Interference fading point compensation method for coherent phi-OTDR

Abstract

The invention discloses an interference fading point compensation method for a coherent phi-OTDR (Optical Time Domain Reflectometer), which comprises the following steps of: identifying an interference fading point on the basis of complex envelope characteristics obtained by coherent receiving and I / Q (Input / Output) demodulation, and performing interpolation reconstruction on a fading point echo vector by using a neighborhood non-fading point on a complex plane, so as to recalculate a phase and a differential phase; therefore, phase demodulation failure and differential phase artifacts caused by fading can be suppressed. According to the method, on the premise of not increasing hardware transformation, differential phase artifacts and abnormal stripes caused by phase demodulation failure at a fading point are reduced, the stability of a differential phase result and event identifiability are improved, and relatively low calculation complexity is kept to adapt to offline or quasi-real-time processing.

Description

Technical Field

[0001] This invention belongs to the field of acoustic sensing technology, specifically a method for compensating for interference fading points in coherent Φ-OTDR. Background Technology

[0002] Distributed acoustic sensing systems utilize optical fibers as a distributed sensing medium to locate and recover waveforms of vibration disturbances along a line. Coherent Φ-OTDRs typically obtain the I / Q components of the Rayleigh backscattered signal through coherent reception, and perform phase demodulation and differential phase calculation at the data processing end to achieve quantitative measurement of external disturbances.

[0003] In practical systems, due to the randomness of the superposition of multiple scatterer vectors within the resolving unit, destructive interference can occur at certain locations, leading to a significant decrease in echo amplitude. These locations are referred to as interference fading points. At interference fading points, the signal amplitude is close to the noise floor, making phase estimation highly sensitive to noise. The demodulated phase is easily dominated by noise, resulting in abnormal fringes or background artifacts in the differential phase waterfall plot, affecting event readability and introducing false alarms.

[0004] In existing technologies, common approaches to mitigate the effects of fading include multi-frequency detection or frequency division multiplexing, polarization diversity, introducing additional hardware structures to improve echo stability, and compensation methods based on machine learning models. However, these methods often lead to increased system complexity and cost, or impose higher requirements on real-time performance and engineering deployment.

[0005] Disadvantages of existing technology: When relying on multi-frequency / diversity solutions, it is necessary to increase light source frequency planning, channel synthesis and synchronization control, which increases system complexity and cost.

[0006] Some hardware modification solutions have high requirements for optical path stability, device consistency, and on-site maintenance, which is not conducive to rapid deployment.

[0007] Machine learning methods typically require a large amount of training data and computing power, and their robustness and interpretability are uncertain in engineering scenarios.

[0008] Without additional processing, phase demodulation failure caused by fading points will manifest as fixed-position artifacts or abnormal fringes in the differential phase results, reducing the reliability of event identification and increasing the risk of false alarms. Summary of the Invention

[0009] To address the deficiencies and shortcomings mentioned in the prior art, this invention provides an interferometric fading point compensation method for coherent Φ-OTDR. Without increasing hardware modifications, it reduces differential phase artifacts and anomalous fringes caused by phase demodulation failures at fading points, improves the stability and event identifiability of differential phase results, and maintains low computational complexity to adapt to offline or near real-time processing.

[0010] To achieve the above objectives, the present invention provides the following technical solution: an interference fading point compensation method for coherent Φ-OTDR, which is based on the complex envelope characteristics obtained by coherent reception and I / Q demodulation. By identifying interference fading points and using neighborhood non-fading points on the complex plane to interpolate and reconstruct the fading point echo vector, the phase and differential phase are recalculated to suppress phase demodulation failure and differential phase artifacts caused by fading.

[0011] An interferometric fading point compensation method for coherent Φ-OTDR, the specific steps of which are as follows: Step S1: Obtain the I / Q discrete sampling sequence of the coherent Φ-OTDR echo, and represent it as a complex signal s(z,t)=I(z,t)+jQ(z,t) at each distance sampling point z and slow time sampling point t; Step S2: The interference fading point appears as a local concave in the amplitude distribution. Calculate the amplitude A(z,t)=|s(z,t)| and construct a local baseline A_base(z,t) on the distance axis to characterize the slow-varying attenuation and average level of the distance dimension. Step S3: Calculate the normalized amplitude ratio R(z,t)=A(z,t) / A_base(z,t); when R(z,t) is lower than the preset threshold γ, mark the corresponding distance position as the interference fading point to form the fading point set F; Step S4: For each fading point z f Search for the nearest non-fading point z to the left and right on the distance axis, respectively. L With z R Alternatively, a neighborhood set can be formed by searching for several nearest non-fading points to provide a basis for phase constraints and interpolation reconstruction. Step S5: At each slow time sample t, reconstruct the complex signal of the fading point based on the neighborhood non-fading points; Step S6: For the compensated complex signal s c Phase calculation is performed on (z,t) φ(z,t) = arg(s c (z,t)) and complete phase unwrapping and differential phase calculation according to the existing process, output differential phase waterfall plot or time series results for event identification and localization.

[0012] Preferably, the local baseline A_base(z,t) in step S2 is obtained through local statistics.

[0013] Preferably, the preset threshold γ in step S3 is an adaptive threshold γ(z) or γ(t), which can be determined by the statistics of the amplitude ratio R(z,t) within the distance sliding window.

[0014] Preferably, the statistic for the amplitude ratio R(z,t) within the sliding window is a quantile, the mean plus or minus the standard deviation, or a robust statistic.

[0015] Preferably, the complex signal reconstruction in step S5 employs complex plane linear interpolation: ŝ(z f ,t)=s(z L ,t)+((z f -z L ) / (z R -z L ))·(s(z R ,t)−s(z L ,t)), and use ŝ(z f ,t) replace the original s(z) f ,t), to obtain the compensated complex signal sequence s c (z,t).

[0016] Preferably, in step S5, the complex signal reconstruction uses weighted interpolation, spline interpolation, or multi-point least squares fitting. The neighborhood points can be expanded to the K nearest non-fading points on both sides of the distance axis, and the neighborhood points are weighted according to the magnitude, coherence, or noise estimation.

[0017] Compared with the prior art, the beneficial effects of the present invention are: By reconstructing the echo vector at the fading point in the complex plane, the effective amplitude at the fading point is increased, and the sensitivity of phase estimation to noise is reduced, thereby suppressing anomalous fringes and background artifacts in the differential phase results.

[0018] This method does not require changes to the original optical path structure and front-end hardware, and can be directly deployed in existing coherent Φ-OTDR data processing workflows.

[0019] Interpolation compensation only performs local calculations on the set of fading points, resulting in low computational and storage overhead, making it suitable for offline or near real-time processing of long-distance data.

[0020] 4. Under the experimental conditions, the vibration trajectory position was compared with the representative fading position. The signal-to-noise ratio before compensation was 15.70 dB, and after compensation it was increased to 28.05 dB, an increase of 12.35 dB, indicating that the fading-induced artifact fluctuations were significantly suppressed. Attached Figure Description

[0021] Figure 1 This is a block diagram of the coherent Φ-OTDR system structure in this invention; Figure 2 This is a schematic diagram of interference fading point identification in this invention; Figure 3 This is the differential phase waterfall diagram before compensation in this invention; Figure 4 This is a flowchart of the neighborhood interpolation compensation process in this invention; Figure 5 This is the differential phase waterfall diagram after compensation in this invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1

[0023] The present invention provides an interference fading point compensation method for coherent Φ-OTDR. Based on the complex envelope characteristics obtained by coherent reception and I / Q demodulation, the method identifies interference fading points and reconstructs the fading point echo vector by interpolation using neighborhood non-fading points on the complex plane. Then, the phase and differential phase are recalculated to suppress phase demodulation failure and differential phase artifacts caused by fading.

[0024] As shown in Figure 4, an interference fading point compensation method for coherent Φ-OTDR according to the present invention includes steps S1–S6. Step S1: Obtain the I / Q discrete sampling sequence of the coherent Φ-OTDR echo, and represent it as a complex signal s(z,t)=I(z,t)+jQ(z,t) at each distance sampling point z and slow time sampling point t. The structure of the coherent Φ-OTDR system is shown in Figure 1.

[0025] Step S2: The interference fading point exhibits a local concave pattern in the amplitude distribution, as shown in Figure 2. Calculate the amplitude A(z,t) = |s(z,t)|, and construct a local baseline A_base(z,t) on the distance axis to characterize the slowly varying attenuation and average level of the distance dimension. The baseline can be obtained through local statistics.

[0026] Step S3: Calculate the normalized amplitude ratio R(z,t) = A(z,t) / A_base(z,t). When R(z,t) is lower than the preset threshold γ, mark the corresponding distance position as the interference fading point to form the fading point set F.

[0027] Step S4: For each fading point zf Search for the nearest non-fading point z to the left and right on the distance axis, respectively. L With z R Alternatively, a neighborhood set can be formed by searching for several nearest non-fading points to provide a basis for phase constraints and interpolation reconstruction.

[0028] Step S5: At each slow time sample t, reconstruct the complex signal of the fading point based on the neighborhood non-fading points. Complex plane linear interpolation is preferably used: ŝ(z f ,t)=s(z L ,t)+((z f -z L ) / (z R -z L ))·(s(z R ,t)−s(z L ,t)), and use ŝ(z f ,t) replace the original s(z) f ,t), to obtain the compensated complex signal sequence s c (z,t).

[0029] Step S6: For the compensated complex signal s c Phase calculation is performed on (z,t) φ(z,t) = arg(s c (z,t)) and completes phase unwrapping and differential phase calculation according to the existing process, outputting differential phase waterfall plots or time series results for event identification and localization. The comparison of differential phase waterfall plots before and after compensation is shown in Figure 3 and Figure 5. Example 2

[0030] In step S3 of Example 1, the fixed preset threshold γ is replaced with an adaptive threshold γ(z) or γ(t), which can be determined by a statistic of the amplitude ratio R(z,t) within the distance sliding window, such as quantiles, mean plus or minus standard deviation, or robust statistics.

[0031] In situations where there is significant distance attenuation, large differences in noise levels across different distance segments, or uneven echo amplitude fluctuations, adaptive thresholding can reduce false positives and false negatives, making the set of fading points F more consistent with the actual fading distribution. It can adapt to attenuation and amplitude fluctuations at different distances, reducing false positives and false negatives and enhancing robustness over long-distance links. Example 3

[0032] In step S5 of Example 1, linear interpolation is replaced with weighted interpolation, spline interpolation, or multi-point least squares fitting. The neighborhood points can be expanded to the K nearest non-fading points on both sides of the distance axis, and the neighborhood points are weighted according to the magnitude, coherence, or noise estimation.

[0033] When there are nonlinear changes or local waveform distortions in the neighborhood of the fading point, a smoother or more fitting reconstruction effect can be obtained, further reducing artifact residue.

[0034] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for compensating for interferometric fading points in coherent Φ-OTDR, characterized in that: This interference fading point compensation method is based on the complex envelope characteristics obtained from coherent reception and I / Q demodulation. It identifies interference fading points and uses neighborhood non-fading points on the complex plane to interpolate and reconstruct the fading point echo vector, thereby recalculating the phase and differential phase to suppress phase demodulation failure and differential phase artifacts caused by fading.

2. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 1, characterized in that: The specific steps are as follows: Step S1: Obtain the I / Q discrete sampling sequence of the coherent Φ-OTDR echo, and represent it as a complex signal s(z,t)=I(z,t)+jQ(z,t) at each distance sampling point z and slow time sampling point t; Step S2: The interference fading point appears as a local concave in the amplitude distribution. Calculate the amplitude A(z,t)=|s(z,t)| and construct a local baseline A_base(z,t) on the distance axis to characterize the slow-varying attenuation and average level of the distance dimension. Step S3: Calculate the normalized amplitude ratio R(z,t)=A(z,t) / A_base(z,t); when R(z,t) is lower than the preset threshold γ, mark the corresponding distance position as the interference fading point to form the fading point set F; Step S4: For each fading point z f Search for the nearest non-fading point z to the left and right on the distance axis, respectively. L With z R Alternatively, a neighborhood set can be formed by searching for several nearest non-fading points to provide a basis for phase constraints and interpolation reconstruction. Step S5: At each slow time sample t, reconstruct the complex signal of the fading point based on the neighborhood non-fading points; Step S6: For the compensated complex signal s c Phase calculation is performed on (z,t) φ(z,t) = arg(s c (z,t)) and complete phase unwrapping and differential phase calculation according to the existing process, output differential phase waterfall plot or time series results for event identification and localization.

3. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 2, characterized in that: In step S2, the local baseline A_base(z,t) is obtained through local statistics.

4. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 2, characterized in that: In step S3, the preset threshold γ is an adaptive threshold γ(z) or γ(t), which can be determined by the statistics of the amplitude ratio R(z,t) within the distance sliding window.

5. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 4, characterized in that: The statistic for the amplitude ratio R(z,t) within the sliding window is the quantile, the mean plus or minus the standard deviation, or a robust statistic.

6. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 1, characterized in that: In step S5, the complex signal reconstruction employs complex plane linear interpolation: ŝ(z f ,t)=s(z L ,t)+((z f -z L ) / (z R -z L ))·(s(z R ,t)−s(z L ,t)), and use ŝ(z f ,t) replace the original s(z) f ,t), to obtain the compensated complex signal sequence s c (z,t).

7. The method for compensating for interference fading points in coherent Φ-OTDR according to claim 6, characterized in that: In step S5, the complex signal reconstruction uses weighted interpolation, spline interpolation, or multi-point least squares fitting. The neighborhood points can be expanded to the K nearest non-fading points on both sides of the distance axis, and the neighborhood points are weighted according to the magnitude, coherence, or noise estimation.

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