Noise suppression device, noise suppression method, and program

Abstract

To further suppress noise in a noise superimposition signal.SOLUTION: A noise suppression device according to the present disclosure includes a common feature extractor that inputs a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using an optical fiber cable and having noise superimposed thereon, extracts common features of the input plurality of noise-superimposed signals as a noise suppression signal in which noise has been suppressed, and outputs the extracted noise suppression signal.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present disclosure relates to a noise suppression device, a noise suppression method, and a program. [Background technology]

[0002] Distributed Acoustic Sensing (DAS) is a type of optical fiber sensing technology that uses optical fiber cables and is capable of detecting sound and vibrations generated at points on the optical fiber cables.

[0003] It is also possible to acquire a DAS signal indicating sound or vibration detected by the DAS, and recognize an event such as an abnormality that has occurred at a point on the optical fiber cable based on the acquired DAS signal.

[0004] However, the DAS signal is a noisy signal with noise superimposed thereon. Therefore, in order to recognize an event using such a noisy signal, it is necessary to suppress the noise in the noisy signal. As a noise suppression method for suppressing the noise in a noisy signal, for example, there is a method called spectral subtraction described in Patent Document 1. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 10-149191 Summary of the Invention [Problem to be solved by the invention]

[0006] As described above, an example of a noise suppression technique is the spectral subtraction technique described in Patent Document 1. However, there are cases where the noise suppression effect is insufficient simply by using existing noise suppression techniques such as spectral subtraction, and so there has been a demand for techniques that can further suppress noise in noise-containing signals.

[0007] In view of the above-mentioned problems, an object of the present disclosure is to provide a noise suppression device, a noise suppression method, and a program capable of further suppressing noise in a noise-superimposed signal. [Means for solving the problem]

[0008] A noise suppression device according to one aspect includes: The system is equipped with a common feature extractor that inputs a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using optical fiber cables and having noise superimposed thereon, extracts common features of the input plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed, and outputs the extracted noise-suppressed signal.

[0009] A noise suppression method according to one aspect includes: A noise suppression method executed by a noise suppression device, comprising: A number of noise-superimposed signals obtained by distributed acoustic sensing (DAS) using optical fiber cables and superimposed with noise are input, extracting a common feature of the plurality of noisy signals as a noise-suppressed signal in which noise has been suppressed; The noise suppressed signal is output.

[0010] A program according to one aspect comprises: On the computer, A step of inputting a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using optical fiber cables and having noise superimposed thereon; extracting a common feature of the plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed; outputting the noise suppression signal; Execute the command. Effect of the Invention

[0011] According to the above-described aspects, it is possible to provide a noise suppression device, a noise suppression method, and a program that are capable of further suppressing noise in a noise-superimposed signal. [Brief description of the drawings]

[0012] [Figure 1] 1 is a diagram illustrating an example of the configuration of a noise suppression device according to the present disclosure. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of a common feature extractor according to the present disclosure. [Diagram 3] FIG. 2 is a diagram illustrating an example of a general operation of a common feature extractor according to the present disclosure. [Figure 4] 11A to 11C are diagrams illustrating an example of a noise suppression effect achieved by a noise suppression device according to the present disclosure. [Diagram 5] FIG. 1 is a diagram showing an example of a method for expressing a DAS signal. [Figure 6] FIG. 13 is a diagram showing an example of application of Tucker decomposition to a DAS signal. [Figure 7] FIG. 1 is a diagram showing an example of an intuitive image of the present disclosure. [Figure 8] 1 is a diagram illustrating an example of the configuration of a noise suppression device according to the present disclosure. [Figure 9] 1 is a flow diagram illustrating a schematic operation example of a noise suppression device according to the present disclosure. [Figure 10] 1 is a block diagram showing an example of a hardware configuration of a computer that realizes a noise suppression device according to the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. Note that the following description and drawings are omitted and simplified as appropriate for clarity of explanation. In addition, in each of the following drawings, the same elements are given the same reference numerals, and duplicated explanations are omitted as necessary. In addition, the specific numerical values ​​and the like shown in the following description and drawings are merely examples for facilitating understanding of the present disclosure, and are not limited thereto.

[0014] <Embodiment 1> First, with reference to FIG. 1, an example of the configuration of a noise suppression device 10 will be described. As shown in FIG. 1, the noise suppression device 10 includes a common feature extractor 11 .

[0015] Here, it is assumed that a DAS device (not shown) is connected to an optical fiber cable, and detects sound and vibration generated at a point on the optical fiber cable by a DAS using the optical fiber cable, and obtains a DAS signal indicating the detected sound or vibration. It is also assumed that the DAS signal is a signal indicating the time change in frequency of the sound or vibration generated at an arbitrary point on the optical fiber cable and detected by the DAS.

[0016] In addition, the optical fiber cable (not shown) is assumed to be laid outdoors or indoors. When laid outdoors, the optical fiber cable is assumed to be laid, for example, suspended from a pole such as a utility pole or buried underground. When laid indoors, the optical fiber cable is assumed to be laid, for example, under a mat or carpet.

[0017] Also, it is assumed that the DAS device or processing device (not shown) converts the DAS signal acquired by the DAS device using a predetermined noise suppression method, i.e., performs processing to suppress noise in the DAS signal using the predetermined noise suppression method. Also, it is assumed that the predetermined noise suppression method is, for example, a method such as spectral subtraction, Wiener filtering, or singular value decomposition. Note that these noise suppression methods are known methods, and therefore their description will be omitted.

[0018] The common feature extractor 11 receives a DAS signal from a DAS device (not shown) as a second noise-superimposed signal on which noise has been superimposed. In addition, the common feature extractor 11 inputs a signal obtained by converting a DAS signal using a predetermined noise suppression technique from a DAS device or processing device (not shown), i.e., a signal in which noise of the DAS signal has been suppressed using a predetermined noise suppression technique, as a first noise-superimposed signal on which noise has been superimposed.

[0019] The common feature extractor 11 extracts a common feature of the input first noise-superimposed signal and second noise-superimposed signal as a noise-suppressed signal in which noise has been suppressed, and outputs the extracted noise-suppressed signal.

[0020] Next, a configuration example of the common feature extractor 11 will be described with reference to FIG. As shown in FIG. 2, the common feature extractor 11 includes a first nonlinear conversion unit 111, a second nonlinear conversion unit 112, an error calculation unit 113, and an extraction unit 114.

[0021] The first nonlinear transformation section 111 receives the first noise-added signal, and performs nonlinear transformation on the first noise-added signal using the parameters. The second nonlinear transformation section 112 receives the second noise-added signal and performs nonlinear transformation on the second noise-added signal using the parameters.

[0022] For example, it is assumed that the first nonlinear transformation unit 111 and the second nonlinear transformation unit 112 execute a nonlinear transformation of Y=aX+b. Under this assumption, a and b correspond to the above-mentioned parameters.

[0023] The error calculation unit 113 calculates the error by using the difference between the output of the first nonlinear conversion unit 111 and the output of the second nonlinear conversion unit 112. That is, in the first embodiment, the error calculation unit 113 calculates the error as follows. Error = Difference between the output of the first nonlinear conversion unit 111 and the output of the second nonlinear conversion unit 112

[0024] The extraction unit 114 compares the error calculated by the error calculation unit 113 with a threshold value ε. If the comparison result shows that the error is less than the threshold value ε, the extraction unit 114 extracts the output of the second nonlinear conversion unit 112, i.e., the second noise-superimposed signal nonlinearly converted by the second nonlinear conversion unit 112, as a noise suppression signal, and outputs the extracted noise suppression signal.

[0025] On the other hand, if the comparison result indicates that the error is equal to or greater than the threshold ε, the extraction unit 114 updates the parameters of the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112. Then, the extraction unit 114 causes the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112 to perform nonlinear conversion using the updated parameters, and causes the error calculation unit 113 to perform error calculation. As a result, if the error is still equal to or greater than the threshold ε, the extraction unit 114 updates the parameters of the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112 again.

[0026] That is, the extraction unit 114 repeats updating the parameters of the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112 until the error becomes less than the threshold ε. Then, when the error becomes less than the threshold ε, the extraction unit 114 extracts the output of the second nonlinear conversion unit 112 as a noise suppression signal, and outputs the extracted noise suppression signal.

[0027] Next, a schematic operation example of the common feature extractor 11 will be described with reference to FIG. 3, first, the first nonlinear conversion unit 111 receives a first noise-superimposed signal and performs nonlinear conversion on the first noise-superimposed signal using parameters (step S11). Also, the second nonlinear conversion unit 112 receives a second noise-superimposed signal and performs nonlinear conversion on the second noise-superimposed signal using parameters (step S12).

[0028] Next, the error calculation section 113 calculates an error using the difference between the output of the first nonlinear conversion section 111 and the output of the second nonlinear conversion section 112 (step S13).

[0029] Next, the extraction unit 114 compares the error calculated by the error calculation unit 113 with a threshold value ε (step S14). If the comparison result shows that the error is less than the threshold value ε (True in step S14), the extraction unit 114 extracts the output of the second nonlinear conversion unit 112, i.e., the second noise-superimposed signal nonlinearly converted by the second nonlinear conversion unit 112, as a noise suppression signal, and outputs the extracted noise suppression signal (step S15).

[0030] On the other hand, if the comparison result shows that the error is equal to or greater than the threshold ε (step S14: False), the extraction unit 114 repeats updating the parameters of the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112 until the error becomes less than the threshold ε (step S16). Then, when the error becomes less than the threshold ε (step S14: True), the extraction unit 114 extracts the output of the second nonlinear conversion unit 112 as a noise suppression signal, and outputs the extracted noise suppression signal (step S15).

[0031] As described above, according to the first embodiment, the common feature extractor 11 extracts a common feature of the first noise-superimposed signal and the second noise-superimposed signal on which noise has been superimposed, as a noise-suppressed signal in which noise has been suppressed. This allows the common feature extractor 11 to further suppress the noise of the second noise-superimposed signal (or the first noise-superimposed signal). Furthermore, the common feature extractor 11 can suppress the noise of the second noise-superimposed signal (or the first noise-superimposed signal) by receiving only the first noise-superimposed signal and the second noise-superimposed signal as input.

[0032] An example of the noise suppression effect achieved by the noise suppression device 10 will be described below with reference to FIG. 4 shows, from the top, a clean signal (correct signal) in which the noise of the second noise-superimposed signal is suppressed by simulation, the second noise-superimposed signal, a noise-suppressed signal in which the noise of the second noise-superimposed signal is suppressed by related technology, and a noise-suppressed signal in which the noise of the second noise-superimposed signal is suppressed by the present disclosure. The third noise-suppressed signal by related technology from the top is a signal in which the noise of the second noise-superimposed signal is suppressed by a predetermined noise suppression method, and corresponds to the first noise-superimposed signal. The four signals on the left side of FIG. 4 are signals that indicate the time change in frequency of sound or vibration generated at any point on the optical fiber cable and detected by the DAS, and the four signals on the right side of FIG. 4 are signals that indicate the time change in amplitude of sound or vibration generated at any point on the optical fiber cable and detected by the DAS.

[0033] As shown in FIG. 4, the noise-suppressed signal obtained by suppressing the noise of the second noise-superimposed signal according to the related art cannot reproduce the clean signal (correct signal), and it is clear that the noise suppression effect is insufficient.

[0034] In contrast, the noise-suppressed signal obtained by suppressing the noise of the second noise-superimposed signal according to the present disclosure can almost reproduce the clean signal (correct signal), and it is clear that a sufficient noise suppression effect is obtained.

[0035] In the first embodiment, the noise suppression device 10 receives two noise-superimposed signals, the first noise-superimposed signal and the second noise-superimposed signal, but the number of input noise-superimposed signals is not limited to two. The noise suppression device 10 may be configured to receive a plurality of noise-superimposed signals.

[0036] Although the noise suppression device 10 receives the second noise-superimposed signal and the first noise-superimposed signal obtained by suppressing the noise of the second noise-superimposed signal by a predetermined noise suppression method, the type of the input noise-superimposed signal is not limited to this. For example, the noise suppression device 10 may be configured to receive a plurality of noise-superimposed signals obtained by a DAS for sounds or vibrations generated in the same area using different optical fiber cables.

[0037] <Embodiment 2> The second embodiment is different from the first embodiment in that the common feature extractor 11 extracts a common feature of the first noise superimposed signal and the second noise superimposed signal as a noise suppression signal in consideration of the spatial features around the optical fiber cable. Note that the configuration of the second embodiment is the same as that of the first embodiment, and therefore a description thereof will be omitted.

[0038] First, with reference to FIG. 5, an example of a method for expressing a DAS signal that can be acquired by a DAS will be described. As shown in Figure 5, the DAS signal can be expressed as a third-order tensor, namely, space (channel), time, and frequency. Here, a channel is each sensing point on the optical fiber cable. Therefore, the space contains a large number of channels.

[0039] Therefore, the spatial characteristics around the optical fiber cable include: (1) Low rank of spatial dimension of DAS signals That is, the number of sound sources or vibration sources is small compared to the number of channels on the optical fiber cable. (2) Non-uniformity of sensitivity between channels on an optical fiber cable That is, the sensitivity (signal-to-noise ratio (SNR)) to the DAS signal differs between channels on the optical fiber cable.

[0040] Therefore, taking into consideration the above (1) and (2), the common feature extractor 11 performs the following process to extract a common feature between the first noise-superimposed signal and the second noise-superimposed signal as a noise-suppressed signal.

[0041] (1) Low rank of spatial dimension of DAS signals The first nonlinear transformation unit 111 and the second nonlinear transformation unit 112 perform nonlinear transformation with a low-rank constraint on the spatial dimension on the first noisy signal and the second noisy signal, respectively.

[0042] Here, in order to explain the above-mentioned processing by the first nonlinear conversion section 111 and the second nonlinear conversion section 112, an example in which Tucker decomposition is applied to a DAS signal will be explained with reference to FIG.

[0043] The Tucker decomposition is an example of tensor decomposition, and is a method of unfolding a given tensor into a low-rank core tensor (core) and a factor matrix (factor) using a rank given in advance.

[0044] As shown in FIG. 6, for DAS signals, the rank numbers given to the space (channel), time, and frequency tensors are: Time:R t , Frequency: R f , Channel:R c Moreover, the rank number of the original DAS signal is set as follows. Time:D t、 Frequency:D f , Channel: D c

[0045] As mentioned above, the DAS signal has a low spatial dimension and hence is c and R c is considered to be related as follows: R c >=D c

[0046] The above low-rank constraint on spatial dimensions corresponds to a folding operation that multiplies a low-rank core tensor (i.e., space (channel)) by a factor matrix to return it to the original tensor size.

[0047] That is, the first nonlinear conversion unit 111 and the second nonlinear conversion unit 112 perform the above-mentioned operation (folding) on ​​the first noise-superimposed signal and the second noise-superimposed signal, respectively, and then perform nonlinear conversion. (2) Non-uniformity of sensitivity between channels on an optical fiber cable The error calculation unit 113 calculates the error by using the difference between the output of the first nonlinear conversion unit 111 and the output of the second nonlinear conversion unit 112, and by using a regularization term that takes into account the difference in sensitivity between the channels on the optical fiber cable. That is, in the second embodiment, the error calculation unit 113 calculates the error as follows. Error = difference between the output of the first nonlinear conversion unit 111 and the output of the second nonlinear conversion unit 112 + regularization term considering the difference in sensitivity between each channel on the optical fiber cable

[0048] Next, an example of an intuitive image of the second embodiment will be described with reference to FIG. As shown in FIG. 7, in the second embodiment, a process is performed to extract a noise suppression signal as a common feature of the two noise-superimposed signals, while taking into consideration low-rank constraints and regularization of the spatial dimension so that the second noise-superimposed signal does not deviate too far from the first noise-superimposed signal.

[0049] In addition, since the operations of the second embodiment other than the above-mentioned operations are similar to those of the first embodiment, the explanation thereof will be omitted.

[0050] As described above, according to the second embodiment, the common feature extractor 11 extracts a common feature of the first noise superimposed signal and the second noise superimposed signal as a noise suppression signal, taking into consideration the spatial characteristics around the optical fiber cable. This allows the common feature extractor 11 to further suppress the noise of the second noise superimposed signal (or the first noise superimposed signal) compared to the first embodiment. Other effects are the same as those of the first embodiment.

[0051] <Embodiment 3> The third embodiment corresponds to an embodiment that conceptualizes the first and second embodiments described above. First, with reference to FIG. 8, an example of the configuration of the noise suppression device 20 will be described. As shown in FIG. 8, the noise suppression device 20 includes a common feature extractor 21.

[0052] The common feature extractor 21 receives as input a plurality of noisy signals acquired by a DAS using an optical fiber cable and having noise superimposed thereon. Moreover, the common feature extractor 21 extracts a common feature of the inputted plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed. Moreover, the common feature extractor 21 outputs the extracted noise suppression signal.

[0053] Next, a schematic operation example of the noise suppression device 20 will be described with reference to FIG. 9, first, the common feature extractor 21 inputs a plurality of noise-superimposed signals obtained by a DAS using an optical fiber cable and having noise superimposed thereon (step S21). Next, the common feature extractor 21 extracts a common feature of the inputted plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed (step S22). After that, the common feature extractor 21 outputs the extracted noise-suppressed signal (step S23).

[0054] As described above, according to the third embodiment, the common feature extractor 21 extracts a common feature of a plurality of noise-superimposed signals on which noise has been superimposed as a noise-suppressed signal in which the noise has been suppressed. This allows the common feature extractor 21 to further suppress the noise of the noise-superimposed signals. Other effects are the same as those of the first and second embodiments described above.

[0055] The common feature extractor 21 may extract a common feature of a plurality of noise superimposed signals as a noise suppression signal, taking into consideration spatial features around the optical fiber cable.

[0056] Furthermore, the multiple noise-superimposed signals may be a first noise-superimposed signal and a second noise-superimposed signal. In this case, the common feature extractor 21 may include a first nonlinear conversion unit that receives the first noise-superimposed signal and performs nonlinear conversion of the first noise-superimposed signal using a parameter, a second nonlinear conversion unit that receives the second noise-superimposed signal and performs nonlinear conversion of the second noise-superimposed signal using a parameter, an error calculation unit that calculates an error using a difference between an output of the first nonlinear conversion unit and an output of the second nonlinear conversion unit, and an extraction unit that repeats updating of the parameter until the error becomes less than a threshold, extracts the output of the first nonlinear conversion unit or the output of the second nonlinear conversion unit as a noise suppression signal when the error becomes less than the threshold, and outputs the extracted noise suppression signal.

[0057] The spatial characteristic around the optical fiber cable may be a difference in sensitivity between each point on the optical fiber cable. In this case, the error calculation unit may calculate the error using a difference between the output of the first nonlinear conversion unit and the output of the second nonlinear conversion unit and a regularization term that takes into account the difference in sensitivity between each point on the optical fiber cable.

[0058] Furthermore, the spatial characteristic of the vicinity of the optical fiber cable may be a low-rank property of the spatial dimension of the first noisy signal and the second noisy signal. In this case, the first nonlinear transformation unit and the second nonlinear transformation unit may perform a nonlinear transformation with a low-rank constraint of the spatial dimension on the first noisy signal and the second noisy signal.

[0059] The spatial characteristics around the optical fiber cable may be a difference in sensitivity between each point on the optical fiber cable and a low rank of the spatial dimension of the first noisy signal and the second noisy signal. In this case, the error calculation unit may calculate the error using a difference between the output of the first nonlinear conversion unit and the output of the second nonlinear conversion unit and a regularization term that takes into account the difference in sensitivity between each point on the optical fiber cable. The first nonlinear conversion unit and the second nonlinear conversion unit may perform nonlinear conversion with a low rank constraint of the spatial dimension on the first noisy signal and the second noisy signal.

[0060] Furthermore, the first noise-superimposed signal may be a signal obtained by converting the second noise-superimposed signal using a predetermined noise suppression technique. In this case, when the error becomes less than the threshold, the extractor may extract the output of the second nonlinear converter as a noise-suppressed signal and output the extracted noise-suppressed signal.

[0061] Furthermore, the first noisy signal and the second noisy signal may be signals acquired by a DAS for sound or vibration generated in the same area using different optical fiber cables.

[0062] <Hardware configuration of a noise suppression device according to an embodiment> Next, with reference to FIG. 10, an example of the hardware configuration of a computer that realizes the above-described noise suppression devices 10 and 20 will be described.

[0063] 10, a computer 90 includes a processor 91, a memory 92, a storage 93, an input / output interface (input / output I / F) 94, and a communication interface (communication I / F) 95. The processor 91, the memory 92, the storage 93, the input / output interface 94, and the communication interface 95 are connected by a data transmission path for transmitting and receiving data to and from each other.

[0064] The processor 91 is, for example, an arithmetic processing device such as a central processing unit (CPU) or a graphics processing unit (GPU). The memory 92 is, for example, a random access memory (RAM) or a read only memory (ROM). The storage 93 is, for example, a storage device such as a hard disk drive (HDD), a solid state drive (SSD), or a memory card. The storage 93 may also be a memory such as a RAM or a ROM.

[0065] A program is stored in the storage 93. When the program is loaded into a computer, it includes a set of instructions (or software code) for causing the computer 90 to perform one or more functions of the noise suppression devices 10 and 20 described above. The components of the noise suppression devices 10 and 20 described above may be realized by the processor 91 reading and executing the program stored in the storage 93. Furthermore, the storage function of the noise suppression devices 10 and 20 described above may be realized by the memory 92 or the storage 93.

[0066] The above-mentioned programs may also be stored on non-transitory computer-readable media or tangible storage media. By way of example and not limitation, computer-readable media or tangible storage media include RAM, ROM, flash memory, SSD or other memory technology, CD (Compact Disc)-ROM, DVD (Digital Versatile Disc), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The programs may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.

[0067] The input / output interface 94 is connected to a display device 941, an input device 942, a sound output device 943, and the like. The display device 941 is a device that displays a screen corresponding to drawing data processed by the processor 91, such as an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, or a monitor. The input device 942 is a device that accepts an operation input by an operator, and is, for example, a keyboard, a mouse, or a touch sensor. The display device 941 and the input device 942 may be integrated and realized as a touch panel. The sound output device 943 is a device that acoustically outputs a sound corresponding to the sound data processed by the processor 91, such as a speaker.

[0068] The communication interface 95 transmits and receives data to and from an external device. For example, the communication interface 95 communicates with the external device via a wired communication path or a wireless communication path.

[0069] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-mentioned embodiments. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be appropriately combined with other embodiments.

[0070] Moreover, each drawing is merely an example for describing one or more embodiments. Each drawing may relate not only to one particular embodiment, but to one or more other embodiments. As can be understood by those skilled in the art, various features or steps described with reference to any one drawing may be combined with features or steps shown in one or more other drawings to create an embodiment not explicitly shown or described, for example. Not all features or steps shown in any one drawing are necessarily required to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0071] Furthermore, some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. (Appendix 1) a common feature extractor that receives a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using an optical fiber cable and having noise superimposed thereon, extracts a common feature of the plurality of noise-superimposed signals received as a noise-suppressed signal in which noise has been suppressed, and outputs the extracted noise-suppressed signal; Noise suppression device. (Appendix 2) The common feature extractor extracts a common feature of the plurality of noise superimposed signals as the noise suppression signal, taking into account spatial characteristics of the periphery of the optical fiber cable. 2. A noise suppression device as described in claim 1. (Appendix 3) the plurality of noisy signals are a first noisy signal and a second noisy signal; The common feature extractor comprises: a first nonlinear conversion unit that receives the first noise-superimposed signal and performs nonlinear conversion on the first noise-superimposed signal using a parameter; a second nonlinear conversion unit that receives the second noise-superimposed signal and performs nonlinear conversion on the second noise-superimposed signal using the parameter; an error calculation unit that calculates an error using a difference between an output of the first nonlinear conversion unit and an output of the second nonlinear conversion unit; and an extraction unit that repeats updating of the parameters until the error becomes less than a threshold value, and when the error becomes less than the threshold value, extracts an output of the first nonlinear conversion unit or an output of the second nonlinear conversion unit as the noise suppression signal, and outputs the extracted noise suppression signal. 2. A noise suppression device as described in claim 1. (Appendix 4) the spatial characteristic of the vicinity of the fiber optic cable being a difference in sensitivity between points on the fiber optic cable; the error calculation unit calculates the error by using the difference and a regularization term that takes into account a difference in sensitivity between each point on the optical fiber cable. 4. A noise suppression device according to claim 3. (Appendix 5) a spatial characteristic of the vicinity of the optical fiber cable being a low rank of a spatial dimension of the first noisy signal and the second noisy signal; The first nonlinear transformation unit and the second nonlinear transformation unit perform nonlinear transformation with a low rank constraint on a spatial dimension on the first noise-added signal and the second noise-added signal. 4. A noise suppression device according to claim 3. (Appendix 6) the spatial characteristics of the vicinity of the optical fiber cable being sensitivity differences between points on the optical fiber cable and low rank of spatial dimensions of the first noisy signal and the second noisy signal; the error calculation unit calculates the error using the difference and a regularization term that takes into account a difference in sensitivity between each point on the optical fiber cable; The first nonlinear transformation unit and the second nonlinear transformation unit perform nonlinear transformation with a low rank constraint on a spatial dimension on the first noise-added signal and the second noise-added signal. 4. A noise suppression device according to claim 3. (Appendix 7) the first noise-superimposed signal is a signal obtained by converting the second noise-superimposed signal using a predetermined noise suppression technique; When the error becomes less than the threshold, the extraction unit extracts the output of the second nonlinear conversion unit as the noise suppression signal, and outputs the extracted noise suppression signal. 4. A noise suppression device according to claim 3. (Appendix 8) The first noise-superimposed signal and the second noise-superimposed signal are signals obtained by the DAS for sound or vibration generated in the same area using different optical fiber cables. 4. A noise suppression device according to claim 3. (Appendix 9) A noise suppression method executed by a noise suppression device, comprising: A number of noise-superimposed signals obtained by distributed acoustic sensing (DAS) using optical fiber cables and superimposed with noise are input, extracting a common feature of the plurality of noisy signals as a noise-suppressed signal in which noise has been suppressed; outputting the noise suppression signal; Noise suppression methods. (Appendix 10) On the computer, A step of inputting a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using optical fiber cables and having noise superimposed thereon; extracting a common feature of the plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed; outputting the noise suppression signal; A program that executes the following.

[0072] Some or all of the elements (e.g., configurations and functions) described in Supplementary Notes 2 to 8 that are dependent on Supplementary Note 1 may also be dependent on Supplementary Notes 9 and 10 in the same dependent relationship as Supplementary Notes 2 to 8. Some or all of the elements described in any Supplementary Note may be applied to various hardware, software, recording means for recording software, systems, and methods. [Explanation of symbols]

[0073] 10 Noise suppression device 11 Common Feature Extractor 111 First Nonlinear Transformation Section 112 Second Nonlinear Transformation Section 113 Error calculation section 114 Extraction part 20 Noise suppression device 21 Common Feature Extractor 90 Computer 91 Processor 92 Memory 93 Storage 94 Input / Output Interface 941 Display device 942 Input Device 943 Sound output device 95 Communication Interface

Claims

1. a common feature extractor that receives a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using an optical fiber cable and having noise superimposed thereon, extracts a common feature of the plurality of noise-superimposed signals received as a noise-suppressed signal in which noise has been suppressed, and outputs the extracted noise-suppressed signal; Noise suppression device.

2. The common feature extractor extracts a common feature of the plurality of noise superimposed signals as the noise suppression signal, taking into account spatial characteristics of the periphery of the optical fiber cable.

2. The noise suppression device according to claim 1.

3. the plurality of noisy signals are a first noisy signal and a second noisy signal; The common feature extractor comprises: a first nonlinear conversion unit that receives the first noise-added signal and performs nonlinear conversion on the first noise-added signal using a parameter; a second nonlinear conversion unit that receives the second noise-added signal and performs nonlinear conversion on the second noise-added signal using the parameter; an error calculation unit that calculates an error using a difference between an output of the first nonlinear conversion unit and an output of the second nonlinear conversion unit; and an extraction unit that repeats updating of the parameters until the error becomes less than a threshold value, and when the error becomes less than the threshold value, extracts an output of the first nonlinear conversion unit or an output of the second nonlinear conversion unit as the noise suppression signal, and outputs the extracted noise suppression signal.

2. The noise suppression device according to claim 1.

4. the spatial characteristic of the vicinity of the fiber optic cable being a difference in sensitivity between points on the fiber optic cable; the error calculation unit calculates the error by using the difference and a regularization term that takes into account a difference in sensitivity between each point on the optical fiber cable.

4. The noise suppression device according to claim 3.

5. a spatial characteristic of the vicinity of the optical fiber cable being a low rank of a spatial dimension of the first noisy signal and the second noisy signal; The first nonlinear transformation unit and the second nonlinear transformation unit perform nonlinear transformation with a low rank constraint on a spatial dimension on the first noise-added signal and the second noise-added signal.

4. The noise suppression device according to claim 3.

6. the spatial characteristics of the vicinity of the optical fiber cable being sensitivity differences between points on the optical fiber cable and low rank of spatial dimensions of the first noisy signal and the second noisy signal; the error calculation unit calculates the error using the difference and a regularization term that takes into account a difference in sensitivity between each point on the optical fiber cable; The first nonlinear transformation unit and the second nonlinear transformation unit perform nonlinear transformation with a low rank constraint on a spatial dimension on the first noise-added signal and the second noise-added signal.

4. The noise suppression device according to claim 3.

7. the first noise-superimposed signal is a signal obtained by converting the second noise-superimposed signal using a predetermined noise suppression technique, When the error becomes less than the threshold, the extraction unit extracts the output of the second nonlinear conversion unit as the noise suppression signal, and outputs the extracted noise suppression signal.

4. The noise suppression device according to claim 3.

8. The first noise-superimposed signal and the second noise-superimposed signal are signals acquired by the DAS for sound or vibration generated in the same area using different optical fiber cables.

4. The noise suppression device according to claim 3.

9. A noise suppression method executed by a noise suppression device, comprising: A plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using optical fiber cables and having noise superimposed thereon are input; extracting a common feature of the plurality of noisy signals as a noise-suppressed signal in which noise has been suppressed; outputting the noise suppression signal; Noise suppression methods.

10. On the computer, A step of inputting a plurality of noise-superimposed signals acquired by distributed acoustic sensing (DAS) using an optical fiber cable and having noise superimposed thereon; extracting a common feature of the plurality of noise-superimposed signals as a noise-suppressed signal in which noise has been suppressed; outputting the noise suppression signal; A program that executes the following.

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