CN106404016A - Fiber sampling signal filtering method and device and fiber sensing system - Google Patents

Abstract

The invention discloses a fiber sampling signal filtering method and device and a fiber sensing system. The method comprises steps that fiber sampling signals are acquired; the fiber sampling signals are converted from light signals reflected by fiber; the fiber sampling signals are filtered through employing a UKF filter to acquire fiber sampling signals after filtering. Through the method, influence of noise on fiber vibration signals is reduced, and accuracy of identification of a fiber vibration source is improved.

Description

Filtering method and device of optical fiber sampling signal and optical fiber sensing system

Technical Field

The invention relates to the technical field of optical fiber sensing, in particular to a filtering method and device of an optical fiber sampling signal and an optical fiber sensing system.

Background

With the development of optical fiber processing technology, optical fibers have been used as sensors in various detection fields for measuring ambient environmental conditions, such as whether an object passes through, and what the object is. When the optical fiber sensor is affected by external interference, partial characteristics of transmission light in the optical fiber are changed, the optical fiber sensing system receives optical signals of the optical fiber, performs photoelectric conversion, analyzes characteristics of the converted electrical signals to judge the change of the optical characteristics, and further determines the environmental conditions of the corresponding position of the optical fiber, such as vehicle intrusion, and the like, so that the monitoring of the environment can be realized.

However, the fiber optic signal acquired by the fiber optic sensing system may have interfering signals that are susceptible to the identification of the fiber optic environmental condition. Therefore, how to effectively filter the acquired optical fiber signals becomes the key of the optical fiber sensing system.

Disclosure of Invention

The invention mainly solves the technical problem of providing a filtering method and a filtering device for an optical fiber sampling signal and an optical fiber sensing system, which can reduce the influence of noise on an optical fiber vibration signal and improve the accuracy of optical fiber vibration source identification.

In order to solve the technical problems, the invention adopts a technical scheme that: a method for filtering a fiber optic sampled signal is provided, the method comprising: acquiring an optical fiber sampling signal; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber; and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal.

Wherein, adopt UKF filter to carry out the filtering to the optic fibre sampled signal, include: establishing a state equation of the optical fiber sampling signal: x is the number of_k+1＝f(x_k,u_k)+ω_k(ii) a And the observation equation: y is_k＝h(x_k)+v_k(ii) a Wherein x is_kSampling the signal state quantity, y, for the optical fiber_kFor optical fibre sampling of signal observations u_kAs system input, ω_kFor the filter noise, v_kTo observe white noise; estimating the state quantity of the optical fiber sampling signal by using the observed quantity and the state equation of the optical fiber sampling signal to obtain a state estimation value of the optical fiber sampling signal; and obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, thereby filtering the optical fiber sampling signal.

The method for estimating the state quantity of the optical fiber sampling signal by using the observed quantity and the state equation of the optical fiber sampling signal to obtain the state estimation value of the optical fiber sampling signal comprises the following steps: estimating the state quantity of the optical fiber sampling signal by using the observation quantity of the optical fiber sampling signal acquired in advance to obtain a first state quantity estimation value:correcting the first state quantity estimated value by using the observed quantity of the optical fiber sampling signal acquired at the current moment to obtain a second state quantity estimated value:wherein,sampling signal state quantities x for optical fibres_kIs determined by the estimated value of (c),sampling signal observations y for optical fibers_kAn estimate of (d).

Wherein, according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, gain of the UKF filter is obtained, which comprises: the gain of the UKF filter is calculated using the following formula:wherein,

wherein, the method also comprises: set of construction points x_i(ii) a Set of point pairs x_iPerforming f (-) nonlinear transformation to obtain transformed point set Y_i＝f(x_i) (ii) a Wherein f (-) is a function corresponding to the equation of state; for the transformed point set Y_i＝f(x_i) And carrying out weighting processing to obtain the mean value and the variance of the observation quantity y of the optical fiber sampling signal.

Wherein, construct the point set x_iThe method comprises the following steps: from the mean of the random vector xAnd density function P_xEstablishing 2n +1 point sets x_i：Wherein n is the optical fiber sampling signal state quantity x_kK is a scale parameter.

Wherein, the transformed point set Y_i＝f(x_i) Carrying out weighting processing to obtain the mean value and the variance of the observation quantity y of the optical fiber sampling signal, wherein the weighting processing comprises the following steps: obtaining the mean weight coefficient W_i ^(m)Sum weight of variance coefficient W_i ^(c)(ii) a The average of the output y is calculated using the following equation:the variance of the output quantity y is calculated using the following formula:

wherein, a mean weight coefficient W is obtained_i ^(m)Sum weight of variance coefficient W_i ^(c)The method comprises the following steps: the mean weight coefficient W is calculated by the following formula_i ^(m)Sum weight of variance coefficient W_i ^(c)：W₀ ^(m)＝k/(n+k)；W₀ ^(c)＝k/(n+k)+(1-α²+β)；W_i ^(m)＝W_i ^(c)＝k/[2(n+k)]I is 1, …,2n, wherein k is α²(n + λ) -n, α, λ and β are preset parameters.

In order to solve the technical problem, the invention adopts another technical scheme that: there is provided an apparatus for filtering a fiber optic sampled signal, the apparatus comprising: the acquisition module is used for acquiring optical fiber sampling signals; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber; and the filtering module is used for filtering the optical fiber sampling signal by adopting a UKF filter so as to obtain the filtered optical fiber sampling signal.

In order to solve the technical problem, the invention adopts another technical scheme that: an optical fiber sensing system is provided, which comprises an optical fiber sensor and a processing terminal; the optical fiber sensor is used for sending a first optical signal at the tail end of the optical fiber and receiving a second optical signal obtained by reflecting the first optical signal from the tail end of the optical fiber; the processing terminal is used for filtering the optical fiber sampling signal corresponding to the second optical signal, wherein the processing terminal comprises the optical fiber sampling signal filtering device as above to filter the optical fiber sampling signal

The invention has the beneficial effects that: different from the prior art, the filtering method of the optical fiber sampling signal comprises the following steps: acquiring an optical fiber sampling signal; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber; and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal. Under the condition that the algorithm difficulty is not increased, the probability density distribution of the nonlinear function is approximated by UT conversion, the mean value and the variance of the optical fiber sampling signal can be verified more accurately, the influence of noise on the optical fiber vibration signal is reduced, and the accuracy of optical fiber vibration source identification is improved.

Drawings

FIG. 1 is a schematic structural diagram of an embodiment of a method for filtering a fiber sampling signal according to the present invention;

FIG. 2 is a schematic structural diagram of an embodiment of an optical fiber sensing system of the present invention;

FIG. 3 is a schematic flow chart of the sub-steps included in step S12 shown in FIG. 1;

FIG. 4 is a schematic flow chart of UT conversion in an embodiment of the filtering method for fiber sampling signals according to the present invention;

FIG. 5 is a schematic structural diagram of an embodiment of a filtering apparatus for fiber sampling signals according to the present invention;

fig. 6 is a schematic structural diagram of another embodiment of the filtering apparatus for fiber sampling signals according to the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

Referring to fig. 1, fig. 1 is a schematic structural diagram of an embodiment of a filtering method for an optical fiber sampling signal according to the present invention, the method including:

s11: and acquiring an optical fiber sampling signal.

The optical fiber sampling signal is obtained by converting an optical signal reflected by the optical fiber.

Fig. 2 shows an optical fiber sensing system, which can detect multiple concurrent vibration sources simultaneously by detecting the reflected light interference intensity variation caused by the phase variation of the backscattered signal in an optical pulse modulation manner, so as to realize early warning and positioning of the vibration sources, for example, in conjunction with fig. 2. The optical fiber sensing system comprises an optical fiber sensor 21, an optical system 23, a photoelectric conversion circuit 24 and a processing terminal 22 which are connected in sequence.

The fiber optic sensor 21 is disposed in an environment to be monitored, such as the ground, to monitor the environmental condition. The optical fiber sensor 21 can use a free fiber core in a common communication optical cable as a sensing unit to perform distributed multi-point vibration measurement. The basic principle is that when external vibration acts on the communication optical cable, the fiber core in the optical cable is deformed, so that the length and the refractive index of the fiber core are changed, and the phase of light in the optical cable is changed. When light is transmitted in the optical cable, Rayleigh scattered light is continuously transmitted backwards due to the action of photons and fiber core lattices. When vibration occurs outside, the phase of the back rayleigh scattering light changes, and the signal light carrying the outside vibration information is processed by the optical system 23 to convert the weak phase change into light intensity change, and then is subjected to photoelectric conversion by the photoelectric conversion circuit 24 and corresponding signal processing, and then enters the human processing terminal 22 for data analysis. The processing terminal 22 judges the occurrence of a vibration event based on the result of the analysis, and confirms the vibration location.

Specifically, the optical fiber sensor 21 periodically emits a first optical signal from one end, the first optical signal may be a pulse signal, such as laser with a pulse width of 10ns, the first optical signal is subjected to rayleigh scattering at various positions in the optical fiber cable to form a second optical signal, and the second optical signal is reflected back to one end of the optical fiber sensor 21. The optical fiber sensor 21 outputs the second optical signal from the one end. The optical system 23 samples the second optical signal to obtain a plurality of optical signals corresponding to different optical fiber positions. The sampling interval may collect optical signals transmitted by the optical fiber at a set distance, for example, the first sampling optical signal corresponds to an optical signal reflected at a position 1 meter away from one end of the optical fiber, the second sampling optical signal corresponds to an optical signal reflected at a position 2 meters away from one end of the optical fiber, and so on.

The optical system 23 converts the sampled optical signals into corresponding electrical signals through the photoelectric conversion circuit 24 for signal processing. Here, the analog signal may be obtained by conversion by a general photoelectric conversion circuit 24 such as APD, and the analog signal may be converted into a digital signal by an analog-to-digital converter and transmitted to the processing terminal 22.

The processing terminal 22 processes the fiber digital signal to determine whether the fiber position corresponding to the fiber digital signal is vibrating. Specifically, the Processing terminal 22 may further include a high-speed data acquisition card (FPGA) module and a Digital Signal Processing (DSP) module, where the FPGA module is configured to acquire the optical fiber Digital signals to obtain a plurality of optical fiber sampling signals. The FPGA module buffers the collected optical fiber sampling signal in an FIFO buffer in the FPGA module, a half-full signal line of the FIFO is connected with the DSP module, and when the FIFO is half full, EDMA transaction of the DSP is triggered to transfer the related data of the optical fiber sampling signal from the FIFO to a memory of the DSP, such as SDRAM. And when the data length in the memory reaches a system set value, processing the optical fiber sampling signal in the memory, such as vibration source identification and the like. The filtering related step and the following singular value decomposition and noise elimination related steps can be executed before the filtering related step and the following singular value decomposition and noise elimination related steps are stored into a memory of the DSP, or the collected optical fiber sampling signal is directly stored into the memory of the DSP, and the filtering related step and the following singular value decomposition and noise elimination related steps are executed after the data length of the memory reaches a set value.

Specifically, the processing terminal collects the fiber sampling signals in real time, the collection interval may be adjusted according to an actual situation, generally, the collection interval is between 0 μ s and 100 μ s, such as 40 μ s, 10 μ s, 100 μ s, and the like, in this embodiment, the collection interval is 0, that is, the processing terminal continuously collects n fiber sampling signals { x (1), x (2), …, x (n) }, where n is an integer greater than 1.

In other embodiments, at least one of the partial steps of the optical system, the photoelectric conversion step and the analog-to-digital conversion step may be executed by the processing terminal 22, for example, the processing terminal 22 is further configured to perform analog-to-digital conversion on the optical fiber analog signal detected by the optical fiber sensor to obtain an optical fiber digital signal; or the processing terminal 22 is further configured to demodulate the optical signal reflected by the optical fiber sensor, convert the demodulated optical signal into an analog electrical signal, and then perform analog-to-digital conversion on the analog electrical signal.

S12: and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal.

UKF (unscented Kalman Filter), the Chinese definition is lossless Kalman filtering, unscented Kalman filtering, or de-aroma Kalman filtering. The method is a combination of a lossless Transform (UT) and a standard Kalman filtering system, and a nonlinear system equation is suitable for the standard Kalman filtering system under a linear assumption through the lossless Transform.

Specifically, referring to fig. 3, S12 specifically includes the following sub-steps:

s121: establishing a state equation of the optical fiber sampling signal: x is the number of_k+1＝f(x_k,u_k)+ω_k(ii) a And the observation equation: y is_k＝h(x_k)+v_k。

Wherein x is_kSampling the signal state quantity, y, for the optical fiber_kFor optical fibre sampling of signal observations u_kAs system input, ω_kFor the filter noise, v_kTo observe white noise.

Specifically, x_kMay be a multi-modal vector, e.g. [ x ]₁，x₂，…，x_k]Where each element in the vector represents a characteristic of the fiber sampled signal, including amplitude, frequency, time, etc. y is_kFor the observed quantity detected by the measuring device, for example, a voltage value obtained with a multimeter, a time obtained with a clock, or the like. u. of_kIs the control quantity of the system at the time k, and when there is no control quantity, u_kMay be 0.

Wherein, ω is_kIs the system noise, i.e. the noise of the filter, andv_kto observe noise, andω_kand v_kIndependent of each other and independent of the system state x.

S122: and estimating the state quantity of the optical fiber sampling signal by utilizing the observed quantity and the state equation of the optical fiber sampling signal to obtain a state estimation value of the optical fiber sampling signal.

Irrespective of the conditional density function P_x|yHow (x | y) is characterized, the least mean square estimate is the conditional mean μ_x|yE { x | y }. The implementation of the nonlinear state filtering process includes two stages of estimation and correction. The method comprises the following specific steps:

1. estimating: estimating the state quantity of the optical fiber sampling signal by using the observation quantity of the optical fiber sampling signal acquired in advance to obtain a first state quantity estimation value:

wherein the goodness of the estimate of the state quantity may be described by the covariance of the estimation error:

2. and (3) correction: correcting the first state quantity estimated value by using the observed quantity of the optical fiber sampling signal acquired at the current moment to obtain a second state quantity estimated value:

wherein,sampling signal state quantities x for optical fibres_kIs determined by the estimated value of (c),sampling signal observations y for optical fibers_kAn estimate of (d).

S123: and obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, thereby filtering the optical fiber sampling signal.

Specifically, the gain of the filter may be obtained by:

wherein,

optionally, a method of UT transformation may be introduced in the above-described embodiments.

The main idea of the UT transformation is that "approximating a probability distribution is easier than approximating a non-linear function", which uses a determined set of points S (also called Sigma points) to characterize the input distribution (or part of the statistical features), then performs a non-linear transformation on each Sigma point separately, and captures the transformed statistical properties by a weighted calculation. This approach treats the system as a "black box" and thus does not rely on specific non-linearities and does not require the calculation of a jacobian matrix.

The key of the UT algorithm is a Sigma point sampling strategy, namely a method for determining the number, the position and the corresponding weight of Sigma points, which ensures that a cost function approaching to certain output performance indexes reaches the minimum while the distribution characteristic of an input variable x is grasped.

Referring specifically to fig. 4, the process of UT conversion is described in detail below:

s41: set of construction points x_i。

In particular, it can be based on the average of the random vector xAnd density function P_xEstablishing 2n +1 point sets x_i：

Wherein n is the optical fiber sampling signal state quantity x_kK is a scale parameter.

In particular, k ═ kα²(n + lambda) -n, which can be adjusted to improve the approximation accuracy. λ is a second scale parameter, typically set to 0 or 3-n. Using the set of sample points x_iA gaussian distribution of states x can be approximated.

S42: set of point pairs x_iPerforming f (-) nonlinear transformation to obtain transformed point set Y_i＝f(x_i)。

Where f (-) is a function corresponding to the equation of state.

Transformed Sigma point set { Y_iThe distribution of y ═ f (x) can be approximated.

S43: for the transformed point set Y_i＝f(x_i) And carrying out weighting processing to obtain the mean value and the variance of the observation quantity y of the optical fiber sampling signal.

Specifically, S43 may specifically include the following steps:

the mean weight coefficient W is calculated by the following formula_i ^(m)Sum weight of variance coefficient W_i ^(c)：

W₀ ^(m)＝k/(n+k)；

W₀ ^(c)＝k/(n+k)+(1-α²+β)；

W_i ^(m)＝W_i ^(c)＝k/[2(n+k)],i＝1,…,2n；

Wherein k is α²(n + λ) -n, α, λ and β are preset parameters.

Wherein α determines the distribution of Sigma points around x, usually set to a small positive number (1 > α ≧ 1 e)^-4) β is a state distribution parameter, which is optimal for a Gaussian distribution β -2, and if the state variable is a single variable, the optimal choice is β -0, adjusting α and λ appropriately can improve the accuracy of the estimated mean, and adjusting β can improve the accuracy of the variance.

The average of the output y is calculated using the following equation:

the variance of the output quantity y is calculated using the following formula:

the UT transform includes the following features:

(1) the probability density distribution of the nonlinear function is approximated instead of approximating the nonlinear function, and even if the model of the system is complex, the difficulty of algorithm realization is not increased;

(2) the accuracy of the statistic of the obtained nonlinear function can reach third order (Taylor expansion);

(3) the non-conductive non-linear functions can be handled without the need to compute Jacobi matrices.

Different from the prior art, the filtering method for the optical fiber sampling signal of the embodiment includes: acquiring an optical fiber sampling signal; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber; and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal. Under the condition that the algorithm difficulty is not increased, the probability density distribution of the nonlinear function is approximated by UT conversion, the mean value and the variance of the optical fiber sampling signal can be verified more accurately, the influence of noise on the optical fiber vibration signal is reduced, and the accuracy of optical fiber vibration source identification is improved.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an embodiment of a filtering apparatus for an optical fiber sampling signal according to the present invention, the apparatus including:

an obtaining module 51, configured to obtain an optical fiber sampling signal; the optical fiber sampling signal is obtained by converting an optical signal reflected by the optical fiber.

And a filtering module 52, configured to filter the optical fiber sampling signal by using a UKF filter to obtain a filtered optical fiber sampling signal.

Optionally, the filtering module 52 is specifically configured to: establishing a state equation of the optical fiber sampling signal: x is the number of_k+1＝f(x_k,u_k)+ω_k(ii) a And the observation equation: y is_k＝h(x_k)+v_k(ii) a Wherein x is_kSampling the signal state quantity, y, for the optical fiber_kFor optical fibre sampling of signal observations u_kAs system input, ω_kFor the filter noise, v_kTo observe white noise; estimating the state quantity of the optical fiber sampling signal by using the observed quantity and the state equation of the optical fiber sampling signal to obtain a state estimation value of the optical fiber sampling signal; and obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, thereby filtering the optical fiber sampling signal.

Optionally, the filtering module 52 is specifically configured to: estimating the state quantity of the optical fiber sampling signal by using the observation quantity of the optical fiber sampling signal acquired in advance to obtain a first state quantity estimation value:correcting the first state quantity estimated value by using the observed quantity of the optical fiber sampling signal acquired at the current moment to obtain a second state quantity estimated value:wherein,sampling signal state quantities x for optical fibres_kIs determined by the estimated value of (c),sampling signal observations y for optical fibers_kAn estimate of (d).

Optionally, a filtering module 52 is specifically used for: the gain of the UKF filter is calculated using the following formula:wherein,

optionally, the filtering module 52 is further configured to: set of construction points x_i(ii) a Set of point pairs x_iPerforming f (-) nonlinear transformation to obtain transformed point set Y_i＝f(x_i) (ii) a Wherein f (-) is a function corresponding to the equation of state; for the transformed point set Y_i＝f(x_i) And carrying out weighting processing to obtain the mean value and the variance of the observation quantity y of the optical fiber sampling signal.

Optionally, the filtering module 52 is specifically configured to: from the mean of the random vector xAnd density function P_xEstablishing 2n +1 point sets x_i：Wherein n is the optical fiber sampling signal state quantity x_kK is a scale parameter.

Optionally, the filtering module 52 is specifically configured to: obtaining the mean weight coefficient W_i ^(m)Sum weight of variance coefficient W_i ^(c)(ii) a The average of the output y is calculated using the following equation:the variance of the output quantity y is calculated using the following formula:

optionally, the filtering module 52 is specifically configured to: the mean weight coefficient W is calculated by the following formula_i ^(m)Sum weight of variance coefficient W_i ^(c)：W₀ ^(m)＝k/(n+k)；W₀ ^(c)＝k/(n+k)+(1-α²+β)；W_i ^(m)＝W_i ^(c)＝k/[2(n+k)]I is 1, …,2n, wherein k is α²(n + λ) -n, α, λ and β are preset parameters.

It can be understood that the modules are respectively configured to execute corresponding steps in the foregoing method embodiments, and the specific execution process is as described in the foregoing method embodiments and is not described herein again.

Referring to fig. 6, fig. 6 is a schematic structural diagram of another embodiment of the filtering apparatus for fiber sampling signals according to the present invention, which includes a processor 61, a memory 62, a receiver 63, and a transmitter 64.

The processor 61, the memory 62, the receiver 63 and the transmitter 64 may be one or more.

The receiver 63 is used for receiving information transmitted by an external device, for example, an optical fiber sampling signal transmitted by an optical fiber sensor or a state quantity extracted from the optical fiber sampling signal.

The transmitter 64 is used to transmit the result of the processing, for example, an alarm signal may be transmitted to an alarm, a display, etc., although in other embodiments, the transmitter 64 may not be present.

The memory 62 is used for storing system files, application software, and preset algorithms, functions, parameters, thresholds, etc., and may also store historical vibration signals of the optical fiber or extracted historical state quantities of vibration levels. The memory 62 may include at least one of a read-only memory, a random access memory, and a non-volatile random access memory (NVRAM), among others.

The processor 61 is configured to perform the following steps:

acquiring a fiber sampling signal through a receiver 63; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber; and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal.

Optionally, the processor 61 is specifically configured to: establishing a state equation of the optical fiber sampling signal: x is the number of_k+1＝f(x_k,u_k)+ω_k(ii) a And the observation equation: y is_k＝h(x_k)+v_k(ii) a Wherein x is_kSampling the signal state quantity, y, for the optical fiber_kFor optical fibre sampling of signal observations u_kAs system input, ω_kFor the filter noise, v_kTo observe white noise; estimating the state quantity of the optical fiber sampling signal by using the observed quantity and the state equation of the optical fiber sampling signal to obtain a state estimation value of the optical fiber sampling signal; and obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, thereby filtering the optical fiber sampling signal.

Optionally, the processor 61 is specifically configured to: estimating the state quantity of the optical fiber sampling signal by using the observation quantity of the optical fiber sampling signal acquired in advance to obtain a first state quantity estimation value:correcting the first state quantity estimated value by using the observed quantity of the optical fiber sampling signal acquired at the current moment to obtain a second state quantity estimated value:wherein,sampling signal state quantities x for optical fibres_kIs determined by the estimated value of (c),sampling signal observations y for optical fibers_kAn estimate of (d).

Optionally, the processor 61 is specifically configured to: the gain of the UKF filter is calculated using the following formula:wherein,

optionally, the processor 61 is further configured to: set of construction points x_i(ii) a Set of point pairs x_iPerforming f (-) nonlinear transformation to obtain transformed point set Y_i＝f(x_i) (ii) a Wherein f (-) is a function corresponding to the equation of state; for the transformed point set Y_i＝f(x_i) And carrying out weighting processing to obtain the mean value and the variance of the observation quantity y of the optical fiber sampling signal.

Optionally, the processor 61 is specifically configured to: from the mean of the random vector xAnd density function P_xEstablishing 2n +1 point sets x_i：Wherein n is the optical fiber sampling signal state quantity x_kK is a scale parameter.

Optionally, the processor 61 is specifically configured to: obtaining the mean weight coefficient W_i ^(m)Sum weight of variance coefficient W_i ^(c)(ii) a The average of the output y is calculated using the following equation:the variance of the output quantity y is calculated using the following formula:

optionally, the processor 61 is specifically configured to: the mean weight coefficient W is calculated by the following formula_i ^(m)Sum weight of variance coefficient W_i ^(c)：W₀ ^(m)＝k/(n+k)；W₀ ^(c)＝k/(n+k)+(1-α²+β)；W_i ^(m)＝W_i ^(c)＝k/[2(n+k)]I is 1, …,2n, wherein k is α²(n + λ) -n, α, λ and β are preset parameters.

The processor 61 may also be referred to as a CPU (Central Processing Unit). In a particular application, the various components of the terminal are coupled together by a bus, which may include a power bus, a control bus, a status signal bus, etc., in addition to a data bus. But for clarity of illustration the various buses are labeled as buses in the figures.

It will be appreciated that the processor 61 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 61. The processor 61 described above may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 62, and the processor 61 reads the information in the corresponding memory, and completes the steps of the above method in combination with the hardware thereof.

In the embodiments provided in the present invention, it should be understood that the disclosed method and apparatus can be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated units in the other embodiments described above may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A method for filtering a sampled optical fiber signal, comprising:

acquiring an optical fiber sampling signal; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber;

and filtering the optical fiber sampling signal by adopting a UKF filter to obtain a filtered optical fiber sampling signal.

2. The method of claim 1,

adopt the UKF filter to right the filtering of optic fibre sampling signal includes:

establishing a state equation of the optical fiber sampling signal:

x_k+1＝f(x_k,u_k)+ω_k；

and the observation equation:

y_k＝h(x_k)+v_k；

wherein x is_kSampling the signal state quantity, y, for said fiber_kSampling the signal observations for said fiber_kAs system input, ω_kIs the noise of the filter, v_kTo observe white noise;

estimating the state quantity of the optical fiber sampling signal by using the observed quantity of the optical fiber sampling signal and the state equation to obtain a state estimation value of the optical fiber sampling signal;

and obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal, thereby filtering the optical fiber sampling signal.

3. The method of claim 2,

the estimating the state quantity of the optical fiber sampling signal by using the observed quantity of the optical fiber sampling signal and the state equation to obtain the state estimation value of the optical fiber sampling signal includes:

estimating the state quantity of the optical fiber sampling signal by using the observation quantity of the optical fiber sampling signal acquired in advance to obtain a first state quantity estimation value:

${\stackrel{\‾}{x}}_k=E\left\{x_k\right|Y^{k-1}\};$

correcting the first state quantity estimated value by using the observed quantity of the optical fiber sampling signal acquired at the current moment to obtain a second state quantity estimated value:

${\hat{x}}_k=E\left\{x_k\right|Y^k\}={\stackrel{\‾}{x}}_k+K_k\[y_k-{\stackrel{\‾}{y}}_k\];$

wherein,sampling the signal state quantity x for said optical fiber_kIs determined by the estimated value of (c),sampling the signal observations y for said optical fiber_kAn estimate of (d).

4. The method of claim 3,

the obtaining the gain of the UKF filter according to the observed quantity of the optical fiber sampling signal and the state estimation value of the optical fiber sampling signal comprises:

the gain of the UKF filter is calculated using the following formula:

$K_k=P_{xy}\left(k\right)P_y^{-1}\left(k\right);$

wherein,

$P_y\left(k\right)=E\{\[y_k-h\left({\stackrel{\‾}{x}}_k\right)\]{\[y_k-h\left({\stackrel{\‾}{x}}_k\right)\]}^T|Y^{k-1}\};$

$P_{xy}\left(k\right)=E\{\[x_k-{\stackrel{\‾}{x}}_k\]{\[y_k-h\left({\stackrel{\‾}{x}}_k\right)\]}^T|Y^{k-1}\}.$

5. the method of claim 2, further comprising:

set of construction points x_i；

For the point set x_iPerforming f (-) nonlinear transformation to obtain transformed point set Y_i＝f(x_i) (ii) a Wherein f (-) is a function corresponding to the equation of state;

for the transformed point set Y_i＝f(x_i) And carrying out weighting processing to obtain the mean value and the variance of the optical fiber sampling signal observed quantity y.

6. The method of claim 5,

the set of construction points x_iThe method comprises the following steps:

from the mean of the random vector xAnd density function P_xEstablishing 2n +1 point sets x_i：

$x_i=\left\{\begin{array}{c}\stackrel{\‾}{x}+{\left(\sqrt{\left(n+k\right)P_x}\right)}_i,i=1,2,...,n\\ \stackrel{\‾}{x}-{\left(\sqrt{\left(n+k\right)P_x}\right)}_i,i=n+1,...2n\\ \stackrel{\‾}{x},i=0\end{array}\right.;$

Wherein n is the optical fiber sampling signal state quantity x_kK is a scale parameter.

7. The method of claim 5,

the pair of transformed point sets Y_i＝f(x_i) Performing weighting processing to obtain a mean value and a variance of the observation quantity y of the optical fiber sampling signal, wherein the weighting processing comprises the following steps:

obtaining the mean weight coefficient W_i ^(m)Sum weight of variance coefficient W_i ^(c)；

The average of the output y is calculated using the following equation:

$\stackrel{\‾}{y}\≈\underset{i=0}{\overset{2n}{\Σ}}{W}_i^{\left(m\right)}{Y}_i;$

the variance of the output quantity y is calculated using the following formula:

$P_y\≈\underset{i=0}{\overset{2n}{\Σ}}{W}_i^{\left(c\right)}(Y_i-\stackrel{\‾}{y}){(Y_i-\stackrel{\‾}{y})}^T.$

8. the method of claim 7,

the obtained mean weight coefficient W_i ^(m)Sum weight of variance coefficient W_i ^(c)The method comprises the following steps:

the mean weight coefficient W is calculated by the following formula_i ^(m)Sum weight of variance coefficient W_i ^(c)：

$W_0^{\left(m\right)}=k/(n+k);$

$W_0^{\left(c\right)}=k/(n+k)+(1-{\mathrm{\α}}^2+\mathrm{\β});$

W_i ^(m)＝W_i ^(c)＝k/[2(n+k)],i＝1,…,2n；

Wherein k is α²(n + λ) -n, α, λ and β are preset parameters.

9. An apparatus for filtering a sampled optical fiber signal, comprising:

the acquisition module is used for acquiring optical fiber sampling signals; the optical fiber sampling signal is obtained by converting an optical signal reflected by an optical fiber;

and the filtering module is used for filtering the optical fiber sampling signal by adopting a UKF filter so as to obtain a filtered optical fiber sampling signal.

10. An optical fiber sensing system is characterized by comprising an optical fiber sensor and a processing terminal;

the optical fiber sensor is used for sending a first optical signal at the tail end of an optical fiber and receiving a second optical signal obtained by reflecting the first optical signal from the tail end of the optical fiber;

the processing terminal is configured to filter an optical fiber sampling signal corresponding to the second optical signal, wherein the processing terminal includes the optical fiber sampling signal filtering apparatus according to claim 9, so as to filter the optical fiber sampling signal.