reported "I" type elastomer, the location and frequency SNR enhancement caused by our new proposed "n" type elastomer are 8.39 dB and 11.02 dB in SMF based system. The values are further improved to 10.51 dB and 13.38 dB in MMF and "n" type elastomer integrated system. And a phase-pressure sensitivity of -94.62 dB re rad/µPa has been achieved at 2.5 kHz. This non-contact weak acoustic signal detection technique has great application potential in the quasi-distributed partial discharge (PD) detection of smart grid.

An integrated workflow for pre-stack gather optimization

Abstract High-quality seismic data contribute to improving the prediction accuracy of complex reservoirs. Currently, there are several methods for enhancing pre-stack gather resolution and signal-to-noise ratio (SNR). Meanwhile, to avoid incorrect seismic interpretation, we must evaluate whether the processed data maintains its original characteristics and reliability. This paper establishes an integrated workflow for optimizing common-reflection-point (CRP) gather that is divided into processing and quality control. Furthermore, we summarize the comprehensive quality control means and explain their specific significance in each step. Data processing includes four parts: gather flattening, SNR enhancement, energy compensation, and resolution improvement. Simultaneously, we use well log data, forward simulation, stack data, and inversion to guarantee the processed data is optimized and keeps its original characteristics. Applications in carbonate reservoir CRP gathers demonstrate that this workflow can comprehensively optimize pre-stack seismic data and improve SNR and resolution. Importantly, the quality controls guarantee results have improved accuracy in reservoir prediction and stronger correlation coefficients with well data.

Investigation of the JPA-Bandwidth Improvement in the Performance of the QTMS Radar.

Josephson parametric amplifier (JPA) engineering is a significant component in the quantum two-mode squeezed radar (QTMS) to enhance, for instance, radar performance and the detection range or bandwidth. We simulated a proposal of using engineered JPA (EJPA) to enhance the performance of a QTMS radar. We defined the signal-to-noise ratio (SNR) and detection range equations of the QTMS radar. The engineered JPA led to a remarkable improvement in the quantum radar performance, i.e., a large enhancement in SNR of about 6 dB more than the conventional QTMS radar (with respect to the latest version of the QTMS radar and not to the classical radar), a substantial improvement in the probability of detection through far fewer channels. The important point in this work was that we expressed the importance of choosing suitable detectors for the QTMS radars. Finally, we simulated the transmission of the signal to the target in the QTMS radar and obtained a huge increase in the QTMS radar range, up to 482 m in the current study.

Resonating sub-wavelength metallic wires based pads for boosting signal-to-noise ratio of birdcage head coils at 1.5T MRI

Magnetic resonance imaging (MRI) is an increasingly popular non-invasive diagnostic imaging tool in modern healthcare. The signal-to-noise ratio (SNR) of MRI can be improved by locally enhancing radiofrequency (RF) magnetic field using metamaterials — without the need for stepping up static magnetic field strength. However, designing a thin and compact metamaterial-based structure for the most commonly used 1.5T MRI systems (operating at f0∼64MHz) remains highly challenging due to long vaccum wavelength λ0∼4.7m at resonance. The limited free space available inside MRI receive coil arrays (typically 10-20mm) restricts the practical usability of any bulky resonator (with dimensions in order of meters) inside commercial 1.5T MRI head transceiver-coils. In this paper, we design a thin and compact RF metamaterial-based pad comprising dual-layer wire-array resonators that fits in the available space and provides significant magnetic field enhancement at 1.5T MRI. The metamaterial-based pad provides the SNR enhancement by a factor of ∼19, on the surface of bio-model in contact with the pad, as compared to the case without pad while maintaining specific absorption rate well below the standard safety limit. We present an equivalent circuit approach combined with a transformer-based model to compute the SNR enhancement factor of metamaterial-based pad, which adequately explains the underlying physical mechanism of metamaterial’s magnetic resonance and closely estimates our numerical findings. We believe that, when integrated into the clinical 1.5T MRI systems, our proposed metamaterial-based pad can help improve the SNR of head MRI scans, resulting in either higher image quality or reduced scan time.

SNR enhanced high-speed two-photon microscopy using a pulse picker and time gating detection

Two-photon microscopy (TPM) is an attractive biomedical imaging method due to its large penetration depth and optical sectioning capability. In particular, label-free autofluorescence imaging offers various advantages for imaging biological samples. However, relatively low intensity of autofluorescence leads to low signal-to-noise ratio (SNR), causing practical challenges for imaging biological samples. In this study, we present TPM using a pulse picker to utilize low pulse repetition rate of femtosecond pulsed laser to increase the pulse peak power of the excitation source leading to higher emission of two-photon fluorescence with the same average illumination power. Stronger autofluorescence emission allowed us to obtain higher SNR images of arterial and liver tissues. In addition, by applying the time gating detection method to the pulse signals obtained by TPM, we were able to significantly reduce the background noise of two-photon images. As a result, our TPM system using the pulsed light source with a 19 times lower repetition rate allowed us to obtain the same SNR image more than 19 times faster with the same average power. Although high pulse energy can increase the photobleaching, we also observed that high-speed imaging with low total illumination energy can mitigate the photobleaching effect to a level similar to that of conventional illumination with a high repetition rate. We anticipate that this simple approach will provide guidance for SNR enhancement with high-speed imaging in TPM as well as other nonlinear microscopy.

Estimation of intelligent-based quality of service in terrestrial FSO links: A case of South Africa propagation paths

Free Space Optical (FSO) communication is one of the popular technologies’ dominants in the optical communication domain. Despite all the advantages, FSO links are grossly affected by severe atmospheric conditions such as fog, rain, snow, smoke, and dust or aerosol particles suspended in the air. Fog is one of the major challenges for free-space optics to achieve carrier-class availability and causes extreme attenuation. A 10-year (2010––2019) visibility data were obtained from the South African Weather Services (SAWS) with a special focus on Cape Town (–33.925° S, 18.424° E). This extracted and processed Cape Town data was used to estimate the needed fog-induced attenuation. The intelligent algorithm is rooted in the theory of Artificial Neural Networks (ANN) systems which intelligently control the sub-tropical climate conditions of the chosen region. The adopted network-based technique is capable to interact with ever-changing weather by generating appropriate improvements to the free space optical communication link quality of service for efficient services to the customers. In this study, an Intelligent Algorithm (IA) based on an Artificial Neural Network (ANN) has been utilized to improve the reliability of QoS that can satisfy customer SLAs and improve received signal over FSO communications. The results obtained by implementing the IA system indicates that the power transmitted range from 8 to 100 dB and the adjusted Signal to Noise Ratio (SNR) between 390–––420 dB at 650 nm optical wavelength, whereas the same trend could be observed when the optical wavelength of 1550 nm was applied. Subsequently, the model effectively estimated the automatic transmit power control for enhancement in SNR and resulting in better QoS at the receiving end, regardless of the related weather changes along with the transmission link.

Joint Transceiver Beamforming and Reflecting Design for Active RIS-Aided ISAC Systems

Integrated sensing and communication (ISAC) is recognized as a promising technology with great potential in saving hardware and spectrum resources, since it simultaneously realizes radar detection and user communication functions in the fully-shared platform. Employing reconfigurable intelligent surface (RIS) in ISAC systems is able to provide a virtual line-of-sight (LoS) path to conquer blockage problem as well as introduce new degrees of freedom (DoFs) to further enhance system performance. Nevertheless, the multiplicative fading effect of passive RIS limits its applications in the absence of direct links, which promotes the development of active RIS. In this paper, we consider an active RIS-assisted ISAC system and aim to jointly design the transmit beamformer, the active RIS reflection and the radar receive filter to maximize the radar output signal-to-noise ratio (SNR) while guaranteeing pre-defined signal-to-interference-plus-noise ratios (SINRs) for communication users. To solve for this non-convex problem, an efficient algorithm is developed by leveraging the techniques of block coordinate descent (BCD), Dinkelbach's transform and majorization-minimization (MM). Simulation results verify the significant advancement of deploying active RIS in ISAC systems, which can achieve up to 32 dB radar SNR enhancement compared with the passive RIS-assisted ISAC systems.

Self-Illuminating NIR-II Chemiluminescence Nanosensor for In Vivo Tracking H2 O2 Fluctuation.

Chemiluminescence (CL) imaging, as an excitation-free technique, exhibits a markedly improved signal-to-noise ratio (SNR) owing to the absence of an excitation light source and autofluorescence interference. However, conventional chemiluminescence imaging generally focuses on the visible and first near-infrared (NIR-I) regions, which hinders high-performance biological imaging due to strong tissue scattering and absorption. To address the issue, self-luminescent NIR-II CL nanoprobes with a second near-infrared (NIR-II) luminescence in the presence of hydrogen peroxide arerationally designed. A cascade energy transfer, including chemiluminescence resonance energy transfer (CRET) from the chemiluminescent substrate to NIR-I organic molecules and Förster resonance energy transfer (FRET) from NIR-I organic molecules to NIR-II organic molecules, occurs in the nanoprobes, contributing to NIR-II light with great efficiency and good tissue penetration depth. Based on excellent selectivity, high sensitivity to hydrogen peroxide, and long-lasting luminescence performance, the NIR-II CL nanoprobes areapplied to detect inflammation in mice, showing a 7.4-fold enhancement in SNR compared with that of fluorescence.

Phase correction based SNR enhancement for distributed acoustic sensing with strong environmental background interference

Fiber-optic distributed acoustic sensing (DAS) systems based on phase-sensitive optical time domain reflectometry (Φ-OTDR) measure acoustic waves by demodulating the phase variations of the Rayleigh backscattering (RBS) signals in a sensing optical fiber. However, in harsh environments, strong environmental background interference, coupled with the interference fading of the RBS, would introduce severe distortions in DAS signal that cannot be corrected or even can be worsened by phase unwrapping, thus resulting in low signal to noise ratio (SNR) and even undetectable signal. In this work, a novel method based on trend prediction is proposed to correct the distortions induced by phase unwrapping error around the fading points. The method is further validated in processing the data acquired from a field test performed in ocean environments using a home-built DAS system. By locating and erasing the distortion points, and then detrending, the acoustic signal buried in strong environmental background interference is retrieved with an SNR improvement greater than 10 dB. The results show that the proposed phase correction method can effectively enhance DAS's SNR for those challenging applications with strong background interference.

SNR Enhancement for BOTDR With Spatial-Adaptive Image Denoising Method

A spatial-adaptive image denoising (SAID) method is proposed to enhance the signal-to-noise ratio (SNR) of Brillouin optical time domain reflectometer (BOTDR) without deterioration of spatial resolution. Through analyzing the principle of denoising, the spatial-adaptive denoising network structure is constructed, which can effectively reduce noise and avoid over-smoothing. Moreover, a high-similarity dataset generation method is designed to further enhance the denoising effect. The SAID method is experimentally implemented on two-dimension Brillouin gain spectrum matrix over a 25.1 km-long optical fiber with the spatial resolution of 2 m. The experimental results show that the SNR enhancement of SAID method is 21.92 dB, and the data processing time is only 2.48 s. Whereas the SNR enhancement of conventional 10000 times trace averaging method is merely 9.98 dB, but the data processing time is increased to 174.52 s. Therefore, it is demonstrated that the SAID method has obvious advantages in SNR enhancement and data processing speed without deteriorating the spatial resolution of BOTDR.