A real-time positioning method and device for an intruding sound source target

Abstract

The application discloses a kind of real-time positioning method and device of intruding sound source target, belong to acoustic wave detection field.The real-time positioning method includes using distributed acoustic wave sensing optical cable to construct detection network, obtains the acoustic wave signal and its power spectral density characteristics of intruding sound source target from detection network, can further obtain the time difference of acoustic wave to each sensing channel after filtering, according to the maximum value of time difference, construct pseudo-random number of Gaussian distribution and introduce it to time difference, and the corresponding intruding sound source target position estimation value can be obtained by calculation, the estimation value with the highest occurrence probability is obtained as the final intruding sound source target position by repeating calculation, the detection and positioning of intruding sound source target in network are realized.The problem that environmental noise influence cannot be eliminated in the prior art, leading to the problem that accurate and rapid positioning of intruding sound source target cannot be realized, the real-time, detection range and positioning accuracy of intruding sound source target are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of acoustic wave detection, and more specifically, relates to a method and apparatus for real-time localization of intrusive acoustic source targets. Background Technology

[0002] Perimeter security is of great military significance and requires detection technologies with high sensitivity, wide monitoring range, and real-time response. Intrusion sound sources are a major aspect of perimeter security, placing even higher demands on detection technologies. Currently, the main monitoring methods for intrusion sound sources are manual inspections and camera video surveillance. These technologies suffer from limitations such as small monitoring range, low efficiency, and susceptibility to weather conditions, failing to adequately guarantee perimeter security. Therefore, a real-time location method for intrusion sound sources is urgently needed for early warning.

[0003] To support the growth of internet traffic, telecommunications operators have deployed large-scale fiber optic cables. Distributed fiber optic acoustic sensing technology, as a new type of sensing technology, uses fiber optic cables as the sensing medium to monitor vibration events. It has advantages such as high sensitivity, wide monitoring coverage, online real-time response, strong anti-electromagnetic interference capability, and resistance to harsh environments. This technology effectively utilizes existing fiber optic cable resources, saving a significant portion of hardware costs, and has been reported to be applied in fields such as traffic monitoring.

[0004] Among the existing publicly available technologies for locating intrusion sound sources, patent CN115902786A employs a dual-system microphone array and different sound source localization schemes, resulting in a complex system structure, high cost, and poor real-time performance. Patent CN113484865B uses a particle swarm optimization algorithm whose convergence speed and accuracy are affected by various factors, and the algorithm may get stuck in local optima, affecting the accuracy and reliability of localization. Patent CN117148272A uses machine learning for sound source localization, which has high requirements for datasets and hardware, is computationally complex, and is not suitable for real-time sound source localization in complex environments. Patent CN116972955A uses distributed fiber optic acoustic wave sensing technology to locate low-altitude UAVs, but the parameters used for localization are greatly affected by wind noise, resulting in limited localization accuracy.

[0005] In summary, distributed fiber optic acoustic sensing technology can convert existing communication fiber optic cable resources into sensor arrays for large-scale monitoring of external vibration events. Environmental noise and other factors will become the main factors affecting positioning accuracy. Existing technologies make it difficult to reduce the impact of environmental noise in real time, which makes it impossible to achieve accurate and rapid positioning of intrusion sound source targets. Summary of the Invention

[0006] In view of the shortcomings of related technologies, the present invention aims to provide a real-time location method and device for intrusion sound source targets, which aims to improve the monitoring range, applicable environment, accuracy and real-time performance of reconnaissance and location of intrusion sound sources.

[0007] To achieve the above objectives, in a first aspect, the present invention provides a method for real-time localization of an intrusion sound source target, comprising:

[0008] S1. Divide the acoustic wave sensing optical cable of the area to be tested into M sensing channels, and obtain the acoustic wave signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3.

[0009] S2. Based on the power spectral density characteristics of the acoustic signal, determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed, filter the acoustic signal detected by each sensor channel using this frequency band range, and divide the filtered signal into frames.

[0010] S3. Let n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames;

[0011] S4. Select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels;

[0012] S5. Based on the relational formula The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N ]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, D m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal;

[0013] S6. Let n = n + 1, and repeat steps S3-S5 until n is greater than N, thereby traversing all frame signals and obtaining N sets of location information of the intrusion sound source target.

[0014] S7. Update the referenced pseudo-random number. Repeat steps S3-S6 L-1 times to obtain L×N sets of location information A of the intrusion sound source targets. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1;

[0015] S8. Obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

[0016] Optionally, step S4 includes:

[0017] S41, the spatial distance from the intrusion sound source target to the m-th sensing channel is... The relationship between the spatial distance from the intrusion sound source target to the sensing channel and the time difference of sound wave arrival is as follows: The spatial location of the intrusion sound source target is [X0, Y0, Z0], and the spatial location of the m-th sensing channel is [X... m ,Y m Z m D1 represents the spatial distance between the intrusion sound source target and the reference channel. m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For ideal sound wave propagation speed;

[0018] S42, according to and Constructing computational equation G n a n =b n ;

[0019] in,

[0020] S43. Solve the equation in step S42 to obtain the location information of the intrusion sound source target, a = [a1…a2]. n …a N ];in, H represents the conjugate transpose of the matrix.

[0021] Optionally, the acoustic wave sensing optical cable is one of a single-mode optical cable, a multi-mode optical cable, a discrete scattering enhanced microstructure optical cable, or a spirally wound acoustic pressure sensitizing optical cable.

[0022] Optionally, the length of the sensing channel on the acoustic wave sensing optical cable is greater than or equal to the minimum spatial resolution of the connected acoustic wave sensing system; except for the sensing channels located at the beginning and end of the acoustic wave sensing optical cable, the lengths of the other sensing channels are equal.

[0023] Optionally, the step of framing the filtered signal includes:

[0024] The T-second acoustic wave signal acquired by each sensor channel is divided into frames of ti seconds to obtain N frames of signal; wherein the length of each frame of signal is greater than or equal to the minimum time sampling interval of the acoustic wave signal, and the length of the other frames of signal is equal except for the last frame.

[0025] Optionally, the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame signal can be calculated using any of the following methods: generalized cross-correlation, Kalman filtering, least mean square error adaptive filtering, or machine learning. n .

[0026] Optionally, the pseudo-random numbers that exhibit a Gaussian distribution The arrival time difference τ calculated based on the nth frame signal n The maximum value is constructed to obtain, where, The mean and standard deviation are 0 and 0.15, respectively.

[0027]

[0028] Secondly, the present invention provides a real-time positioning device for an intrusion sound source target, comprising:

[0029] The acoustic signal acquisition module is used to divide the acoustic sensing optical cable of the area to be tested into M sensing channels, and acquire the acoustic signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3.

[0030] The acoustic signal processing module is used to determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed based on the power spectral density characteristics of the acoustic signal, filter the acoustic signals detected by each sensor channel in this frequency band range, and divide the filtered signal into frames.

[0031] The configuration module is used to set n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames;

[0032] The time difference calculation module is used to select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels;

[0033] The location information prediction module is used to predict the location information based on the relational formula. The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N ]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, Dm v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal;

[0034] The repeated calculation module is used to set n = n + 1 and repeatedly execute the steps of the setting module - location information estimation module until n is greater than N, thereby realizing the traversal of all frame signals and obtaining N sets of location information of the intrusion sound source target;

[0035] The location information calculation module is used to update the referenced pseudo-random numbers. Repeat step L-1 of the setting module-repetitive calculation module to obtain L×N sets of location information A of the intrusion sound source target. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1;

[0036] The real-time tracking module is used to obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

[0037] Compared with existing technologies, the above-described technical solution of this invention achieves the following beneficial effects: This invention provides a real-time localization method for intrusive sound source targets. It utilizes a highly sensitive distributed acoustic wave sensing optical cable to construct multiple sensing channels, forming a detection network to detect and locate intrusive sound source targets in the network under test. The acoustic wave signal and its power spectral density characteristics of the intrusive sound source target are obtained from the detection network. After filtering, the time difference of the sound wave arriving at each sensing channel can be obtained. A Gaussian-distributed pseudo-random number is constructed and introduced into the time difference, allowing for the calculation of the corresponding estimated location information of the intrusive sound source target. The pseudo-random number efficiently compensates for the time-domain parameters used in localization, avoiding local optima and enhancing the accuracy of the localization results. Repeated calculations are performed to obtain the location information estimate with the highest probability of occurrence as the final location of the intrusive sound source target. This effectively improves the real-time performance of intrusive sound source target localization, expands the detection range, makes it applicable to complex environments, and improves localization accuracy. Attached Figure Description

[0038] Figure 1 A flowchart illustrating a real-time localization method for an intrusion sound source target provided by the present invention;

[0039] Figure 2 This invention provides a method for laying optical cables;

[0040] Figure 3This invention provides a time-domain acoustic signal and its power spectral density curve for a targetless acoustic source.

[0041] Figure 4 This invention provides the acoustic time-domain signal and its power spectral density curve of a target with an intrusive sound source;

[0042] Figure 5 These are the frame time-domain signals of several sensing channels provided by this invention;

[0043] Figure 6 This is the final location estimation result of the intrusion sound source target provided by the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0045] The following description, in conjunction with a preferred embodiment, illustrates the content involved in the above embodiments.

[0046] Example 1

[0047] like Figure 1 As shown, the present invention provides a real-time localization method for an intrusion sound source target, comprising:

[0048] S1. Divide the acoustic wave sensing optical cable of the area to be tested into M sensing channels, and obtain the acoustic wave signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3.

[0049] S2. Based on the power spectral density characteristics of the acoustic signal, determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed, filter the acoustic signal detected by each sensor channel using this frequency band range, and divide the filtered signal into frames.

[0050] S3. Let n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames;

[0051] S4. Select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels;

[0052] S5. Based on the relational formula The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N ]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, D m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal;

[0053] S6. Let n = n + 1, and repeat steps S3-S5 until n is greater than N, thereby traversing all frame signals and obtaining N sets of location information of the intrusion sound source target.

[0054] S7. Update the referenced pseudo-random number. Repeat steps S3-S6 L-1 times to obtain L×N sets of location information A of the intrusion sound source targets. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1;

[0055] S8. Obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

[0056] like Figure 1 As shown, a highly sensitive acoustic wave sensing optical cable is first laid in the area to be tested, and then connected to a distributed optical fiber acoustic wave sensing system using connecting optical fibers. Distributed optical fiber acoustic wave sensing technology is used to acquire the acoustic wave signals from each sensing channel on the sensing optical cable. The sensing channels form a detection network, which acquires the acoustic wave signals from the entire area to be tested. The acoustic wave sensing optical cable can utilize existing optical cables or be newly laid as needed. Phase-sensitive optical time-domain reflectometry is used to acquire the acoustic wave signals from each sensing channel on the sensing optical cable.

[0057] Optionally, the acoustic wave sensing optical cable is one of a single-mode optical cable, a multi-mode optical cable, a discrete scattering enhanced microstructure optical cable, or a spirally wound acoustic pressure sensitizing optical cable.

[0058] Specifically, the real-time localization method for an intrusion sound source target provided by this invention is deployed as follows: Figure 2 As shown.

[0059] In the embodiments provided by the present invention, the acoustic sensing optical cable is a 3m interval discrete scattering enhanced microstructure optical cable, which is laid in a 10cm underground pipe, and can realize two-dimensional positioning of the intrusion sound source target.

[0060] When multiple sensing channels are divided on the acoustic sensing optical cable, the length of the sensing channel is greater than or equal to the minimum spatial resolution of the connected acoustic sensing system; except for the sensing channels located at the beginning and end of the acoustic sensing optical cable, the lengths of the other sensing channels are equal.

[0061] In the embodiments provided by the present invention, the minimum spatial resolution of the acoustic wave sensing system is 0.6m, and the length of the divided sensing channels is 3m.

[0062] Furthermore, the deployed acoustic sensing optical cable is divided into M sensing channels, denoted as C. m , where m is the sensor channel number.

[0063] Obtain the power spectral density P of the acoustic signal from the m-th sensing channel after T seconds. m The acoustic signals detected by each sensor channel are filtered according to the frequency band range where the energy of the intrusion sound source target signal is mainly distributed. The filtered signals are then framed, specifically as follows:

[0064] When there is no intrusive sound source target in the area to be tested, the power spectral density feature P of the sound wave signal acquired by the m-th sensing channel is obtained. m1 ;

[0065] When an intrusive sound source target exists in the area to be measured, the power spectral density characteristic P of the sound wave signal acquired by the m-th sensing channel is obtained. m2 ;

[0066] Based on the power spectral density characteristics of the target where there is no intrusive sound source, P m1 The power spectral density characteristics of the intrusion sound source target P exist. m2 The frequency band range of the intrusion sound source target [f] is obtained. b1 ~f b2 ]; with [f b1 ~f b2 The acoustic wave signals detected by each sensor channel are bandpass filtered to obtain the filtered signal.

[0067] The filtering methods include any one of bandpass filtering, lowpass filtering, adaptive filtering, or machine learning.

[0068] In the embodiments provided by the present invention, by Figure 3 and Figure 4 It can be seen that the energy of the acoustic signal of the intrusion sound source is mainly distributed in the frequency band range [20Hz~200Hz]. A bandpass filter with a passband of [20Hz~200Hz] is used to filter the acoustic signals acquired by each sensor channel.

[0069] Optionally, the step of framing the filtered signal includes:

[0070] The T-second acoustic wave signal acquired by each sensor channel is divided into frames of ti seconds to obtain N frames of signal; wherein the length of each frame of signal is greater than or equal to the minimum time sampling interval of the acoustic wave signal, and the length of the other frames of signal is equal except for the last frame.

[0071] Specifically, in the embodiments provided by the present invention, the minimum time sampling interval for the acoustic wave signal by the acoustic wave sensing system is 0.1 ms, and the length of each signal frame is 1 s. Figure 5 It is a frame time-domain signal of several sensing channels.

[0072] Furthermore, step S4 specifically includes:

[0073] S41. Select the first sensing channel as the reference channel, and calculate the time difference between the arrival time of the sound wave at the reference channel and other sensing channels in the same frame of signal. Where n is the frame number, n is less than or equal to N, N is the total number of frames, m is the sensor channel number, and M is the total number of sensor channels.

[0074] Optionally, the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame signal can be calculated using any of the following methods: generalized cross-correlation, Kalman filtering, least mean square error adaptive filtering, or machine learning. n .

[0075] In the embodiments provided by the present invention, the generalized cross-correlation method is used to calculate the time difference between the arrival of the intrusive sound source target sound wave in the same frame signal at the reference channel and other sensing channels.

[0076] S42. Based on the maximum time difference obtained from the same frame of signal, construct a pseudo-random number generator with a Gaussian distribution. And introduce it into the corresponding time difference τ n Time difference after introducing pseudo-random number correction

[0077] Among them, the pseudo-random numbers that exhibit a Gaussian distribution The arrival time difference τ calculated based on the nth frame signal n The maximum value is constructed to obtain, where, The mean and standard deviation are 0 and 0.15, respectively.

[0078] Optionally, the S5 steps include:

[0079] S51, the spatial distance from the intrusion sound source target to the m-th sensing channel is... The relationship between the spatial distance from the intrusion sound source target to the sensing channel and the time difference of sound wave arrival is as follows: The spatial location of the intrusion sound source target is [X0, Y0, Z0], and the spatial location of the m-th sensing channel is [X... m,Y m Z m D1 represents the spatial distance between the intrusion sound source target and the reference channel. m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For ideal sound wave propagation speed;

[0080] In the embodiments provided by the present invention, v s Let τ be the ideal speed of sound wave propagation, 150 m / s, and let τ be the time difference between the arrival of the same sound wave at the reference channel and other sensing channels. The errors of both are reflected in τ.

[0081] S52, according to and Construct equation G n a n =b n ;

[0082] in,

[0083] S53. Solve the equation in step S52 to obtain the location information of the intrusion sound source target, a = [a1…a2]. n …a N ]; where a n This provides the location information of the intrusion sound source target in the nth frame of the signal. H represents the conjugate transpose of the matrix.

[0084] Based on steps S6-S7, the pseudo-random numbers introduced for each update are repeatedly calculated to obtain L×N sets of location information A of the intrusion sound source targets. L×N .

[0085] In the embodiment provided by the present invention, the distance between the sensing optical cable and the intrusion sound source target in the Z direction is 10cm, which is negligible relative to the speed of sound wave propagation. In order to intuitively represent the positioning effect of the present invention, the positioning result in the Z direction will not be reflected in the final result.

[0086] In one specific embodiment, such as Figure 6 As shown, the actual location of the intrusion sound source target is (2m, 1.4m). According to steps S1-S5, the location of the intrusion sound source target calculated by the arrival time difference before introducing pseudo-random numbers is (2.164m, 1.532m). In step S5, steps S3 to S4 are repeated 100,000 times. The location coordinates with the highest probability of occurrence calculated by the arrival time difference after introducing pseudo-random numbers are (2.136m, 1.477m). Therefore, (2.136m, 1.477m) is the final estimated location coordinate of the intrusion sound source target.

[0087] This invention employs a highly sensitive distributed acoustic wave sensing optical cable to construct multiple sensing channels, forming a detection network to detect and locate intrusive sound source targets in the network under test. The acoustic wave signal and its power spectral density characteristics of the intrusive sound source target are obtained from the detection network. After filtering, the time difference of the sound wave arriving at each sensing channel is obtained. A Gaussian-distributed pseudo-random number is constructed and introduced into the time difference to calculate the corresponding estimated location information of the intrusive sound source target. Repeated calculations are performed to obtain the location information estimate with the highest probability of occurrence as the final location of the intrusive sound source target. This invention proposes introducing pseudo-random numbers to efficiently compensate for the time-domain parameters used in positioning, avoiding local optima and enhancing the accuracy of the positioning results. It solves the technical problem in existing technologies where it is difficult to reduce the impact of environmental noise in real time, leading to the inability to achieve accurate and rapid positioning of intrusive sound source targets. Accurate and rapid positioning and tracking of intrusive sound source targets can be achieved. This is of great significance for the application of distributed fiber optic acoustic wave sensing technology in perimeter security and military anti-submarine warfare.

[0088] Example 2

[0089] This invention provides a real-time location device for an intrusion sound source target, comprising:

[0090] The acoustic signal acquisition module is used to divide the acoustic sensing optical cable of the area to be tested into M sensing channels, and acquire the acoustic signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3.

[0091] The acoustic signal processing module is used to determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed based on the power spectral density characteristics of the acoustic signal, filter the acoustic signals detected by each sensor channel in this frequency band range, and divide the filtered signal into frames.

[0092] The configuration module is used to set n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames;

[0093] The time difference calculation module is used to select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels;

[0094] The location information prediction module is used to predict the location information based on the relational formula. The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, D m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal;

[0095] The repeated calculation module is used to set n = n + 1 and repeatedly execute the steps of the setting module - location information estimation module until n is greater than N, thereby realizing the traversal of all frame signals and obtaining N sets of location information of the intrusion sound source target;

[0096] The location information calculation module is used to update the referenced pseudo-random numbers. Repeat step L-1 of the setting module-repetitive calculation module to obtain L×N sets of location information A of the intrusion sound source target. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1;

[0097] The real-time tracking module is used to obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

[0098] The real-time positioning device for an intrusion sound source target provided in this embodiment of the invention is used to execute the real-time positioning method for an intrusion sound source target in Embodiment 1, and has the same or similar beneficial effects, which will not be repeated here.

[0099] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for real-time localization of an intrusion sound source target, characterized in that, include: S1. Divide the acoustic wave sensing optical cable of the area to be tested into M sensing channels, and obtain the acoustic wave signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3. S2. Based on the power spectral density characteristics of the acoustic signal, determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed, filter the acoustic signal detected by each sensor channel using this frequency band range, and divide the filtered signal into frames. S3. Let n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames; S4. Select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels; S5. Based on the relational formula The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N ]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, D m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal; S6. Let n = n + 1, and repeat steps S3-S5 until n is greater than N, thereby traversing all frame signals and obtaining N sets of location information of the intrusion sound source target. S7. Update the referenced pseudo-random number. Repeat steps S3-S6 L-1 times to obtain L×N sets of location information A of the intrusion sound source targets. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1; S8. Obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

2. The real-time positioning method as described in claim 1, characterized in that, The S5 steps include: S51, the spatial distance from the intrusion sound source target to the m-th sensing channel is... The relationship between the spatial distance from the intrusion sound source target to the sensing channel and the time difference of sound wave arrival is as follows: The spatial location of the intrusion sound source target is [X0,Y0,Z0], and the spatial location of the m-th sensing channel is [X... m ,Y m Z m D1 represents the spatial distance between the intrusion sound source target and the reference channel. m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For ideal sound wave propagation speed; S52, according to and Constructing computational equation G n a n =b n ; in, S53. Solve the equation in step S52 to obtain the location information of the intrusion sound source target, a = [a1…a2]. n …a N ];in, H represents the conjugate transpose of the matrix.

3. The real-time positioning method as described in claim 1, characterized in that, The acoustic sensing optical cable is one of the following: single-mode optical cable, multi-mode optical cable, discrete scattering enhanced microstructure optical cable, or spiral wound acoustic pressure sensitizing optical cable.

4. The real-time positioning method as described in claim 1, characterized in that, The length of the sensing channel on the acoustic wave sensing optical cable is greater than or equal to the minimum spatial resolution of the connected acoustic wave sensing system; except for the sensing channels located at the beginning and end of the acoustic wave sensing optical cable, the lengths of the other sensing channels are equal.

5. The real-time positioning method as described in claim 1, characterized in that, The step of framing the filtered signal includes: The T-second acoustic wave signal acquired by each sensor channel is divided into frames of ti seconds to obtain N frames of signal; wherein the length of each frame of signal is greater than or equal to the minimum time sampling interval of the acoustic wave signal, and the length of the other frames of signal is equal except for the last frame.

6. The real-time positioning method as described in claim 1, characterized in that, The time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame signal can be calculated using any of the following methods: generalized cross-correlation method, Kalman filtering method, least mean square error adaptive filtering method, or machine learning method. n .

7. The real-time positioning method as described in claim 6, characterized in that, The pseudo-random numbers that exhibit a Gaussian distribution The arrival time difference τ calculated based on the nth frame signal n The maximum value is constructed to obtain, where, The mean and standard deviation are 0 and 0, respectively.

8. A real-time positioning device for an intrusion sound source target, characterized in that, include: The acoustic signal acquisition module is used to divide the acoustic sensing optical cable of the area to be tested into M sensing channels, and acquire the acoustic signal in the area to be tested through each sensing channel; wherein, the value of M is a positive integer greater than or equal to 3. The acoustic signal processing module is used to determine the frequency band range in which the signal energy of the corresponding intrusion sound source target is mainly distributed based on the power spectral density characteristics of the acoustic signal, filter the acoustic signals detected by each sensor channel in this frequency band range, and divide the filtered signal into frames. The configuration module is used to set n = 1; where n is the frame number, n is less than or equal to N, and N is the total number of frames; The time difference calculation module is used to select the first sensing channel as the reference channel and calculate the time difference τ between the sound wave arriving at the reference channel and other sensing channels in the nth frame of the signal. n Regarding the time difference τ n Introducing pseudo-random numbers with a Gaussian distribution Obtain the corrected time difference m is the sensor channel number, and M is the total number of sensor channels; The location information prediction module is used to predict the location information based on the relational formula. The location information of the intrusion sound source target under the frame signal is calculated as a = [a1…a2]. n …a N ]; where D1 is the spatial distance between the intrusion sound source target and the reference channel, D m v represents the spatial distance from the intrusion sound source target to the m-th sensing channel. s For the ideal speed of sound wave propagation, a n This provides the location information of the intrusion sound source target under the nth frame of the signal; The repeated calculation module is used to set n = n + 1 and repeatedly execute the steps of the setting module - location information estimation module until n is greater than N, thereby realizing the traversal of all frame signals and obtaining N sets of location information of the intrusion sound source target; The location information calculation module is used to update the referenced pseudo-random numbers. Repeat step L-1 of the setting module-repetitive calculation module to obtain L×N sets of location information A of the intrusion sound source target. L×N Select the set of location information that appears with the highest probability. The calculated location information of the intrusion sound source target; L is a positive integer greater than 1; The real-time tracking module is used to obtain the calculated position information of the intrusion sound source target at any time in the area to be tested, so as to realize the real-time tracking of the intrusion sound source target.

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