CN118362198A - Distributed acoustic wave sensing phase drift elimination method - Google Patents
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Abstract
The invention provides a distributed acoustic wave sensing phase drift elimination method, which comprises the following steps: acquiring each signal component in the distributed acoustic wave sensing system and respectively carrying out phase demodulation to obtain a phase value of each signal component at the current moment; initializing a Kalman filter, and updating an equation by Kalman filter time for each signal component, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment; calculating a Kalman gain coefficient by a Kalman gain equation; calculating the phase drift estimated value of the current moment of each signal component, and updating the posterior estimated covariance of the current moment of each signal component; finally, calculating and outputting the phase value of each signal component without drift at the current moment, and finishing the elimination of the phase drift at the current moment; the invention is suitable for various distributed acoustic wave sensing systems, can eliminate the phase drift of each signal component and can maintain the phase consistency of each signal component in real time.
Description
Technical Field
The invention relates to the technical field of optical fiber communication and sensing, in particular to a distributed acoustic wave sensing phase drift elimination method.
Background
Distributed fiber vibration sensing technology has evolved rapidly over the last two decades. The distributed optical fiber vibration sensor includes an interferometric sensor and a back-scattering sensor. The formation of Rayleigh scattering in an optical fiber results mainly from material density and refractive index non-uniformities that are formed during the fiber fabrication process for various reasons. The optical fiber distributed sensor based on the interference technology is mainly based on the phase modulation characteristic of external disturbance signals on optical wave transmission in the optical fiber, and the sensing and the detection of the external disturbance signals are realized by demodulating the phase information change of the returned optical wave signals.
In the signal demodulation process, the distributed optical fiber sensing system based on the phase sensitive optical time domain reflectometer (phi-OTDR) uses narrow linewidth signals with strong coherence, and in the coherence process of signal light and local oscillation light, the situation that local light intensity is weaker, namely fading noise, is easy to occur. The fading noise can cause the situation that the local position of the optical fiber has phase demodulation errors, so as to form a detection blind area, and the detection blind area is usually solved by using signal multiplexing/demultiplexing to obtain a plurality of signal components.
For example, a non-fading multi-wavelength distributed acoustic wave sensing system and a differential rotation vector superposition method are disclosed in the existing patent documents, wherein a multi-wavelength light source module is used for generating multiplexed multi-wavelength probe light and a plurality of independent local oscillation light; the pulse modulation module is used for pulse modulation and frequency shift of the multi-wavelength probe light to generate short pulse laser; the circulator is used for receiving the short pulse laser and outputting multi-wavelength scattered light; the sensing optical cable is used for scattering the short pulse laser to form multi-wavelength scattered light; the receiving module is used for demultiplexing the multi-wavelength scattered light and enabling each independent local oscillation light to interfere with the scattered light signal with the corresponding wavelength and form a beat frequency signal through photoelectric conversion; the differential vector superposition module is used for vector combination of the multi-wavelength beat frequency signals; the signal processing module is used for phase demodulation to obtain optical phase information distributed along the sensing optical cable; although this prior art can reduce interference fading and polarization fading, this prior art solution is only applicable to ideal cases where the phase of each signal component should remain consistent after the initial phase is eliminated by the rotation vector; however, due to frequency drift and random phase noise of the laser, phase errors are generated among the components, and the errors are accumulated continuously along with time, so that accumulated phase errors except for phase changes caused by vibration are generated among the components, the occurrence of errors can reduce the modulus value of a rotation vector sum, even when the phase error items of the components are large enough to exceed pi/2, cancellation occurs, and fading noise occurrence and phase signal distortion are increased.
Disclosure of Invention
The invention provides a distributed acoustic wave sensing phase drift elimination method which can eliminate phase drift in real time so as to keep the phase consistency of each signal component.
In order to solve the technical problems, the technical scheme of the invention is as follows:
A distributed acoustic wave sensing phase drift elimination method comprises the following steps:
s1: acquiring each signal component in the distributed acoustic wave sensing system and respectively carrying out phase demodulation to obtain a phase value of each signal component at the current moment;
s2: initializing a Kalman filter, and updating an equation for each signal component by Kalman filtering time, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment;
S3: substituting the prior estimated covariance of the current moment into a Kalman gain equation for each signal component, and calculating a Kalman gain coefficient;
S4: calculating the phase drift estimated value of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient; updating posterior estimation covariance of the current moment of each signal component;
s5: and calculating and outputting a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, and finishing the elimination of the phase drift at the current moment of each signal component.
Preferably, the step S1 includes:
acquiring each signal component in the distributed acoustic wave sensing system, respectively carrying out phase demodulation, and respectively obtaining the current moment of each signal component Is of the angle of irradiance of (a)And according to the last timeIs a phase value after demodulation ofAt the current timeTo obtain the phase value of each signal component at the current moment。
Preferably, the step S2 includes:
initializing state parameters of a Kalman filter;
For each signal component, updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment by using a Kalman filtering time updating equation, wherein the formula is as follows:
Wherein, For the current momentIs used to estimate the covariance of the prior estimate,For the last momentIs used to estimate the covariance of the posterior estimate,Covariance is excited for the process of the kalman filter.
Preferably, the step S3 includes:
for each signal component, substituting the prior estimated covariance of the current moment into a Kalman gain equation, and calculating a Kalman gain coefficient according to the following formula:
Wherein, In order to be a kalman gain factor,Is the measurement covariance of the kalman filter.
Preferably, in the step S4, calculating the estimated phase drift value of the current time of each signal component includes:
Updating the state of the Kalman filter, and calculating the estimated value of the phase drift of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient, wherein the estimated value of the phase drift of each signal component at the current moment is calculated according to the following formula:
Wherein, For the current momentIs determined by the phase drift estimate of (a); For the last moment Is used for the phase drift estimation of (a).
Preferably, in the step S4, the a posteriori estimated covariance of the current time of each signal component is updated according to the following formula:
Wherein, For the current momentIs used to estimate covariance.
Preferably, the step S5 includes:
and calculating a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, wherein the formula is as follows:
Wherein, The phase value is a phase value without drift at the current moment;
Outputting the phase value of each signal component without drift at the current moment And finishing the elimination of the phase drift of each signal component at the current moment.
Preferably, in the step S1, the distributed acoustic wave sensing system includes: a distributed optical fiber sensing system based on phase sensitive optical time domain reflectometer phi-OTDR.
Preferably, in step S1, each signal component is specifically a multiplexed signal in a distributed acoustic wave sensing system, and the multiplexing includes: space division multiplexing, frequency division multiplexing, wavelength division multiplexing, time division multiplexing, and polarization multiplexing;
or the signal component is embodied as a single signal in a distributed acoustic wave sensing system that is not modulated with a multiplexed signal.
Preferably, the order of the kalman filter is a first order;
The invention is not limited in particular to the order of the kalman filter, the kalman filter of the first order is only an exemplary representation, and the method of the invention can be applied to kalman filters of all orders (first order, second order and higher).
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
The invention provides a distributed acoustic wave sensing phase drift elimination method, which comprises the steps of firstly, obtaining each signal component in a distributed acoustic wave sensing system, and respectively carrying out phase demodulation to obtain a phase value of each signal component at the current moment; initializing a Kalman filter, and updating an equation by Kalman filter time for each signal component, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment; substituting the prior estimation covariance of the current moment into a Kalman gain equation, and calculating a Kalman gain coefficient; then calculating the phase drift estimated value of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient; updating posterior estimation covariance of the current moment of each signal component; finally, calculating and outputting a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, and finishing the elimination of the phase drift at the current moment of each signal component;
According to the invention, the phase drift at the current moment is estimated according to the phase drift at the last moment of the component by carrying out Kalman filtering tracking on the phase obtained by demodulating each signal component of the distributed acoustic wave sensing system, so that the method can be applied to the distributed acoustic wave sensing system with any multiplexing signal quantity, effectively eliminate the phase drift of each signal component and keep the phase consistency of each signal component in real time; in addition, for a single signal component distributed acoustic wave sensing system, the invention can effectively eliminate the phase drift of the single signal component distributed acoustic wave sensing system.
Drawings
Fig. 1 is a flowchart of a distributed acoustic wave sensing phase drift cancellation method provided in embodiment 1.
Fig. 2 is a schematic structural diagram of the distributed acoustic wave sensor system provided in embodiment 2.
Fig. 3 is a logic flow diagram of a distributed acoustic wave sensing phase drift cancellation method provided in embodiment 2.
Fig. 4 is a graph showing the change of the argument of each signal component with time before and after the phase shift cancellation provided in embodiment 2.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the present patent;
for the purpose of better illustrating the embodiments, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the actual product dimensions;
It will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 1, the present embodiment provides a distributed acoustic wave sensing phase drift elimination method, which includes the following steps:
s1: acquiring each signal component in the distributed acoustic wave sensing system and respectively carrying out phase demodulation to obtain a phase value of each signal component at the current moment;
s2: initializing a Kalman filter, and updating an equation for each signal component by Kalman filtering time, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment;
S3: substituting the prior estimated covariance of the current moment into a Kalman gain equation for each signal component, and calculating a Kalman gain coefficient;
S4: calculating the phase drift estimated value of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient; updating posterior estimation covariance of the current moment of each signal component;
s5: and calculating and outputting a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, and finishing the elimination of the phase drift at the current moment of each signal component.
In the specific implementation process, firstly, each signal component in a distributed acoustic wave sensing system is acquired and is subjected to phase demodulation respectively to obtain a phase value of each signal component at the current moment;
Initializing a Kalman filter, and updating an equation by Kalman filter time for each signal component, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment;
substituting the prior estimation covariance of the current moment into a Kalman gain equation, and calculating a Kalman gain coefficient;
then calculating the phase drift estimated value of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient; updating the posterior estimation covariance of the current moment of each signal component, wherein the posterior estimation covariance of the current moment after updating is used for calculating a Kalman gain coefficient at the next moment;
Finally, calculating and outputting a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, and finishing the elimination of the phase drift at the current moment of each signal component;
repeating the steps to eliminate the real-time phase drift of each signal component of the distributed acoustic wave sensing system;
According to the method, the Kalman filtering tracking is carried out on the phase obtained by demodulating each signal component of the distributed acoustic wave sensing system, the phase drift at the current moment is estimated according to the phase drift at the last moment of the component, the method can be suitable for the distributed acoustic wave sensing system with any multiplexing signal quantity, the phase drift of each signal component is effectively eliminated, and the phase consistency of each signal component is maintained in real time.
Example 2
The embodiment provides a distributed acoustic wave sensing phase drift elimination method, which comprises the following steps:
S1: each signal component in the distributed acoustic wave sensing system is acquired and is subjected to phase demodulation respectively to obtain a phase value of each signal component at the current moment, and the method comprises the following steps:
acquiring each signal component in the distributed acoustic wave sensing system, respectively carrying out phase demodulation, and respectively obtaining the current moment of each signal component Is of the angle of irradiance of (a)And according to the last timeIs a phase value after demodulation ofAt the current timeTo obtain the phase value of each signal component at the current moment；
S2: initializing a Kalman filter, for each signal component, updating an equation by Kalman filtering time, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment, wherein the method comprises the following steps:
initializing state parameters of a Kalman filter;
For each signal component, updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment by using a Kalman filtering time updating equation, wherein the formula is as follows:
Wherein, For the current momentIs used to estimate the covariance of the prior estimate,For the last momentIs used to estimate the covariance of the posterior estimate,Exciting covariance for the process of the Kalman filter;
S3: substituting the prior estimated covariance of the current moment into a Kalman gain equation for each signal component, and calculating a Kalman gain coefficient, wherein the method comprises the following steps of:
for each signal component, substituting the prior estimated covariance of the current moment into a Kalman gain equation, and calculating a Kalman gain coefficient according to the following formula:
Wherein, In order to be a kalman gain factor,Measurement covariance for a kalman filter;
S4: according to the phase value and Kalman gain coefficient of each signal component at the current moment, calculating the phase drift estimated value of each signal component at the current moment, comprising:
Updating the state of the Kalman filter, and calculating the estimated value of the phase drift of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient, wherein the estimated value of the phase drift of each signal component at the current moment is calculated according to the following formula:
Wherein, For the current momentIs determined by the phase drift estimate of (a); For the last moment Is determined by the phase drift estimate of (a);
And updating the posterior estimated covariance of the current moment of each signal component:
Wherein, For the current momentIs a posterior estimate of covariance;
s5: and calculating a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, wherein the formula is as follows:
Wherein, The phase value is a phase value without drift at the current moment;
Outputting the phase value of each signal component without drift at the current moment The elimination of the phase drift of each signal component at the current moment is completed;
in the step S1, the distributed acoustic wave sensing system includes: a distributed optical fiber sensing system based on a phase sensitive optical time domain reflectometer phi-OTDR;
In the step S1, each signal component is specifically a multiplexed signal in the distributed acoustic wave sensing system, and the multiplexing includes: space division multiplexing, frequency division multiplexing, wavelength division multiplexing, time division multiplexing, and polarization multiplexing;
Or the signal component is specifically a single signal in a distributed acoustic wave sensing system which is not modulated by a multiplexing signal;
in this embodiment, the order of the kalman filter is a first order;
The method of the present embodiment can also be applied to kalman filters of all orders (first order, second order, and higher).
In the specific implementation process, as shown in fig. 2, fig. 2 is an exemplary distributed acoustic wave sensing system, which includes a narrow linewidth continuous laser 1, a first optical fiber coupler 2, a second optical fiber coupler 3, a first acousto-optic modulator 4, a second acoustic modulator 5, a signal transmitting device 6, a delay optical fiber 7, a third optical fiber coupler 8, a first erbium-doped optical fiber amplifier 9, a first optical filter 10, an optical circulator 11, a second erbium-doped optical fiber amplifier 12, a second optical filter 13, a fourth optical fiber coupler 14, a photoelectric balance receiver 15, and a signal processing device 16;
The output end of the narrow linewidth continuous laser 1 is connected with the input end of a first optical fiber coupler 2, the first output end of the first optical fiber coupler 2 for detecting light is connected with the first input end of a fourth optical fiber coupler 14, and the second output end is connected with the input end of a second optical fiber coupler 3; the output end of the second optical fiber coupler 3 is respectively connected with the first acoustic optical modulator 4 and the second acoustic optical modulator 5, and the signal sending device 6 modulates continuous light by emitting electric pulses, and the two paths of continuous light are respectively modulated into light pulses with frequency shift amounts of 80 MHz and 200 MHz; the output end of the second acoustic optical modulator 5 is connected with a delay optical fiber 7, and delays the pulse light generated by the second acoustic optical modulator 5; the output end of the first acousto-optic modulator 4 and the delay optical fiber 7 are connected with the input end of the third optical fiber coupler 8; the input end of the third optical fiber coupler 8 is connected with the input end of the first erbium-doped optical fiber amplifier 9, and the optical power of the pulse light is amplified; the output end of the first erbium-doped fiber amplifier 9 is connected with the input end of the first optical filter 10, and filters the pulse light; the output end of the first optical filter 10 is connected with a first port of the optical circulator 11; the second port of the optical circulator 11 is connected with light to be detected, and light pulses enter the optical fiber to be detected through the optical circulator; the third port of the optical circulator 11 is connected with the input end of the second erbium-doped optical fiber amplifier 12, and the Rayleigh scattered light transmitted in the back direction enters the second erbium-doped optical fiber amplifier 12 through the optical circulator for amplifying the optical power; the output end of the second erbium-doped fiber amplifier 12 is connected with a second optical filter 13 for filtering the amplified scattered light; the second optical filter 13 is connected with a second input end of the fourth optical fiber coupler 14; the output end of the fourth optical fiber coupler 14 is connected with a photoelectric balance receiver 15, so as to photoelectrically convert scattered light signals; the photoelectric balance receiver 15 is connected to a signal processing device 16, and the signal processing device 16 is internally provided with the phase drift elimination method provided by the embodiment, and processes the received signal by using the method;
As shown in fig. 3, fig. 3 is a logic flow diagram of a phase drift cancellation method in the present embodiment, which includes the following steps:
1) Parameter initialization: setting Kalman filter parameters 、、Pulse counterStarting counting;
2) Signal acquisition: pulse detection of $N$ time to obtain Rayleigh scattering signal The signal is generated by the light pulses of 80 MHz and 200 MHz modulated by AOMs (first acousto-optic modulator 4 and second acousto-optic modulator 5);
3) First layer demultiplexing: rayleigh scattering signal The Rayleigh scattering signals generated by the two pulses are separated into independent components through band-pass filters with center frequencies of 80 MHz and 200 MHz respectively, and IQ demodulation is carried out; wherein, 200 MHz signals are subjected to delay alignment to make the physical positions corresponding to 80 MHz and 200 MHz signals consistent, and signal vectors are obtained respectivelyAnd；
4) Second layer demultiplexing: by spectral decomposition of two signal componentsAndIs decomposed into 6 parts, respectivelyAnd is long with the gauge lengthPerforming space difference to obtain space difference vector；
5) Phase drift cancellation: the phase of each current component is obtained through four-quadrant arctangent and unwrappingThen estimating the phase drift at the current moment through Kalman filtering, and subtracting the current phase drift;
6) Rotation vector sum algorithm: the initial phase is subtracted from each component to perform initial rotation, and a new space difference vector is constructed by taking the rotated phase as a argument and taking the modulus of the space difference vector as a modulus value Then vector combination is carried out to obtain；
7) Third layer multiplexing algorithm: for space positionTaking the signal vector in the neighborhood windowCombining to obtain；
8) And (3) phase demodulation: for a pair ofSolving four-quadrant arctangent and unwrapping, and outputting the phase value at the current moment；
9) Repeating the steps 2) to 8) at the next moment;
As shown in fig. 4, fig. 4 (a) shows the signal components when the above step 5) is not performed The change with time of the argument of (b) of FIG. 4 (b) is the signal components when the above step 5) is performedChanges in the irradiance with time; it can be seen that when the kalman filter is not implemented to eliminate the phase drift, the phase errors are gradually accumulated with the lapse of time for each signal component; after Kalman filtering, the phase error is eliminated, thereby proving the effectiveness of the method;
The method carries out Kalman filtering tracking on the phase obtained by demodulating each signal component of the distributed acoustic wave sensing system, estimates the phase drift at the current moment according to the phase drift at the last moment of the component, can be suitable for the distributed acoustic wave sensing system with any multiplexing signal quantity, effectively eliminates the phase drift of each signal component and keeps the phase consistency of each signal component in real time; in addition, for a single signal component distributed acoustic wave sensing system, the method can also effectively eliminate the phase drift of the single signal component distributed acoustic wave sensing system.
The same or similar reference numerals correspond to the same or similar components;
the terms describing the positional relationship in the drawings are merely illustrative, and are not to be construed as limiting the present patent;
It is to be understood that the above examples of the present invention are provided by way of illustration only and not by way of limitation of the embodiments of the present invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.
Claims (10)
1. The distributed acoustic wave sensing phase drift elimination method is characterized by comprising the following steps of:
s1: acquiring each signal component in the distributed acoustic wave sensing system and respectively carrying out phase demodulation to obtain a phase value of each signal component at the current moment;
s2: initializing a Kalman filter, and updating an equation for each signal component by Kalman filtering time, and updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment;
S3: substituting the prior estimated covariance of the current moment into a Kalman gain equation for each signal component, and calculating a Kalman gain coefficient;
S4: calculating the phase drift estimated value of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient; updating posterior estimation covariance of the current moment of each signal component;
s5: and calculating and outputting a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, and finishing the elimination of the phase drift at the current moment of each signal component.
2. The method for eliminating phase drift of distributed acoustic wave sensing according to claim 1, wherein said step S1 comprises:
acquiring each signal component in the distributed acoustic wave sensing system, respectively carrying out phase demodulation, and respectively obtaining the current moment of each signal component Is of the angle of irradiance of (a)And according to the last timeIs a phase value after demodulation ofAt the current timeTo obtain the phase value of each signal component at the current moment。
3. The method for eliminating phase drift of distributed acoustic wave sensing according to claim 2, wherein said step S2 comprises:
initializing state parameters of a Kalman filter;
For each signal component, updating the prior estimated covariance of the current moment according to the posterior estimated covariance of the last moment by using a Kalman filtering time updating equation, wherein the formula is as follows:
Wherein, For the current momentIs used to estimate the covariance of the prior estimate,For the last momentIs used to estimate the covariance of the posterior estimate,Covariance is excited for the process of the kalman filter.
4. A distributed acoustic wave sensing phase drift cancellation method according to claim 3, wherein said step S3 comprises:
for each signal component, substituting the prior estimated covariance of the current moment into a Kalman gain equation, and calculating a Kalman gain coefficient according to the following formula:
Wherein, In order to be a kalman gain factor,Is the measurement covariance of the kalman filter.
5. The method of claim 4, wherein in step S4, calculating the estimated phase drift value of each signal component at the current time comprises:
Updating the state of the Kalman filter, and calculating the estimated value of the phase drift of each signal component at the current moment according to the phase value of each signal component at the current moment and the Kalman gain coefficient, wherein the estimated value of the phase drift of each signal component at the current moment is calculated according to the following formula:
Wherein, For the current momentIs determined by the phase drift estimate of (a); For the last moment Is used for the phase drift estimation of (a).
6. The method of claim 4, wherein in step S4, the a posteriori estimated covariance of the current time of each signal component is updated according to the following formula:
Wherein, For the current momentIs used to estimate covariance.
7. The method for eliminating phase drift of distributed acoustic wave sensing according to claim 5, wherein said step S5 comprises:
and calculating a phase value without drift at the current moment by using the phase value and the phase drift estimated value of the current moment of each signal component, wherein the formula is as follows:
Wherein, The phase value is a phase value without drift at the current moment;
Outputting the phase value of each signal component without drift at the current moment And finishing the elimination of the phase drift of each signal component at the current moment.
8. The method for eliminating phase drift of distributed acoustic wave sensing according to any one of claims 1 to 7, wherein in step S1, the distributed acoustic wave sensing system includes: a distributed optical fiber sensing system based on phase sensitive optical time domain reflectometer phi-OTDR.
9. The method for eliminating phase drift of distributed acoustic wave sensing according to any one of claims 1 to 7, wherein in step S1, each signal component is specifically a multiplexed signal in a distributed acoustic wave sensing system, and the multiplexing includes: space division multiplexing, frequency division multiplexing, wavelength division multiplexing, time division multiplexing, and polarization multiplexing;
or the signal component is embodied as a single signal in a distributed acoustic wave sensing system that is not modulated with a multiplexed signal.
10. The method for eliminating phase drift of distributed acoustic wave sensing according to any one of claims 1 to 7, wherein the order of the kalman filter is a first order.
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