A positioning method for a distributed fiber optic sensing system

Abstract

A positioning method for a distributed optical fiber sensing system, which eliminates the influence of the scale of the optical fiber sensing channel by phase correction of the signals collected by the optical fiber sensor array, and the corrected signals can directly use the array signal processing method to obtain high-precision target source position information. The method does not depend on the special design of the optical fiber winding structure, and is suitable for conventional buried communication optical cables. The present application has the advantages of simple implementation, low cost, wide range and high precision, and can further improve the positioning ability of the existing sensing system to the target signal in the actual application scene, and is suitable for railway safety, perimeter security, earthquake rapid reporting and other fields, and has great significance.

Description

Technical Field

[0001] This invention relates to the field of target source monitoring, specifically a positioning method for a distributed optical fiber sensing system. Background Technology

[0002] Distributed fiber optic sensors are widely used in railway safety monitoring, perimeter security, seismology, and other fields, all of which require high-precision positioning of target sources. Existing distributed fiber optic sensors only have one-dimensional detection capabilities, allowing for one-dimensional spatial positioning of target sources along the fiber optic line. They cannot accurately determine the spatial location of target sources located at a certain lateral distance from the fiber optic cable.

[0003] Existing technology 1 [Liang J, Wang Z, Lu B, et al. Distributed acoustic sensing for 2D and 3D acoustic source localization. Optics Letters, 2019] utilizes a densely wound optical fiber structure to locate airborne sound sources by compressing the aperture of the optical fiber array elements and using array signal processing. However, in practical applications, it is mostly based on conventional communication optical cables, which makes it difficult to achieve dense winding. The optical fiber sensing channel has a certain spatial scale, resulting in a wave field gradient distribution within the sensing channel, making it difficult to directly use array signal processing methods to achieve high-precision positioning.

[0004] Existing technology two [Liu Z, Zhang L, et al. Underwater acoustic source localization based on phase-sensitive optical time domain reflectionometry. Optics express, 2021] uses optical fibers wound around a 3D-printed elastic structure to form a sensor array. Based on the time difference of arrival (TDOA) algorithm, it utilizes the signal time delay of multiple sensing channels to achieve underwater sound source localization. However, for sound sources at long distances, the localization accuracy of a single TDOA algorithm is poor, making it impossible to achieve large-scale reliable applications using conventional optical cables. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, this invention proposes a positioning method for distributed optical fiber sensing systems. By correcting the phase deviation of the optical fiber array, high-precision positioning of the target source can be achieved using conventionally buried optical cables. This method is applicable to existing sensing systems and has the advantages of simple implementation, low cost, wide coverage, and high precision. It not only greatly improves the positioning capability of distributed optical fibers for abnormal signals in fields such as railway safety and perimeter security, but also broadens the application of distributed optical fibers in large-scale disturbance positioning, such as earthquake positioning and volcanic eruption positioning, thus possessing practical value.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] This invention proposes a positioning method for a distributed optical fiber sensing system, characterized in that the positioning method includes the following steps:

[0008] 1) The distributed optical fiber sensor transmits a probe light signal to the sensing optical fiber and receives the returned sampling signal S(l,t), where l represents the one-dimensional axial space of the sensing optical fiber and t represents the receiving time.

[0009] 2) Bandpass filtering is performed on the sampled signal S(l,t) according to the target source signal frequency band, and the signal amplitude is normalized;

[0010] 3) Select an optical fiber array aperture of length L within the aforementioned sensing optical fiber, and collect sampling signals from N sensing channels at intervals Δn within this optical fiber array aperture as the sampling signal group X(t)=[S(l1,t) S(l 1+Δn ,t) ... S(l 1+NΔn ,t)] T Where, l1 represents the starting position of the optical fiber array aperture on the optical fiber link;

[0011] 4) Select the first sensing channel as the reference sensing channel, and calculate the time delay 'a' of the sampled signal of each sensing channel within the aperture of the fiber array relative to the reference sensing channel. n (Δτ)=[Δτ 11 Δτ 21 ... Δτ N1 ] T Where n = 1, 2, ..., N, and N represents the number of sensor channels;

[0012] 5) Use the Time Difference of Arrival (TDOA) method to pre-estimate the target source location:

[0013] Take any two sampling signals from the two sensing channels mentioned in step 4) and use them to form an array element delay group Θ(Δτ)=[Δτ i1 Δτ j1] T Where 1≤i,j≤N and i≠j, the position of the target source relative to the reference sensor channel is estimated based on the arrival time delay difference method and the positional relationship between the sensor channels.

[0014] 6) Repeat step 5) to form K different time delay groups. Each time delay group estimates the position of the target source relative to the reference sensing channel. The average of the estimates for the K positions is: The final estimated location of the target source was obtained.

[0015] 7) Based on the estimated location of the target source Phase correction is performed on the sampled signal of the fiber optic sensing channel;

[0016] 8) The target source location is obtained by using array signal processing methods on the corrected sampled signal from 7).

[0017] Step 7) Based on the predicted location of the target source Phase correction is performed on the sampled signal of the fiber optic sensing channel, specifically including:

[0018] a) Calculate the phase deviation of the sampled signal for each sensing channel: For the i-th sensing channel, the phase of the sampled signal is the integral of the wave field along the axial length of the sensing channel, i.e. The N sensing channels of a sensing fiber can be equivalent to a sensor array, and the phase of the sampling signal of the equivalent sensing array can be expressed as:

[0019] b) Construct a uniform linear array by selecting the starting position of each sensing channel. The phase of the sampled signal of the i-th sensing channel within the uniform linear array is... Therefore, within the equivalent sensing array and the uniform linear array, for the i-th sensing channel, the phase deviation of the sampled signal is:

[0020] c) Correct the phase deviation of the equivalent sensor array. The corrected phase of the sampled signal of the equivalent sensor array is expressed as:

[0021] In step 3), the sensor channel spacing Δn and the number of sensor channels N need to be determined according to the specific application scenario requirements such as the frequency of the target source and the propagation speed of the medium.

[0022] In step 8), the array signal processing method is one of the following: beamforming algorithm, spatial spectrum estimation algorithm, or direction of arrival estimation algorithm.

[0023] The advantages and technical effects of this invention are as follows:

[0024] 1. This invention is applicable to existing distributed optical fiber systems. It can be implemented simply by utilizing sensing channels distributed along the optical fiber and processing the received signals. It is simple to implement and has a low cost.

[0025] 2. This invention does not rely on a specially wound optical fiber structure and is applicable to buried communication cables or sparsely wound optical cables in practical applications, thus possessing practicality. By estimating the target source location and performing phase correction of the optical fiber sampling signal, the positioning accuracy is high. Therefore, this invention not only greatly improves the ability of distributed optical fiber sensors to locate abnormal signals in fields such as railway safety and perimeter security, but also broadens the application of distributed optical fiber sensors in large-scale disturbance positioning, such as earthquake positioning and volcanic eruption positioning. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a distributed optical fiber sensing system.

[0027] Figure 2 This is a flowchart of the positioning method for a distributed optical fiber sensing system according to the present invention. Detailed Implementation

[0028] The present invention will be further described below with reference to the accompanying drawings and embodiments, but is not limited thereto. Several implementation methods can be adopted according to the concept of the present invention. The following schemes are only for illustrative purposes, and the specific schemes are not limited thereto. Furthermore, for ease of description, only the parts relevant to the present invention are shown in the accompanying drawings, not the entire process.

[0029] Please see Figure 1 , Figure 1 This is a schematic diagram of a distributed optical fiber sensing system. As shown in the figure, the distributed optical fiber sensing system includes a distributed optical fiber sensor 1 and a sensing optical fiber 5.

[0030] Please see Figure 2 , Figure 2 This is a flowchart of the positioning method for a distributed optical fiber sensing system according to the present invention. As shown in the figure, a positioning method for a distributed optical fiber sensing system includes the following steps:

[0031] 1) The distributed optical fiber sensor 1 transmits a probe light signal to the sensing optical fiber 5 and receives the returned sampling signal S(l,t), where l represents the one-dimensional axial space of the sensing optical fiber and t represents the receiving time.

[0032] 2) Bandpass filtering is performed on the sampled signal S(l,t) according to the frequency band of the target source 2 signal, and the signal amplitude is normalized;

[0033] 3) Within the sensing fiber optic cable 5, select an optical fiber array aperture 6 of length L. Within the optical fiber array aperture 6, take N sampling signals collected by sensing channels 3 at intervals Δn as the sampling signal group X(t)=[S(l1,t) S(l 1+Δn ,t) ...S(l 1+NΔn ,t)] T Where, l1 represents the starting position of the optical fiber array aperture 6 on the sensing optical fiber 5;

[0034] 4) Select the first sensing channel as the reference sensing channel 7, and calculate the time delay 'a' of the sampling signal of each sensing channel within the aperture 6 of the fiber array relative to the reference sensing channel 7. n (Δτ)=[Δτ 11 Δτ 21 ... Δτ N1 ] T Where n = 1, 2, ..., N, and N represents the number of sensor channels;

[0035] 5) The location of target source 2 is pre-estimated using the time difference of arrival method:

[0036] Take the time delay Δτ of the two sensing channels in step 4). 21 and Δτ 31 This forms a time delay group Θ(Δτ)=[Δτ 21 Δτ 31 ] T Based on the arrival time delay difference method and the positional relationship between the sensing channels, the position of target source 2 relative to reference array element channel 7 is estimated.

[0037] 6) Repeat step 5), selecting a total of 4 different time delay groups, namely Θ(Δτ)=[Δτ 21 Δτ 31 ] T ,Θ(Δτ)=[Δτ 31 Δτ 51 ] T ,Θ(Δτ)=[Δτ 41 Δτ 71 ] T ,Θ(Δτ)=[Δτ 51 Δτ 91 ] T Each time delay group estimates the position of target source 2 relative to reference array element channel 7. The average of the estimates from the four positions is: The final estimated location of target source 2 was obtained.

[0038] 7) Based on the estimated location of the target source 2 Phase correction is performed on the sampled signal of the fiber optic sensing channel 3:

[0039] 8) The target source is located using array signal processing methods on the corrected sampled signal;

[0040] In step 7), the location is estimated based on the target source 2. Phase correction is performed on the sampled signal of the fiber optic sensing channel 3, specifically including:

[0041] a) Calculate the phase deviation of the sampled signal for each sensing channel: For the i-th sensing channel, the phase of the sampled signal is the integral of the wave field along the axial length of the sensing channel, i.e. The N sensing channels of the sensing fiber 5 can be equivalent to a sensor array, and the phase of the equivalent sensing array 8 can be expressed as:

[0042] b) A uniform linear array 4 is constructed by selecting the starting position of each sensing channel. The phase of the sampled signal of the i-th sensing channel within the uniform linear array is... Therefore, within the equivalent sensing array 8 and the uniform linear array 4, for the i-th sensing channel, the phase deviation of the sampled signal is:

[0043] c) Correct the phase deviation of the equivalent sensor array 8. The corrected phase of the sampled signal of the equivalent sensor array 8 is expressed as:

[0044] In step 2), the spacing Δn between the sensing channels 3 and the number N of the sensing channels 3 need to be determined according to the specific application scenario requirements such as the frequency of the target source 2 and the propagation speed of the medium.

[0045] In step 6), the array signal processing method is one of the following: beamforming algorithm, spatial spectrum estimation algorithm, or direction of arrival estimation algorithm.

Claims

1. A positioning method for a distributed optical fiber sensing system, the distributed optical fiber sensing system comprising distributed optical fiber sensors and sensing optical fibers, characterized in that, The positioning method includes the following steps: Step S1. The distributed optical fiber sensor transmits a probe light signal to the sensing optical fiber and receives the returned sampling signal. ,in, This represents the one-dimensional axial space of the sensing fiber. Indicates the receiving time; Step S2. Sample the signal Bandpass filtering is performed on the target source signal frequency band, and the signal amplitude is normalized. Step S3. Select an optical fiber array aperture of length L within the sensing optical fiber, and within this optical fiber array aperture, spaced at intervals... Take the sampling signals collected from N sensor channels as the sampling signal group ,in, This indicates the starting position of the optical fiber array aperture on the optical fiber link; Step S4. Select the first sensing channel as the reference sensing channel and calculate the time delay of the sampled signal of each sensing channel within the aperture of the fiber array relative to the reference sensing channel. ,in, , Indicates the number of sensor channels; Step S5. Use the time difference of arrival method to pre-estimate the target source location: Arbitrarily select the time delay of the sampling signals from the two sensing channels in step S4 to form a time delay group. ,in and Based on the time-delay method and the positional relationship between sensor channels, the position of the target source relative to the reference sensor channel is estimated. ; Step S6. Repeat step S5 to form K different time delay groups. Each time delay group estimates the position of the target source relative to the reference sensing channel. The average of the estimates for the K positions is calculated as follows: , The final estimated location of the target source is obtained. ; Step S7. Estimate the location based on the target source. Phase correction is performed on the sampled signal of the fiber optic sensing channel; Step S8. Use array signal processing methods to locate the target source for the corrected sampled signal.

2. The positioning method for a distributed optical fiber sensing system according to claim 1, characterized in that, S7. Based on the predicted location of the target source. Phase correction is performed on the sampled signal of the fiber optic sensing channel, specifically including: S7.1 Calculate the phase deviation of the sampled signal for each sensing channel: For the i-th sensing channel, the phase of the sampled signal is the integral of the wave field along the axial length of the sensing channel, i.e. The N sensing channels of the sensing fiber can be equivalent to a sensor array, and the sampling signal phase of the equivalent sensor array can be expressed as: ; S7.2 A uniform linear array is constructed by selecting the starting position of each sensing channel. The phase of the sampled signal of the i-th sensing channel within the uniform linear array is... Therefore, within the equivalent sensing array and the uniform linear array, for the i-th sensing channel, the phase deviation of the sampled signal is: ; S7.3 corrects the phase deviation of the equivalent sensing array. The corrected phase of the sampled signal of the equivalent sensing array is expressed as follows: .

3. The positioning method for a distributed optical fiber sensing system as described in claim 1, characterized in that, The sensing channel spacing in step S3 The number of sensing channels N needs to be determined based on the frequency of the target source, the propagation speed of the medium, and the specific application scenario requirements.

4. The distributed optical fiber high-precision positioning method based on array phase correction as described in claim 1, characterized in that, The array signal processing method in step S8 is one of the following: beamforming algorithm, spatial spectrum estimation algorithm, and direction of arrival estimation algorithm.

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