Signal processing method, apparatus, device, system, storage medium and product

Abstract

The application is a divisional application of 202610037205.X, and discloses a signal processing method, device, equipment, system, storage medium and product. A to-be-processed signal output by a target signal after passing through a nonlinear device is processed in sections to obtain a plurality of first signal regions; a preset type determination strategy is used to determine region types to which the plurality of first signal regions correspond respectively, wherein the preset type determination strategy is determined based on a steepness of a waveform shape; for each first signal region, a compensation strategy matched with a region type corresponding to the current first signal region is used to compensate a sub-signal in a corresponding region of the target signal for the current first signal region by using an ideal signal, to obtain a compensation signal corresponding to the current first signal region; and a pre-distortion signal corresponding to the ideal signal is determined according to the compensation signals corresponding to the plurality of first signal regions respectively. The application can provide an effective pre-distortion signal for a signal with complex and changeable forms.

Description

[0001] This application is a divisional application. The original application has the application number 202610037205.X, the application date is January 13, 2026, and the invention title is "Signal Processing Method, Apparatus, Device, System, Storage Medium and Product". Technical Field

[0002] This invention relates to the fields of signal processing, signal predistortion, and fiber optic sensing, and particularly to a signal processing method, apparatus, device, system, storage medium, and product. Background Technology

[0003] In signal transmission systems, nonlinear devices often exist along the signal transmission path, such as fiber optic amplifiers, radio frequency power amplifiers, ultrasonic transducers, or any other signal channels with dynamic nonlinearity. Signals will experience nonlinear distortion after passing through nonlinear devices.

[0004] To reduce the impact of nonlinear devices on signal transmission, signal predistortion techniques can be used to predistort the signal to be transmitted. Currently, predistortion algorithms are mainly used to process simple, single-shaped rectangular pulses. Typically, through experiments or modeling, a predistortion signal corresponding to the original signal with the opposite distortion characteristics produced by the nonlinear device is found. This predistortion signal is then used to replace the original signal and is input into the nonlinear device for transmission to counteract the effects of nonlinear distortion.

[0005] However, for signals with non-uniform waveform changes, existing predistortion algorithms struggle to produce high-quality predistortion signals. Summary of the Invention

[0006] This invention provides signal processing methods, apparatus, devices, systems, storage media, and products that can improve the quality of predistorted signals.

[0007] According to one aspect of the present invention, a signal processing method is provided, comprising: The target signal is processed by partitioning the output signal after passing through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; A preset type determination strategy is used to determine the region type corresponding to the plurality of first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape; For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region. Based on the compensation signals corresponding to the plurality of first signal regions, the predistortion signal corresponding to the ideal signal is determined.

[0008] According to another aspect of the present invention, a signal processing apparatus is provided, comprising: The first partitioning module is used to partition the target signal output after passing through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; The type determination module is used to determine the region type corresponding to the plurality of first signal regions respectively using a preset type determination strategy, wherein the preset type determination strategy is determined based on the steepness of the waveform shape; The compensation module is used to adopt a compensation strategy that matches the region type corresponding to the current first signal region for each first signal region, and use the ideal signal to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region. The predistortion signal determination module is used to determine the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the plurality of first signal regions respectively.

[0009] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the signal processing method according to any embodiment of the present invention.

[0010] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the signal processing method described in any embodiment of the present invention.

[0011] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the signal processing method described in any embodiment of the present invention.

[0012] According to another aspect of the present invention, a signal processing system is provided, the signal processing system comprising a signal generator, a laser, an optical fiber amplifier, a coupler, an optical attenuator, a wavelength division multiplexer, an optical switch, a first detector, a second detector, a signal acquisition module, and the electronic equipment described in the embodiments of the present invention; wherein, the signal generator is connected to the laser and is used to control the laser to output a set signal to the optical fiber amplifier, wherein the set signal is correlated with an ideal signal; the coupler is connected to the optical fiber amplifier and is used to divide the set signal into a first signal and a second signal, wherein the first signal is a target signal and the second signal is a measurement signal; the optical attenuator is connected to the coupler. The wavelength division multiplexer (WDM) is used to receive the target signal; the port of the WDM is connected to the coupler to receive the measurement signal, and the WDM is also connected to the probe fiber and the first detector respectively; the optical switch is used to connect to the optical attenuator during the pre-distortion signal debugging stage and to the WDM during the measurement stage; the optical switch is also connected to the second detector; both the first detector and the second detector are connected to the signal acquisition module; the signal acquisition module is connected to the electronic device to input the acquired signal to be processed to the electronic device; the electronic device is connected to the signal generator to send a signal generation command to the signal generator to generate the set signal.

[0013] The technical solution of this invention involves partitioning the target signal output after passing it through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; a preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape; for each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted, and the ideal signal is used to compensate the sub-signals of the current first signal region within the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region; based on the compensation signals corresponding to the multiple first signal regions, the predistortion signal corresponding to the ideal signal is determined. The above technical solution obtains multiple signal regions by partitioning the signal to be processed, and determines the region type corresponding to each signal region according to a preset type determination strategy. It then uses a compensation strategy that matches the region type to compensate the sub-signals of the signal region, thus realizing a differentiated compensation strategy. Compared with a single compensation strategy, this ensures that the obtained pre-distorted signal is more compatible with the morphological characteristics of the signal to be processed, thereby efficiently solving the waveform distortion problem caused by the target signal passing through nonlinear devices. In addition, the partitioning strategy based on the steepness of the waveform shape enables the present invention to efficiently identify the region type, providing a foundation for subsequently formulating corresponding compensation strategies for different region types.

[0014] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a signal processing method provided according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of a signal region partitioning provided according to an embodiment of the present invention; Figure 3 This is a flowchart of a signal processing method provided according to Embodiment 2 of the present invention; Figure 4 This is a flowchart of a signal processing method provided according to Embodiment 3 of the present invention; Figure 5 This is a schematic diagram of a temperature curve provided according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of a signal processing device according to Embodiment 4 of the present invention; Figure 7 This is a schematic diagram of the structure of an electronic device that implements the signal processing method of Embodiment 5 of the present invention; Figure 8 A schematic diagram of the structure of a signal processing system provided according to an embodiment of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first," "second," and "target," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] Example 1 Figure 1 This is a flowchart of a signal processing method according to an embodiment of the present invention. This embodiment is applicable to signal processing or generating pre-distortion signals, etc. The method can be executed by a signal processing device, which can be implemented in hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes: S101. The target signal is processed by partitioning the output signal after passing through the nonlinear device to obtain multiple first signal regions, wherein the target signal is related to the ideal signal.

[0020] In this embodiment, the target signal can be either an optical fiber signal or an electromagnetic signal; the specific signal type is not limited. This embodiment uses an optical fiber signal as an example for description. The target signal can be understood as a signal generated by the laser adjusted by the signal generator in any iteration round. The ideal signal can be understood as the signal expected to be output after the target signal passes through the nonlinear device. In practical applications, the ideal signal can be used as the target signal input to the nonlinear device in the first iteration round, and the target signal in the first iteration round can be a pulse signal.

[0021] Nonlinear devices can be understood as devices that cause nonlinear distortion to the waveform of the target signal, such as erbium-doped fiber amplifiers (EDFAs) and semiconductor optical amplifiers. Correspondingly, if the target signal is an electromagnetic signal, the nonlinear device is one that causes nonlinear distortion to the waveform of the electromagnetic signal. This invention does not impose specific limitations on nonlinear devices. The signal to be processed can be understood as the signal output after the target signal passes through the nonlinear device. The waveform of the signal to be processed generally exhibits nonlinear distortion; for example, the amplitude of the signal to be processed may show asymmetric deviation, or the frequency-time mapping relationship may be distorted. The purpose of iteration is to make the signal to be processed output after the target signal passes through the nonlinear device approximate the ideal signal. The first signal region can be understood as the signal region obtained after dividing or partitioning the signal to be processed according to a partitioning strategy. Each first signal region is generally a continuous signal region in the time or frequency domain.

[0022] For example, taking the first iteration process as an example, the target signal is input into the nonlinear device to obtain the signal to be processed. The signal to be processed is partitioned according to the sliding window method to obtain multiple first signal regions. The window length of the sliding window can be a fixed value or a dynamic value.

[0023] Optionally, the signal to be processed is partitioned using a sliding window approach to obtain multiple first signal regions. The window length of the sliding window is determined based on the time interval between adjacent troughs in the signal to be processed; each first signal region includes at most one peak. For example, such as... Figure 2 As shown, each trough of the signal to be processed is selected, and the time interval between two adjacent troughs is used as the window length of the sliding window. The advantage of this setting is that the window length of the sliding window can be dynamically generated, so that each first signal region after partitioning has better distinguishability, and it can be ensured that the obtained first signal region basically contains the complete waveform fluctuation cycle, which facilitates the subsequent compensation of the signal in the first signal region based on the waveform characteristics of the first signal region.

[0024] In this embodiment, the target signal after passing through the nonlinear device is partitioned for processing. In subsequent steps, different compensation strategies or correction parameters are used to compensate the signal of each region type, thereby obtaining an accurate compensation signal to ensure that the final predistortion signal can offset the distortion of the nonlinear device. In contrast, the traditional scheme uses only a single extraction parameter when extracting the pulse envelope, which cannot simultaneously adapt to the peak pulse characteristics of the high-frequency part and the flat-top characteristics of the low-frequency part. Consequently, the measured signal used in each iteration is inaccurate, making it difficult for the obtained predistortion signal to overcome the distortion problem of the nonlinear device, resulting in a final output waveform that is even worse than before the iteration.

[0025] S102. A preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions. The preset type determination strategy is based on the steepness of the waveform shape.

[0026] In this embodiment, the preset type determination strategy is based on the steepness of the waveform shape. For example, the steepness of the waveform shape can be determined by calculating the slope between the peaks and troughs in the first signal region, and a steepness threshold can be set. By comparing the steepness of the current first signal region with the steepness threshold, the region type corresponding to the current first signal region can be determined. The region type can be preset. For example, the region type can include high-frequency spike regions and low-frequency flat-top regions, etc. The present invention does not limit the specific form of the region type. In addition, multiple steepness thresholds can be set to make more detailed divisions of the region type of the first signal region, so as to make more accurate compensation for the signal of the first signal region in the future.

[0027] S103. For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals in the corresponding region of the target signal of the current first signal region to obtain the compensation signal corresponding to the current first signal region.

[0028] In this embodiment, the compensation strategy can be formulated according to the region type. For example, for high-frequency peak regions, a correction signal can be generated based on the high-frequency local features of the ideal signal; for low-frequency flat-top regions, a correction signal can be generated based on the low-frequency global features of the ideal signal. The specific compensation strategy can be determined based on the actual application scenario. A sub-signal can be understood as the signal within each first signal region of the target signal, for example... Figure 2 The signal between any two adjacent troughs can be considered a sub-signal. The compensation signal can be understood as the signal corresponding to each sub-signal after compensation processing.

[0029] For example, for each first signal region, a compensation strategy matching the current first signal region can be determined based on the region type corresponding to the current first signal region. For instance, if the region type of the current first signal region corresponds to a high-frequency spike region, then a correction signal can be generated based on the high-frequency local features of the ideal signal, thereby compensating the sub-signals in the region corresponding to the current first signal region in the target signal, and thus obtaining the compensation signal corresponding to the sub-signals.

[0030] S104. Determine the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the multiple first signal regions respectively.

[0031] In this embodiment, the predistortion signal can be understood as a signal that can offset the distortion effect of nonlinear devices after compensating the sub-signals in each first signal region of the target signal based on the ideal signal; the predistortion signal can be obtained by integrating the compensation signals corresponding to each sub-signal.

[0032] This invention provides a signal processing method that partitions the output signal of a target signal after passing it through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal. A preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape. For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is used to compensate the sub-signals of the current first signal region within the corresponding region of the target signal using the ideal signal, resulting in a compensation signal corresponding to the current first signal region. Based on the compensation signals corresponding to the multiple first signal regions, a pre-distortion signal corresponding to the ideal signal is determined. The above technical solution obtains multiple signal regions by partitioning the signal to be processed, and determines the region type corresponding to each signal region according to a preset type determination strategy. It then uses a compensation strategy that matches the region type to compensate the sub-signals of the signal region, thus realizing a differentiated compensation strategy. Compared with a single compensation strategy, this ensures that the obtained pre-distorted signal is more compatible with the morphological characteristics of the signal to be processed, thereby efficiently solving the waveform distortion problem caused by the target signal passing through nonlinear devices. In addition, the partitioning strategy based on the steepness of the waveform shape enables the present invention to efficiently identify the region type, providing a foundation for subsequently formulating corresponding compensation strategies for different region types.

[0033] In some embodiments, each first signal region includes at most one peak; the region type includes a first region type and a second region type, wherein the steepness corresponding to the first region type is higher than the steepness corresponding to the second region type; wherein, the region type corresponding to the plurality of first signal regions is determined by a preset type determination strategy, including: for each first signal region, determining the rise time corresponding to the current first signal region, determining the shape factor of the waveform in the current first signal region based on the rise time, determining that the current first signal region corresponds to the first region type if the shape factor is less than a first threshold, and determining that the current first signal region corresponds to the second region type if the shape factor is greater than or equal to the first threshold. The advantage of this setting is that the steepness of each first signal region can be accurately measured based on the rise time corresponding to each first signal region, thereby achieving accurate division of the region type of each first signal region.

[0034] In this embodiment, rise time can be understood as the time taken for the waveform to rise from a first peak position to a second peak position within each first signal region, for example, the time taken for the waveform to rise from 10% to 90% of its amplitude. Shape factor can be understood as a parameter used to measure the steepness of the waveform within the current first signal region. Shape factor is generally a positive integer; the larger the shape factor, the steeper the waveform. For example, if the shape factor of a waveform is 3, then the waveform can be considered a super-Gaussian pulse. First threshold can be understood as a pre-set threshold for the shape factor, used to determine the region type of each first signal region. The steepness corresponding to the first region type is higher than that corresponding to the second region type. For example, the first region type can be a high-frequency spike region, corresponding to higher signal volatility, while the second region type can be a low-frequency flat-top region, corresponding to lower signal volatility.

[0035] For example, the shape factor of the waveform in the current first signal region can be calculated based on the rise time using the following expression: ; in, Represents the rising time; Represents shape factor; Representing the pulse half-width, it can be the time interval between two corresponding points of the signal amplitude in the current first signal region at the peak value 1 / e.

[0036] Example 2 Figure 3 This is a flowchart of another signal processing method provided by an embodiment of the present invention, which is a further refinement based on the above embodiments. Figure 3 As shown, the method includes: S301. The target signal is processed by partitioning the output signal after passing through the nonlinear device to obtain multiple first signal regions, wherein the target signal is related to the ideal signal.

[0037] Here, the signal is understood to be a signal with symmetrical properties.

[0038] In this embodiment, the signal can be a pulse signal with time-domain or frequency-domain symmetry characteristics, such as a swept-frequency optical pulse or a Gaussian pulse.

[0039] S302. A preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape.

[0040] In this embodiment, to ensure higher fidelity for signals of different region types, different compensation methods can be used. For the first region type, the signal is more volatile, resulting in significant amplitude and frequency distortions. For the second region type, the signal is smoother, primarily causing amplitude distortion. Therefore, different calculation methods can be used to determine the correction factor for different region types, allowing for more precise compensation for each first signal region in subsequent steps. Specifically, the first correction factor in the first region type (which can be used to compensate for amplitude distortion) can be determined via S303 to S304, and the second correction factor in the first region type (which can be used to compensate for frequency distortion) can be determined via S305. Figure 3 As shown, steps S303 to S304 and step S305 can be executed in parallel, and step S306 is executed after the execution is completed.

[0041] S303. Based on symmetry, the plurality of first signal regions are divided into a plurality of first signal region pairs.

[0042] For example, multiple first signal regions can be divided according to the number n of troughs in the signal to be processed, resulting in multiple pairs of first signal regions; wherein, if the number n of troughs is even, then the first pair of troughs can be divided into multiple pairs of first signal regions. The first trough to the second The sampling point positions corresponding to the peaks between the troughs are used as the division positions. Two first signal regions that are symmetrical to each other with respect to the division positions are defined as a pair of first signal regions. For example, Figure 2 As shown, the signal to be processed has 26 troughs. Therefore, the sampling point position corresponding to peak 13 between trough 13 and trough 14 can be used as the dividing position. Two first signal regions that are symmetrical to each other at the dividing position are defined as a pair of first signal regions, as shown below. Figure 2The signal region between trough 13 and peak 13 and the signal region between peak 13 and trough 14 constitute one signal region pair; the signal region between trough 12 and trough 13 and the signal region between trough 14 and trough 15 constitute another signal region pair. These, along with two first signal regions whose division positions are symmetrical, form a first signal region pair. This invention does not list all of them. Correspondingly, if the number of troughs n is odd, then the first... The sampling point location corresponding to each trough is used as the division position, and two first signal regions that are symmetrical to the division position are determined as a first signal region pair.

[0043] S304. For each pair of first signal regions, calculate the first peak difference between the two symmetrical first signal regions in the current pair of first signal regions. Determine the first error value based on the quotient of the square of the first peak difference and the square of the ideal peak value of the region corresponding to the ideal signal. The first error value is used to determine the first correction factor, which is greater than 1.

[0044] In this embodiment, the two first signal regions in the same first signal region pair can be understood as being symmetrical in position. To facilitate the distinction between the two first signal regions, they can be referred to as the front signal region and the mirror signal region. During actual acquisition, due to the distortion of the target signal caused by nonlinear devices, the waveforms in the front signal region and the mirror signal region are not symmetrical. Therefore, there is a difference in the peak values ​​between the front signal region and the mirror signal region. The first peak difference can be understood as the difference between the peak amplitudes of the two first signal regions in the current first signal region pair, i.e., the difference between the peak amplitudes of the front signal region and the mirror signal region. The ideal peak value can be the peak amplitude of the ideal signal in any of the first signal regions in the current first signal region pair. That is, the ideal peak value can be the peak value of the front signal region in the current first signal region pair, or it can be the peak value of the mirror signal region in the current first signal region pair, because the waveforms of the front signal region and the mirror signal region in each first signal region pair of the ideal signal are symmetrical.

[0045] For example, the first error value can be determined using the following expression: ; in, Representing the The first error value for a first signal region pair; Representing the The peak value of the preceding signal region in the first signal region pair; Representing the The peak value of the mirror signal region in the first signal region pair; The ideal signal is represented in the first place. The ideal peak value in the first signal region pair.

[0046] In this embodiment, the first correction factor of the current first signal region pair can be used to compensate the two first signal regions in the current first signal region pair. The first correction factor is greater than 1. The advantage of this setting is that the waveform amplitude of the two first signal regions in the current first signal region pair can be efficiently stretched or compressed by the first correction factor greater than 1, so that the waveform amplitude of the two first signal regions is closer to the waveform amplitude of the corresponding position in the ideal signal. For example, the stretching or compression of the waveform amplitude can be efficiently completed by multiplying or dividing with the first correction factor. For example, the first correction factor can be obtained by adding 1 to the first error value.

[0047] S305. Perform a short-time Fourier transform on the signal to be processed to obtain the corresponding first time-frequency distribution curve, extract the ridge line of the first time-frequency distribution curve, and determine the second error value based on the difference between the ridge line of the first time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal. The second error value is used to determine the second correction factor.

[0048] In this embodiment, the ridge line can be understood as a curve obtained by connecting the peaks of the time-frequency distribution curve. The ridge line can be used to reflect the core path of the signal's main frequency change over time. For example, the horizontal axis of the first time-frequency distribution curve is time, and the vertical axis is the frequency of the signal to be processed. By selecting the frequency point with the largest frequency amplitude at each time point and connecting these frequency points according to the time relationship, the ridge line of the first time-frequency distribution curve can be obtained.

[0049] The sweep curve corresponding to the ideal signal is also a frequency-time distribution curve. The sweep curve characterizes the frequency change process of the signal under ideal conditions. The horizontal axis of the sweep curve represents time, and the vertical axis represents the ideal frequency (which can be understood as the frequency value of the ideal signal at each moment). The second error value at each moment can be obtained by dividing the frequency value of the ridge of the first time-frequency distribution curve at each moment by the frequency value of the sweep curve corresponding to the ideal signal at the same moment. The second error value directly reflects the difference between the frequency of the signal under processing and the ideal frequency at each moment. If the second error value is less than 1, it indicates that the frequency of the signal under processing is compressed at the current moment; if the second error value is greater than 1, it indicates that the frequency of the signal under processing is stretched at the current moment. Therefore, when compensating the signal under processing later, the corresponding second correction factor can be determined based on the second error value of the signal under processing at each moment. The specific determination method can be flexibly adjusted according to the compensation method. For example, the second error value can be directly used as the second correction factor. When compensating the signal under processing later, the distortion of the signal under processing can be offset by dividing it with the second correction factor, thus achieving compensation.

[0050] Optionally, to ensure more accurate compensation for each first signal region in the subsequent processing, a short-time Fourier transform can be performed on each first signal region in the signal to be processed to obtain the first time-frequency distribution curve corresponding to the current first signal region. The ridge of the first time-frequency distribution curve is extracted, and the second error value is determined based on the difference between the ridge of the first time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal in the current first signal region. The second correction factor for the current first signal region is then determined based on the second error.

[0051] S306. For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region.

[0052] Optionally, this step includes the following steps A1 to A2: A1. For each first signal region, in response to the first region type corresponding to the current first signal region, determine the comparison result between the peak value of the current first signal region and the peak value of another first signal region in the first signal region pair to which the current first signal region belongs; if the comparison result is greater than (i.e., the peak value of the current first signal region is greater than the peak value of another first signal region in the first signal region pair to which the current first signal region belongs), then divide the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal by the first correction factor and by the second correction factor to obtain the corresponding compensation signal; if the comparison result is less than (i.e., the peak value of the current first signal region is less than the peak value of another first signal region in the first signal region pair to which the current first signal region belongs), then multiply the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal by the first correction factor and divide by the second correction factor to obtain the corresponding compensation signal.

[0053] For example, if the current first signal region is of the first region type, the signal region with the larger peak value can be determined by comparing the peak values ​​of the two first signal regions in a pair corresponding to the current first signal region. For the signal region with the larger peak value, the amplitude of the sub-signal corresponding to the target signal in that region is divided by a first correction factor and then by a second correction factor, and the result is used as the amplitude of the compensation signal for that region. For the signal region with the smaller peak value, the amplitude of the sub-signal corresponding to the target signal in that region is multiplied by the first correction factor and then divided by the second correction factor, and the result is used as the amplitude of the compensation signal for that region. Through the above processing, the corresponding amplitude compensation strategy and frequency compensation strategy can be selected according to the signal characteristics of each signal region corresponding to the first region type, thereby achieving accurate compensation of the target signal.

[0054] For example, in the first During the next iteration, if the current first signal region (e.g., labeled as...) If a signal is classified as a first region type, and its peak value is greater than the peak value of another first signal region in its corresponding first signal region pair, then the compensation signal of the current first signal region at a certain sampling point (e.g., labeled as...) The amplitude of ) can be calculated using the following expression: ; in, Represents signal area The Middle The sampling point at the th sampling point The amplitude of the compensation signal corresponding to the nth iteration can be used as the value of the nth iteration. The amplitude of the target signal during the next iteration; Represents signal area The Middle The sampling point at the th sampling point The amplitude of the target signal corresponding to the nth iteration, i.e., the nth iteration The amplitude of the compensation signal corresponding to the next iteration; Represents signal area The Middle The sampling point at the th sampling point The first correction factor corresponding to the next iteration, where... Represents signal area The Middle The sampling point at the th sampling point In practical applications, the first error value corresponding to the iteration can be considered as the same first error value for each sampling point in the first signal region during the same round of iteration. Therefore, its value can be calculated by the formula for calculating the first error value in the first signal region in the embodiment of the present invention. Represents signal area The Middle The sampling point at the th sampling point The second correction factor corresponding to the next iteration, and its value can be equivalent to the second error value.

[0055] Correspondingly, in the During the next iteration, if the current first signal region (e.g., labeled as...) If a signal is classified as a first region type, and its peak value is less than the peak value of another first signal region in its corresponding first signal region pair, then the compensation signal of the current first signal region at a certain sampling point (e.g., labeled as...) The amplitude of ) can be calculated using the following expression: ; in, Represents signal area The Middle The sampling point at the th sampling point The amplitude of the compensation signal corresponding to the nth iteration can be used as the value of the nth iteration. The amplitude of the target signal during the next iteration; Represents signal area The Middle The sampling point at the th sampling point The amplitude of the target signal corresponding to the nth iteration, i.e., the nth iteration The amplitude of the compensation signal corresponding to the next iteration; Represents signal area The Middle The sampling point at the th sampling point The first correction factor corresponding to the next iteration, where... Represents signal area The Middle The sampling point at the th sampling point In practical applications, the first error value corresponding to the iteration can be considered as the same first error value for each sampling point in the first signal region during the same round of iteration. Therefore, its value can be calculated by the formula for calculating the first error value in the first signal region in the embodiment of the present invention. Represents signal area The Middle The sampling point at the th sampling point The second correction factor corresponding to the next iteration, and its value can be equivalent to the second error value.

[0056] A2. For each first signal region, in response to the second region type corresponding to the current first signal region, for each sampling point in the current first signal region, a third correction factor is determined based on the quotient of the amplitude of the current sampling point and the amplitude of the corresponding sampling point in the ideal signal. The amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is divided by the third correction factor to obtain the corresponding compensation signal.

[0057] In this embodiment, the third correction factor can be used to compensate the amplitude of the signal of the second region type.

[0058] For example, if the current first signal region is of the second region type, it indicates that the signal fluctuation in the current first signal region is relatively smooth. For each sampling point, the amplitude of the current sampling point can be divided by the amplitude of the ideal signal at the corresponding sampling point to obtain a third correction factor. The amplitude of the sub-signal corresponding to the target signal in that region is then divided by the third correction factor, and the result is used as the amplitude of the compensation signal corresponding to the sub-signal, thereby offsetting the amplitude distortion of the sub-signal. The above steps, combined with the signal characteristics of the second region type, achieve accurate amplitude compensation for signals of the second region type. Furthermore, the above steps fully utilize the smooth signal fluctuation characteristic of the second region type, eliminating the need for frequency compensation and improving processing efficiency in practical applications.

[0059] For example, in the first During the next iteration, if the current first signal region (e.g., labeled as...) This is the second region type, whose compensation signal is at a certain sampling point (e.g., labeled as...). The amplitude of ) can be calculated using the following expression: ; ; in, Represents signal area The Middle The sampling point at the th sampling point The amplitude of the compensation signal corresponding to the nth iteration can be used as the value of the nth iteration. The amplitude of the target signal during the next iteration; Represents signal area The Middle The sampling point at the th sampling point The amplitude of the target signal corresponding to the nth iteration, i.e., the nth iteration The amplitude of the compensation signal corresponding to the next iteration; Represents signal area The Middle The sampling point at the th sampling point The third correction factor corresponding to the next iteration; Represents signal area The Middle The sampling point at the th sampling point The amplitude of the sampled signal corresponding to the next iteration; Represents signal area The Middle The sampling point at the th sampling point The amplitude of the ideal signal corresponding to the next iteration.

[0060] S307. Determine the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the multiple first signal regions respectively.

[0061] In this embodiment, the compensation strategy corresponding to each first signal region can be determined based on the above steps, and targeted compensation processing can be performed to obtain the corresponding compensation signal. The compensation signal corresponding to each first signal region is then aligned in the time domain and frequency domain to obtain the predistortion signal.

[0062] This invention, through combining signal characteristics within a first region type and signal characteristics within a second region type, determines correction factors corresponding to the first and second region types, respectively. Based on corresponding compensation strategies, it compensates for signals within the first and second region types, achieving precise compensation for signals of different region types. When determining the first correction factor for the first region type, multiple signal regions are divided into corresponding signal region pairs based on symmetry. A first error value is determined based on the difference in peak values ​​between the two signal regions in a pair and the ideal peak value of the ideal signal in that region. This process precisely quantifies the impact of amplitude distortion on signal symmetry, allowing for more accurate subsequent signal compensation and ensuring signal symmetry. Furthermore, setting the first correction factor to a value greater than 1 ensures that subsequent compensation processing only requires multiplying the signal with the first correction factor. Division operations can efficiently stretch or compress signal amplitude, reducing computational complexity. When determining the second correction factor for the first region type, the signal to be processed is converted to frequency for processing, resulting in a first time-frequency distribution curve. Based on the difference between the ridge of the first time-frequency distribution curve and the sweep curve corresponding to the ideal signal, a second error value is determined, efficiently quantifying the frequency distortion of the signal to be processed. The second correction factor is then determined based on the second error value, enabling precise frequency compensation of the signal to be processed subsequently. By determining the third correction factor for the second region type based on the quotient of the amplitude at each sampling point and the amplitude of the ideal signal at the corresponding sampling point, the amplitude distortion of the signal can be offset simply by division when determining the compensation signal for the second region type. The above process fully incorporates the characteristics of the signal when determining the correction factor for each region type, resulting in more accurate compensation results with lower computational complexity.

[0063] Example 3 Figure 4 This is a flowchart of another signal processing method provided by an embodiment of the present invention. This embodiment further refines the iterative process based on the above embodiment. Figure 4 As shown, the method includes: S401. The target signal is processed by partitioning the output signal after passing through the nonlinear device to obtain multiple first signal regions, wherein the target signal is related to the ideal signal.

[0064] An ideal signal is a signal that possesses symmetrical characteristics.

[0065] S402. A preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape.

[0066] S403. For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals in the corresponding region of the target signal of the current first signal region to obtain the compensation signal corresponding to the current first signal region.

[0067] S404. Based on the compensation signals corresponding to the multiple first signal regions, determine the new target signal corresponding to the ideal signal.

[0068] In this embodiment, the compensation signal corresponding to each first signal region obtained based on the above steps is aligned in the time domain and frequency domain, and the aligned signal is re-input into the nonlinear device as a new target signal.

[0069] S405. Obtain the target signal output after the new target signal passes through the nonlinear device.

[0070] In this embodiment, the signal to be detected is the signal output after the new target signal passes through the nonlinear device. During each iteration, it can be determined whether the signal to be detected meets the preset iteration cutoff requirement. If it does, step S406 can be executed; otherwise, step S407 can be executed. The preset iteration cutoff requirement can be formulated according to the accuracy requirements of the signal in the actual application scenario. For example, it can be based on the symmetry deviation (which is the first error value in the first iteration round) and / or the frequency deviation (which is the second error value in the first iteration round) to set an error threshold, or a fixed number of iteration rounds can be set.

[0071] Optionally, the following method can be used to determine whether the signal to be detected meets the preset iteration cutoff requirement: The signal to be detected is partitioned to obtain multiple second signal regions, each of which includes at most one peak; the multiple second signal regions are divided into multiple symmetrical pairs based on symmetry; for each pair of second signal regions, the second peak difference between the two second signal regions in the current pair is calculated, and a third error value is determined based on the quotient of the square of the second peak difference and the square of the ideal peak value of the region corresponding to the ideal signal; a short-time Fourier transform is performed on the signal to be detected to obtain the corresponding second time-frequency distribution curve, the ridge of the second time-frequency distribution curve is extracted, and a fourth error value is determined based on the difference between the ridge of the second time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal; the error influence degree is determined based on the third error value and the fourth error value; in response to the error influence degree being less than a second threshold, the signal to be detected is determined to meet the preset iteration cutoff requirement.

[0072] In this embodiment, both the third error value and the first error value represent the symmetry deviation caused by signal amplitude distortion in the first region type. Due to the difference in iteration rounds, the values ​​of the third error value and the first error value are different. Similarly, both the fourth error value and the second error value represent the frequency deviation caused by signal frequency distortion in the first region type. Due to the difference in iteration rounds, the values ​​of the fourth error value and the second error value are different. The error impact degree can be used to evaluate whether the symmetry deviation and frequency deviation between the detected signal and the ideal signal meet the requirements, thereby determining whether the iteration can be terminated. For example, by pre-setting a second threshold, the relationship between the error impact degree in the current iteration process and the second threshold can be used to determine whether to continue iterating.

[0073] When calculating the numerical value of the error impact, it can be obtained by weighted summation according to the corresponding weights of the symmetry deviation (e.g., the first error value or the third error value) and frequency deviation (e.g., the second error value or the fourth error value) in each iteration process; or it can be obtained by squaring the symmetry deviation and frequency deviation respectively according to the following expression, summing them, and then taking the square root of the summation result; the method of determining the error impact can be set according to the actual application scenario.

[0074] ; in, Represents the degree of influence of error; This represents the symmetry deviation, and its value is determined based on the current iteration round. For example, it can be the first error value or the third error value. This represents the frequency deviation, the value of which is determined based on the current iteration round. For example, it can be the second error value or the fourth error value.

[0075] The above steps determine whether to continue iterating based on the degree of error impact. The degree of error impact is introduced with symmetry deviation related to amplitude distortion and frequency deviation related to frequency distortion. This allows the preset iteration cutoff requirement to take into account both amplitude distortion and frequency distortion, ensuring that the obtained predistorted signal has higher stability.

[0076] S406. In response to the detection signal meeting the preset iteration cutoff requirement, the new target signal is determined as the predistortion signal corresponding to the ideal signal.

[0077] In this embodiment, if the signal to be detected meets the preset iteration cutoff requirement, it means that the new target signal can cancel the distortion caused by the nonlinear device. Therefore, the new target signal can be used as the pre-distortion signal corresponding to the ideal signal.

[0078] S407. In response to the detection signal not meeting the preset iteration cutoff requirement, compensation processing is performed on the detection signal until the latest detection signal meets the preset iteration cutoff requirement. The latest target signal corresponding to the latest detection signal is determined as the predistortion signal corresponding to the ideal signal.

[0079] In this embodiment, if the signal to be detected does not meet the preset iteration cutoff requirement, it indicates that the signal to be detected output after the new target signal passes through the nonlinear device still has significant distortion. Therefore, the following steps can be repeatedly executed to compensate the signal to be detected: The signal to be detected is partitioned to obtain multiple third signal regions, each of which includes at most one peak; for each third signal region, a compensation strategy matching the region type corresponding to the current third signal region is adopted, and the ideal signal is used to compensate the sub-signals of the current third signal region within the corresponding region of the target signal, obtaining the compensation signal corresponding to the current third signal region; based on the compensation signals corresponding to the multiple third signal regions, a new target signal corresponding to the ideal signal is determined; the new signal to be detected output after the new target signal passes through the nonlinear device is obtained. This process continues until the latest signal to be detected meets the preset iteration cutoff requirement, at which point the latest target signal corresponding to the latest signal to be detected is determined as the pre-distortion signal corresponding to the ideal signal.

[0080] The embodiments of the present invention disclose in detail the iterative process, and calculate the error influence degree based on the third and fourth errors in each round of iteration, thereby determining whether to end the iteration, ensuring that the final predistorted signal can accurately cancel the distortion of the nonlinear device, and ensuring that the signal output after passing through the nonlinear device is closer to the ideal signal.

[0081] In some embodiments of temperature measurement systems utilizing optical signals, the target signal is a pulsed optical signal. When a low-duty-cycle pulsed optical signal passes through a nonlinear device already in a deeply saturated operating state, a transient effect occurs, resulting in significant waveform distortion after the pulsed optical signal passes through the nonlinear device, thereby degrading the accuracy of the temperature curve measured by the temperature measurement system. In this temperature measurement system, the nonlinear device can be an erbium-doped fiber amplifier in a fiber optic Raman temperature sensing system; the ideal signal includes multiple optical signals with different phases; each phase corresponds to a third error value and a fourth error value; the determination of the error influence based on the third and fourth error values ​​includes the following B1 to B6: B1. The signals obtained after using multiple third error values ​​to compensate the corresponding second signal regions are convolved with the simulated fiber response to obtain the first simulated Stokes Raman scattering light and the first simulated anti-Stokes Raman scattering light.

[0082] In this embodiment, using multiple third error values ​​to compensate for the corresponding second signal region may include: for each second signal region, determining the comparison result between the peak value of the current second signal region and the peak value of another second signal region in the pair to which the current second signal region belongs; if the comparison result is greater than (i.e., the peak value of the current second signal region is greater than the peak value of another second signal region in the pair to which the current second signal region belongs), then dividing the amplitude of the sub-signal in the corresponding region of the current second signal region in the target signal by the first correction factor to obtain the corresponding compensation signal; if the comparison result is less than (i.e., the peak value of the current second signal region is less than the peak value of another second signal region in the pair to which the current second signal region belongs), then multiplying the amplitude of the sub-signal in the corresponding region of the current second signal region in the target signal by the first correction factor to obtain the corresponding compensation signal. Then, convolving the compensation signal with the simulated fiber response yields the first simulated Stokes Raman scattered light and the first simulated anti-Stokes Raman scattered light.

[0083] For example, taking a fiber optic Raman temperature sensing system as an example, the process of obtaining the first simulated Stokes Raman scattered light and the first simulated anti-Stokes Raman scattered light is illustrated through simulation. Four-phase optical signals can be used as ideal signals, where the phase deviation between the four phases can be 90°. In the first iteration, the collected four-phase optical signals are input into the EDFA as target signals. For each phase of the optical signal, the third error value generated after the current phase's optical signal passes through the EDFA is added by 1 to obtain the first correction factor for this iteration.

[0084] For each pair of second signal regions, the amplitudes of the signals within the two regions are compared. For the region with the larger amplitude, the compensation signal is calculated using the following expression: ; ; ; ; in, , , ,as well as Each phase represents the phase at the 1st... The compensation signal for each signal region with a relatively large amplitude; , , ,as well as Each phase represents the phase at the 1st... The third error corresponding to the signal region with a relatively large amplitude in the signal region; , , ,as well as Each phase represents the phase at the 1st... The ideal signal corresponds to a signal region with a relatively large amplitude.

[0085] For signal regions with small amplitudes, the compensation signal is calculated using the following expression: ; ; ; ; in, , , ,as well as Each phase represents the phase at the 1st... The compensation signal for each signal region with a smaller amplitude; , , ,as well as Each phase represents the phase at the 1st... The third error corresponding to the signal region with a smaller amplitude in the signal region; , , ,as well as Each phase represents the phase at the 1st... The ideal signal corresponds to a signal region with a relatively small amplitude.

[0086] The compensation signal corresponding to each phase of the optical signal in each second signal region is obtained by following the above process. The compensation signals of each second signal region are aligned in the time domain and frequency domain to obtain the compensation signal corresponding to each phase of the optical signal. The compensation signal is then convolved with the simulated fiber response to obtain the first simulated Stokes Raman scattering light and the first simulated anti-Stokes Raman scattering light corresponding to each phase.

[0087] For example, since the Raman scattering process in the sensing fiber can be regarded as a linear time-invariant system, the Raman scattered light can be regarded as the result of convolving the swept-frequency optical signal (the compensation signal corresponding to the optical signal of each phase can be used as the swept-frequency optical signal corresponding to each phase) with the fiber response. The first simulated Stokes Raman scattered light and the first simulated anti-Stokes Raman scattered light corresponding to each phase can be calculated by the following expression: ; ; ; ; ; ; ; ; in, , , , These represent the first simulated Stokes Raman scattered light corresponding to each phase; , , , These represent the swept-frequency optical signals corresponding to each phase; The fiber response function represents the first simulated Stokes Raman scattered light. The fiber response function can be a time-domain impulse response function. Its parameters can be determined by experiments or simulations in practical applications. This invention does not limit this. , , , These represent the first simulated anti-Stokes Raman scattered light corresponding to each phase; The fiber response function represents the first simulated anti-Stokes Raman scattered light, and its parameters can be determined experimentally or through simulation. This represents the convolution operation.

[0088] B2. The signals obtained after using multiple fourth error values ​​to compensate the corresponding second signal regions are convolved with the simulated fiber response to obtain the second simulated Stokes Raman scattering light and the second simulated anti-Stokes Raman scattering light.

[0089] In this embodiment, using multiple fourth error values ​​to compensate for the corresponding second signal region may include: for each second signal region, dividing the amplitude of the sub-signal in the corresponding region of the target signal within the current second signal region by the second correction factor to obtain the corresponding compensation signal. Then, convolving the compensation signal with the simulated fiber response yields the second simulated Stokes Raman scattered light and the second simulated anti-Stokes Raman scattered light.

[0090] For example, for each phase of the optical signal, the fourth error value of the current phase optical signal in each second signal region can be used as the second correction factor in the corresponding second signal region. The signal amplitude of the current phase optical signal in each second signal region is divided by the second correction factor to obtain the compensation signal in the corresponding signal region. By aligning the compensation signals of each second signal region in the time domain and frequency domain, the compensation signal corresponding to the current phase optical signal is obtained. The compensation signal is then convolved with the simulated fiber response to obtain the second simulated Stokes Raman scattering light and the second simulated anti-Stokes Raman scattering light corresponding to each phase.

[0091] B3. Determine the first simulated temperature curve based on the first simulated Stokes Raman scattering light and the first simulated anti-Stokes Raman scattering light.

[0092] In this embodiment, Euler's formula can be used to perform a difference operation on the four phase-corresponding first simulated Stokes Raman scattered light to obtain the first simulated Stokes Raman scattering differential signal; correspondingly, Euler's formula can be used to perform a difference operation on the four phase-corresponding first simulated anti-Stokes Raman scattered light to obtain the first simulated anti-Stokes Raman scattering differential signal; an ideal matched filter is used to convolve the first simulated Stokes Raman scattering differential signal and the first simulated anti-Stokes Raman scattering differential signal respectively to obtain the first simulated Stokes Raman scattering filtered signal and the first simulated anti-Stokes Raman scattering filtered signal respectively; wherein, the ideal matched filter... The modulation slope and frequency parameters can be determined based on the ideal signal. Optionally, in order to improve the smoothness of the signal after processing by the ideal matched filter in practical applications, the ideal matched filter can be windowed. For example, the ideal matched filter can be convolved with a window function, which can be a Hamming window. This invention does not restrict the window function. The ratio of the first simulated anti-Stokes Raman scattering filtered signal to the first simulated Stokes Raman scattering filtered signal is combined with the first weighting coefficient and the second weighting coefficient to construct a first-order linear relationship to obtain the first simulated temperature curve. The first weighting coefficient and the second weighting coefficient can be pre-calibrated in the actual application scenario.

[0093] For example, the first simulated Stokes Raman scattering differential signal and the first simulated anti-Stokes Raman scattering differential signal can be calculated using the following expressions: ; ; in, The representative used Euler's formula to perform a differential operation on the first simulated Stokes Raman scattered light corresponding to the four phases, and obtained the first simulated Stokes Raman scattered differential signal. The representative used Euler's formula to perform differential operations on the first simulated anti-Stokes Raman scattered light corresponding to the four phases, and obtained the first simulated anti-Stokes Raman scattered differential signal.

[0094] For example, an ideal matched filter can be represented by the following expression: ; Where represents the ideal matched filter; represents the frequency, whose value can be consistent with the ideal signal, for example, . , , ,as well as The frequencies are consistent; under normal circumstances, the ideal signal frequencies of the above four phases are the same. This represents the frequency modulation slope, and its value can be determined based on the ratio of the sweep bandwidth of the sweep signal to the duration of the sweep signal. Represents a time variable.

[0095] Optionally, the first simulated Stokes Raman scattering differential signal and the first simulated anti-Stokes Raman scattering differential signal are convolved using a windowed ideal matched filter to obtain the first simulated Stokes Raman scattering filtered signal and the first simulated anti-Stokes Raman scattering filtered signal, respectively.

[0096] For example, the first simulated Stokes Raman scattering filter signal and the first simulated anti-Stokes Raman scattering filter signal are calculated using the following expressions: ; ; in, This represents the first simulated Stokes Raman scattering filter signal; The ideal matched filter after windowing can be obtained by convolving the ideal matched filter with the Hamming window function; This represents the first simulated Stokes Raman scattering differential signal; This represents the first simulated anti-Stokes Raman scattering filtered signal; This represents the first simulated anti-Stokes Raman scattering differential signal; This represents the convolution operation.

[0097] For example, the temperature values ​​in the first simulated temperature curve are calculated using the following first-order linear expression: ; in, This represents the temperature value at a certain time in the first simulated temperature curve. and These represent the first weighting coefficient and the second weighting coefficient, respectively.

[0098] B4. Determine the second simulated temperature curve based on the second simulated Stokes Raman scattering light and the second simulated anti-Stokes Raman scattering light.

[0099] Correspondingly, Euler's formula can be used to perform a difference operation on the four phase-corresponding second simulated Stokes Raman scattered light to obtain the second simulated Stokes Raman scattering differential signal; Euler's formula can also be used to perform a difference operation on the four phase-corresponding second simulated anti-Stokes Raman scattered light to obtain the second simulated anti-Stokes Raman scattering differential signal; an ideal matched filter can then be used to convolve the second simulated Stokes Raman scattering differential signal and the second simulated anti-Stokes Raman scattering differential signal respectively to obtain the second simulated Stokes Raman scattering filtered signal and the second simulated anti-Stokes Raman scattering filtered signal; wherein, the frequency modulation slope of the ideal matched filter... Parameters such as rate and frequency can be determined based on the ideal signal. Correspondingly, in practical applications, in order to improve the smoothness of the signal after processing by the ideal matched filter, the ideal matched filter can be windowed. For example, the ideal matched filter can be convolved with a window function, which can be a Hamming window. This invention does not impose any restrictions on the window function. The ratio of the second simulated anti-Stokes Raman scattering filtered signal to the second simulated Stokes Raman scattering filtered signal is combined with the third and fourth weighting coefficients to construct a first-order linear relationship to obtain the second simulated temperature curve. The third and fourth weighting coefficients can be pre-calibrated in the actual application scenario.

[0100] B5. Determine the first simulation temperature accuracy based on the first simulation temperature curve; determine the second simulation temperature accuracy based on the second simulation temperature curve.

[0101] In this embodiment, during the measurement of an object's temperature, the temperature curve of a high-temperature object will gradually rise from a low-temperature value to a high-temperature value. Therefore, the first and second simulated temperature curves generally include a high-temperature region, a transition region, and a low-temperature region. For the first simulated temperature curve, the high-temperature accuracy and low-temperature accuracy can be determined based on the temperature accuracy and precision of the high-temperature region, and the temperature accuracy and precision of the low-temperature region, respectively. Specifically, the temperature accuracy of the high-temperature region can be determined based on the average temperature value and the lowest temperature difference value of the high-temperature region; the temperature precision of the high-temperature region can be determined based on the temperature standard deviation of the high-temperature region. The high-temperature accuracy can be obtained by weighting and summing the temperature accuracy and precision of the high-temperature region according to a preset weight. Correspondingly, the low-temperature accuracy can also be determined. The first simulated temperature accuracy is determined based on the high-temperature accuracy and the low-temperature accuracy; for example, the maximum value of the high-temperature accuracy and the low-temperature accuracy is taken as the first simulated temperature accuracy.

[0102] For example, the temperature accuracy and temperature precision in the high-temperature region are weighted and summed according to preset weights using the following expression to obtain the high-temperature precision: ; in, This represents high-temperature accuracy; a high-temperature accuracy range can be set based on this range, for example... Therefore, the high-temperature accuracy range can be [-0.3, 0.3]. Temperature accuracy in the high-temperature zone; Temperature accuracy representing the high-temperature zone; This represents a preset weight, the value of which can be calibrated in experiments or simulations.

[0103] For example, the temperature accuracy and temperature precision in the low-temperature region are weighted and summed according to preset weights using the following expression to obtain the low-temperature precision: ; in, This represents low-temperature accuracy, and a low-temperature accuracy range can be set based on this range. For example... Therefore, the low-temperature accuracy range can be [-0.3, 0.3]. Temperature accuracy in the low-temperature region; Represents the temperature accuracy in the low-temperature region; This represents a preset weight, the value of which can be calibrated in experiments or simulations.

[0104] For example, the maximum value between high-temperature accuracy and low-temperature accuracy is used as the first simulation temperature accuracy: ; in, This represents the accuracy of the first simulation temperature.

[0105] Correspondingly, by processing the second simulated temperature curve using the steps described above, the second simulated temperature accuracy can also be obtained. This invention does not limit the methods used to determine the first and second simulated temperature accuracies.

[0106] B6. Determine the degree of error influence based on the accuracy of the first simulation temperature and the accuracy of the second simulation temperature.

[0107] In this embodiment, the squares of the first simulation temperature accuracy and the second simulation temperature accuracy can be summed, and then the summation result can be square rooted to obtain the error influence degree.

[0108] For example, the impact of error can be represented by the following expression: ; in, Represents the degree of influence of error; Represents the accuracy of the first simulation temperature; This represents the accuracy of the second simulation temperature.

[0109] For example, the optical fiber is 2700 meters long, and at approximately 100 to 135 meters, it is heated to 90 degrees Celsius using a temperature-controlled device. Figure 5 As shown, the first curve 501 is the temperature curve demodulated from the distorted pulse signal, and the second curve 502 is the temperature curve demodulated from the pre-distortion signal according to the present invention. It can be clearly seen that the first curve 501 exhibits severe distortion, with a temperature error reaching tens of degrees Celsius. The second curve 502, after pre-distortion processing, can accurately measure a room temperature of approximately 23 degrees Celsius and a high temperature of approximately 90 degrees Celsius. The system temperature accuracy is approximately... Celsius.

[0110] The above steps enable a precise correlation between the output parameters (e.g., temperature accuracy) and waveform error of the fiber optic Raman temperature sensing system. This allows the error impact to more accurately reflect the quality of system-level performance parameters, ensuring a higher degree of alignment between the evaluation results and the actual performance of the system, and providing stronger engineering guidance. Compared to directly determining the error impact based on waveform error, this invention uses system-level performance parameters as optimization indicators, freeing the iteration cutoff process from the subjective limitation of relying on waveform error to set a second threshold, thereby ensuring that the system's performance parameters can reach a better level.

[0111] Example 4 Figure 6 This is a schematic diagram of a signal processing device provided in Embodiment 4 of the present invention. Figure 6 As shown, the device includes: a first partitioning module 601, a type determination module 602, a compensation module 603, and a predistortion signal determination module 604.

[0112] The first partitioning module is used to partition the target signal output after passing through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; The type determination module is used to determine the region type corresponding to the plurality of first signal regions respectively using a preset type determination strategy, wherein the preset type determination strategy is determined based on the steepness of the waveform shape; The compensation module is used to adopt a compensation strategy that matches the region type corresponding to the current first signal region for each first signal region, and use the ideal signal to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region. The predistortion signal determination module is used to determine the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the plurality of first signal regions respectively.

[0113] This invention provides a signal processing apparatus that partitions a target signal (output from a nonlinear device) to obtain multiple first signal regions, wherein the target signal is correlated with an ideal signal. A preset type determination strategy is used to determine the region type corresponding to each of the multiple first signal regions, where the preset type determination strategy is based on the steepness of the waveform shape. For each first signal region, a compensation strategy matching the region type of the current first signal region is used to compensate the sub-signals within the corresponding region of the target signal using the ideal signal, resulting in a compensation signal corresponding to the current first signal region. Based on the compensation signals corresponding to the multiple first signal regions, a pre-distortion signal corresponding to the ideal signal is determined. The above technical solution obtains multiple signal regions by partitioning the signal to be processed, and determines the region type corresponding to each signal region according to a preset type determination strategy. It then uses a compensation strategy that matches the region type to compensate the sub-signals of the signal region, thus realizing a differentiated compensation strategy. Compared with a single compensation strategy, this ensures that the obtained pre-distorted signal is more compatible with the morphological characteristics of the signal to be processed, thereby efficiently solving the waveform distortion problem caused by the target signal passing through nonlinear devices. In addition, the partitioning strategy based on the steepness of the waveform shape enables the present invention to efficiently identify the region type, providing a foundation for subsequently formulating corresponding compensation strategies for different region types.

[0114] Optionally, each first signal region includes at most one peak; the region type includes a first region type and a second region type, wherein the steepness corresponding to the first region type is higher than the steepness corresponding to the second region type; the type determination module is specifically used for: For each first signal region, the rise time corresponding to the current first signal region is determined, and the shape factor of the waveform in the current first signal region is determined based on the rise time. If the shape factor is less than a first threshold, the current first signal region is determined to correspond to the first region type. If the shape factor is greater than or equal to the first threshold, the current first signal region is determined to correspond to the second region type.

[0115] Optionally, the ideal signal is a signal with symmetrical characteristics; the device further includes: The first signal region pair division module is used to divide the plurality of first signal regions into a plurality of first signal region pairs based on symmetry. The first error value determination module is used to calculate the first peak difference between two symmetrical first signal regions in the current first signal region pair for each first signal region pair, and determine the first error value based on the quotient of the square of the first peak difference and the square of the ideal peak value of the region corresponding to the ideal signal, wherein the first error value is used to determine the first correction factor, and the first correction factor is greater than 1. The second error value determination module is used to perform a short-time Fourier transform on the signal to be processed to obtain a corresponding first time-frequency distribution curve, extract the ridge line of the first time-frequency distribution curve, and determine a second error value based on the difference between the ridge line of the first time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal. The second error value is used to determine a second correction factor. The compensation module includes: The first compensation unit is configured to, for each first signal region, in response to the first region type corresponding to the current first signal region, determine the comparison result between the peak value of the current first signal region and the peak value of another first signal region in the first signal region pair to which the current first signal region belongs; if the comparison result is greater than, then the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is divided by the first correction factor and divided by the second correction factor to obtain the corresponding compensation signal; if the comparison result is less than, then the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is multiplied by the first correction factor and divided by the second correction factor to obtain the corresponding compensation signal. The second compensation unit is used to determine a third correction factor for each first signal region in response to the second region type corresponding to the current first signal region, for each sampling point in the current first signal region, based on the quotient of the amplitude of the current sampling point and the amplitude of the corresponding sampling point in the ideal signal, and to divide the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal by the third correction factor to obtain the corresponding compensation signal.

[0116] Optionally, the predistortion signal determination module includes: The new target signal determination unit is used to determine a new target signal corresponding to the ideal signal based on the compensation signals corresponding to the plurality of first signal regions respectively. The detection signal determination unit is used to acquire the detection signal output after the new target signal passes through the nonlinear device; The first predistortion signal determination unit is used to determine the new target signal as the predistortion signal corresponding to the ideal signal in response to the detection signal meeting the preset iteration cutoff requirement. The second predistortion signal determination unit is used to compensate the signal to be detected in response to the signal to be detected not meeting the preset iteration cutoff requirement, until the latest signal to be detected meets the preset iteration cutoff requirement, and determine the latest target signal corresponding to the latest signal to be detected as the predistortion signal corresponding to the ideal signal.

[0117] Optionally, the ideal signal is a signal with symmetrical characteristics; the detection signal is determined to meet the preset iteration cutoff requirement by the following methods: the detection signal is partitioned to obtain multiple second signal regions, wherein each second signal region includes at most one peak; the multiple second signal regions are divided into multiple symmetrical pairs of second signal regions based on symmetry; for each pair of second signal regions, the second peak difference between the two second signal regions in the current signal region pair is calculated, and a third error value is determined based on the quotient of the square of the second peak difference and the square of the ideal peak value of the corresponding region of the ideal signal; a short-time Fourier transform is performed on the detection signal to obtain the corresponding second time-frequency distribution curve, the ridge of the second time-frequency distribution curve is extracted, and a fourth error value is determined based on the difference between the ridge of the second time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal; the error influence degree is determined based on the third error value and the fourth error value; in response to the error influence degree being less than a second threshold, the detection signal is determined to meet the preset iteration cutoff requirement.

[0118] Optionally, the nonlinear device is an erbium-doped fiber amplifier in the fiber Raman temperature sensing system; the ideal signal includes multiple optical signals with different phases; each phase corresponds to a third error value and a fourth error value; determining the error impact based on the third error value and the fourth error value includes: convolving the signal obtained after signal compensation of the corresponding second signal region using multiple third error values ​​with the simulated fiber response to obtain a first simulated Stokes Raman scattered light and a first simulated anti-Stokes Raman scattered light; convolving the signal obtained after signal compensation of the corresponding second signal region using multiple fourth error values ​​with the simulated fiber response to obtain a second simulated Stokes Raman scattered light and a second simulated anti-Stokes Raman scattered light; determining a first simulated temperature curve based on the first simulated Stokes Raman scattered light and the first simulated anti-Stokes Raman scattered light; determining a second simulated temperature curve based on the second simulated Stokes Raman scattered light and the second simulated anti-Stokes Raman scattered light; determining a first simulated temperature accuracy based on the first simulated temperature curve; determining a second simulated temperature accuracy based on the second simulated temperature curve; and determining the error impact based on the first simulated temperature accuracy and the second simulated temperature accuracy.

[0119] The signal processing apparatus provided in the embodiments of the present invention can execute the signal processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0120] Example 5 Figure 7 A schematic diagram of an electronic device 700 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0121] like Figure 7 As shown, the electronic device 700 includes at least one processor 701 and a memory, such as a read-only memory (ROM) 702 and a random access memory (RAM) 703, communicatively connected to the at least one processor 701. The memory stores computer programs executable by the at least one processor. The processor 701 can perform various appropriate actions and processes based on the computer program stored in the ROM 702 or loaded into the RAM 703 from storage unit 708. The RAM 703 can also store various programs and data required for the operation of the electronic device 700. The processor 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0122] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, such as keyboard, mouse, etc.; output unit 707, such as various types of displays, speakers, etc.; storage unit 708, such as disk, optical disk, etc.; and communication unit 709, such as network card, modem, wireless transceiver, etc. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] Processor 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 701 performs the various methods and processes described above, such as signal processing methods.

[0124] In some embodiments, the signal processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by processor 701, one or more steps of the signal processing method described above may be performed. Alternatively, in other embodiments, processor 701 may be configured to perform the signal processing method by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0131] This disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the signal processing method provided in the above embodiments.

[0132] This disclosure provides a signal processing system, such as... Figure 8 As shown, it includes a signal generator, a laser, an optical fiber amplifier, a coupler, an optical attenuator, a wavelength division multiplexer, an optical switch, a first detector, a second detector, a signal acquisition module, and the electronic equipment described in the embodiments of the present invention; wherein, The signal generator is connected to the laser and is used to control the laser to output a set signal to the fiber amplifier, wherein the set signal is related to an ideal signal; The coupler is connected to the fiber optic amplifier and is used to divide the set signal into a first signal and a second signal, wherein the first signal is a target signal and the second signal is a measurement signal; The optical attenuator is connected to the coupler and is used to receive the target signal; The port of the wavelength division multiplexer is connected to the coupler to receive the measurement signal. The wavelength division multiplexer is also connected to the probe fiber and the first detector. The optical switch is used to connect to the optical attenuator during the pre-distortion signal debugging stage and to the wavelength division multiplexer during the measurement stage; the optical switch is also connected to the second detector; Both the first detector and the second detector are connected to the signal acquisition module; The signal acquisition module is connected to the electronic device and is used to input the acquired signal to be processed into the electronic device; The electronic device is connected to the signal generator and is used to send a signal generation command to the signal generator to generate the set signal.

[0133] For example, taking the process of intensity modulation of chirped pulses using the signal processing system as an example, the laser outputs pulsed light by controlling the signal generator. After the pulsed light passes through the fiber amplifier, distorted pulsed light is generated. The peak power of the distorted pulsed light is ensured to be within the acceptable range of the second detector (which can be a photodetector) by the coupling branch of the coupler (e.g., the 1% branch in a coupler with a coupling ratio of 1:99) and the optical attenuator. During the modulation stage, the optical attenuator and the second detector are interconnected by switching the optical switch, so that the second detector can directly collect the distorted pulsed light. After photoelectric conversion by the second detector, the electrical signal corresponding to the distorted pulsed light is obtained. The electrical signal is collected and amplified by the signal acquisition module and input to the electronic device. By comparing the waveform corresponding to the distorted pulsed light collected in this time with the ideal waveform in the electronic device, and using the signal processing method of the present invention, an intermediate pre-distorted signal is generated, which is the signal to be detected corresponding to this iteration. This signal is then input into the signal amplifier for the next iteration until the iteration cutoff condition is met, and the modulation work is completed. This system achieves closed-loop control of optical signals, effectively overcoming the distortion problem caused by signals passing through nonlinear devices, ensuring the accuracy of pulse signals, and possessing good engineering practicality.

[0134] It should be noted that there are currently various structures for optical signal-based sensing systems, such as Distributed Fiber Acoustic Sensing (DAS), Fiber Bragg Grating (FBG) Sensing Systems, and variant systems based on either DAS or FBG. All of these systems and their variants can acquire pre-distortion signals using the signal processing method provided in this invention to modulate the signal waveform. For example, in an FBG system, taking a heterodyne-based optical path as an example, pulsed light is acquired and pre-distorted by leading a light path after the laser. While an erbium-doped fiber amplifier may not be used in an FBG system, the distortion introduced by the proposed scheme can still be corrected using circuitry and other modules. The use of pre-distortion signals to modulate the signal waveform in these systems should all be included within the scope of this invention.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A signal processing method, characterized in that, include: The target signal is processed by partitioning the output signal after passing through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; A preset type determination strategy is used to determine the region type corresponding to the plurality of first signal regions, wherein the preset type determination strategy is based on the steepness of the waveform shape; For each first signal region, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region. Based on the compensation signals corresponding to the plurality of first signal regions, the predistortion signal corresponding to the ideal signal is determined.

2. The signal processing method according to claim 1, characterized in that, Each first signal region includes at most one peak; the region type includes a first region type and a second region type, wherein the steepness of the first region type is higher than that of the second region type; The method of determining the region type corresponding to the plurality of first signal regions using a preset type determination strategy includes: For each first signal region, the rise time corresponding to the current first signal region is determined, and the region type corresponding to the plurality of first signal regions is determined according to the rise time.

3. The signal processing method according to claim 1, characterized in that, The ideal signal is a signal with symmetrical characteristics; each first signal region includes at most one peak; the region type includes a first region type and a second region type, wherein the steepness corresponding to the first region type is higher than the steepness corresponding to the second region type; the method further includes: Based on symmetry, the plurality of first signal regions are divided into a plurality of first signal region pairs; For each pair of first signal regions, calculate the first peak difference between the two symmetrical first signal regions in the current pair of first signal regions, and determine the first error value based on the quotient of the square of the first peak difference and the square of the ideal peak value of the region corresponding to the ideal signal. The first error value is used to determine the first correction factor, which is greater than 1. A short-time Fourier transform is performed on the signal to be processed to obtain the corresponding first time-frequency distribution curve. The ridge line of the first time-frequency distribution curve is extracted. A second error value is determined based on the difference between the ridge line of the first time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal. The second error value is used to determine the second correction factor. Specifically, a compensation strategy matching the region type corresponding to the current first signal region is adopted. The ideal signal is used to compensate the sub-signals within the corresponding region of the target signal in the current first signal region, resulting in a compensated signal corresponding to the current first signal region. This includes: In response to the first region type corresponding to the current first signal region, a comparison result is determined between the peak value of the current first signal region and the peak value of another first signal region in the first signal region pair to which the current first signal region belongs; if the comparison result is greater than, the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is divided by the first correction factor and divided by the second correction factor to obtain the corresponding compensation signal; if the comparison result is less than, the amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is multiplied by the first correction factor and divided by the second correction factor to obtain the corresponding compensation signal. In response to the second region type corresponding to the current first signal region, for each sampling point in the current first signal region, a third correction factor is determined based on the quotient of the amplitude of the current sampling point and the amplitude of the corresponding sampling point in the ideal signal. The amplitude of the sub-signal in the corresponding region of the current first signal region in the target signal is divided by the third correction factor to obtain the corresponding compensation signal.

4. The signal processing method according to claim 1, characterized in that, The step of determining the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the plurality of first signal regions includes: Based on the compensation signals corresponding to the plurality of first signal regions, a new target signal corresponding to the ideal signal is determined; The new target signal is obtained as the output signal to be detected after passing through the nonlinear device; In response to the detection signal meeting the preset iteration cutoff requirement, the new target signal is determined as the predistortion signal corresponding to the ideal signal; In response to the detection signal not meeting the preset iteration cutoff requirement, the detection signal is compensated until the latest detection signal meets the preset iteration cutoff requirement, and the latest target signal corresponding to the latest detection signal is determined as the predistortion signal corresponding to the ideal signal.

5. The signal processing method according to claim 4, characterized in that, The ideal signal is a signal with symmetrical characteristics; Whether the signal to be detected meets the preset iteration cutoff requirement is determined by the following method: The signal to be detected is partitioned to obtain multiple second signal regions, wherein each second signal region includes at most one peak; Based on symmetry, the plurality of second signal regions are divided into a plurality of symmetrical pairs of second signal regions; For each pair of second signal regions, calculate the second peak difference between the two second signal regions in the current signal region pair, and determine the third error value based on the quotient of the square of the second peak difference and the square of the ideal peak value of the region corresponding to the ideal signal. A short-time Fourier transform is performed on the signal to be detected to obtain the corresponding second time-frequency distribution curve. The ridge of the second time-frequency distribution curve is extracted. Based on the difference between the ridge of the second time-frequency distribution curve and the sweep frequency curve corresponding to the ideal signal, a fourth error value is determined. The degree of error impact is determined based on the third error value and the fourth error value; In response to the error impact being less than a second threshold, it is determined that the signal to be detected meets the preset iteration cutoff requirement; Preferably, the nonlinear device is an erbium-doped fiber amplifier in an optical fiber Raman temperature sensing system; the ideal signal includes multiple optical signals with different phases; each phase corresponds to a third error value and a fourth error value. Determining the error impact based on the third error value and the fourth error value includes: The signals obtained by compensating the corresponding second signal regions with multiple third error values ​​are convolved with the simulated fiber response to obtain the first simulated Stokes Raman scattered light and the first simulated anti-Stokes Raman scattered light. The signals obtained by using multiple fourth error values ​​to compensate the corresponding second signal regions are convolved with the simulated fiber response to obtain the second simulated Stokes Raman scattered light and the second simulated anti-Stokes Raman scattered light. A first simulated temperature curve is determined based on the first simulated Stokes Raman scattering light and the first simulated anti-Stokes Raman scattering light; a second simulated temperature curve is determined based on the second simulated Stokes Raman scattering light and the second simulated anti-Stokes Raman scattering light. The first simulation temperature accuracy is determined based on the first simulation temperature curve; the second simulation temperature accuracy is determined based on the second simulation temperature curve. The degree of error impact is determined based on the accuracy of the first simulation temperature and the accuracy of the second simulation temperature.

6. A signal processing apparatus, characterized in that, include: The first partitioning module is used to partition the target signal output after passing through a nonlinear device to obtain multiple first signal regions, wherein the target signal is related to an ideal signal; The type determination module is used to determine the region type corresponding to the plurality of first signal regions respectively using a preset type determination strategy, wherein the preset type determination strategy is determined based on the steepness of the waveform shape; The compensation module is used to adopt a compensation strategy that matches the region type corresponding to the current first signal region for each first signal region, and use the ideal signal to compensate the sub-signals of the current first signal region in the corresponding region of the target signal to obtain the compensation signal corresponding to the current first signal region. The predistortion signal determination module is used to determine the predistortion signal corresponding to the ideal signal based on the compensation signals corresponding to the plurality of first signal regions respectively.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the signal processing method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the signal processing method according to any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the signal processing method according to any one of claims 1-5.

10. A signal processing system, characterized in that, It includes a signal generator, a laser, an optical fiber amplifier, a coupler, an optical attenuator, a wavelength division multiplexer, an optical switch, a first detector, a second detector, a signal acquisition module, and the electronic device as described in claim 7; wherein, The signal generator is connected to the laser and is used to control the laser to output a set signal to the fiber amplifier, wherein the set signal is related to an ideal signal; The coupler is connected to the fiber optic amplifier and is used to divide the set signal into a first signal and a second signal, wherein the first signal is a target signal and the second signal is a measurement signal; The optical attenuator is connected to the coupler and is used to receive the target signal; The port of the wavelength division multiplexer is connected to the coupler to receive the measurement signal. The wavelength division multiplexer is also connected to the probe fiber and the first detector. The optical switch is used to connect to the optical attenuator during the pre-distortion signal debugging stage and to the wavelength division multiplexer during the measurement stage; the optical switch is also connected to the second detector; Both the first detector and the second detector are connected to the signal acquisition module; The signal acquisition module is connected to the electronic device and is used to input the acquired signal to be processed into the electronic device; The electronic device is connected to the signal generator and is used to send a signal generation command to the signal generator to generate the set signal.

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