Weak signal data fitting method, system and device and storage medium

Abstract

The invention provides a weak signal data fitting method, system and device and a storage medium, and aims to perform data fitting on the number of fluorescence signals obtained by microwave frequency sweeping and the frequency so as to determine the center frequency and the spectral line width. The method comprises the following steps: acquiring a fluorescence signal, performing microwave scanning of different frequencies on the fluorescence signal according to a preset microwave frequency scanning range and a preset step value to obtain the number of fluorescence signals under different frequencies, and drawing a scatter diagram of the frequencies and the number of fluorescence signals; performing nonlinear fitting on data on the scatter diagram by using a mathematical model to obtain a function model and fitting data; calculating the center frequency of the function model based on the function model; the fitting data are stored in a container of a standard library, and the maximum value and the minimum value of a function model are determined through functions of the standard library; calculating a half-height value based on the maximum value and the minimum value; two frequency points are calculated based on the function model and the half-height value, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

Description

Technical Field

[0001] The present application relates to the field of microwave frequency standards, and in particular to a data fitting method, system, device and storage medium for weak signals. Background Art

[0002] The mercury ion microwave frequency standard is a new type of frequency standard that uses a new working principle different from the traditional atomic frequency standards of hydrogen, rubidium, and cesium lamps. It has the characteristics of being basically unaffected by physical particles and external fields, having small motion effects, and having a long quantum state coherence time. Its spectral line width is narrow and the frequency shift is small. The main reason is that by applying an electrostatic field, a magnetic field, or a radio frequency field to the ion trap, the working ions are trapped in the center of the ultra-high vacuum ion trap, making the ions completely isolated and in a "completely static state" without being disturbed by the outside world, thereby greatly improving the performance of the ion microwave frequency standard. The mercury ion microwave frequency standard uses a spectral lamp to pump the ultrafine energy levels of the ions. The high-energy-level atoms transition to the low-energy level after spontaneous radiation, and generate fluorescence signals at the same time, which are collected by the detection system. When the microwave signal frequency is swept within a certain range, the optical detection system will obtain a transition signal. In order to obtain the line type and spectral line width of the scanning spectrum, the frequency-photon signal data needs to be fitted.

[0003] However, since the mercury ion microwave frequency standard is pumped by a mercury lamp, its noise is tens to hundreds of times that of the signal. Therefore, how to perform data fitting for this weak signal is a problem that needs to be solved at present. Summary of the invention

[0004] The embodiments of the present application provide a data fitting method, system, device and storage medium for weak signals, which perform data fitting on the number of fluorescence signals obtained by microwave scanning and the frequency, and then determine the center frequency and spectral line width, provide accurate center frequency and modulation depth data for subsequent experiments, and realize a high-performance new atomic frequency standard.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a data fitting method for a weak signal, the method comprising: acquiring a fluorescence signal, and performing microwave scanning of different frequencies on the fluorescence signal according to a preset microwave frequency scanning range and step value, to obtain the number of fluorescence signals at different frequencies, and then drawing a scatter plot of frequency and number of fluorescence signals;

[0007] Use mathematical models to perform nonlinear fitting on the data on the scatter plot to obtain a function model and fitting data;

[0008] Based on the function model, the center frequency of the function model is calculated;

[0009] The fitting data is stored in a standard library container, and the maximum and minimum values ​​of the function model are determined by using the functions of the standard library;

[0010] Based on the maximum and minimum values ​​of the function model, the half-height value is calculated;

[0011] Based on the function model and the half-height value, two frequency points are calculated, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

[0012] In a possible design scheme, the method of the first aspect further includes that the scatter plot of frequency and the number of fluorescent signals is a two-dimensional data graph, with the horizontal axis being the frequency and the vertical axis being the number of fluorescent signals.

[0013] A possible design scheme, the method of the first aspect further includes performing nonlinear fitting on the data on the scatter plot using a mathematical model to obtain a function model and fitting data, including:

[0014] The function model is:

[0015] Among them, W, S0, y0, and v0 are all fitted coefficients, v is the current operating frequency of the microwave source, and f(v) represents the number of fluorescence signals.

[0016] A possible design scheme, the method of the first aspect also includes, based on the function model, calculating the center frequency of the function model, including: based on the function model, determining that when v takes the value of v0, the function model f(v) reaches a maximum value, wherein v0 is the center frequency.

[0017] In a possible design scheme, the method of the first aspect further includes storing the fitting data in a container of a standard library, and using the function of the standard library to determine the maximum value and the minimum value of the function model, including:

[0018] The fitting data is stored in a container, and the max_element function and min_element function in the C++ standard library are used to traverse the container and return iterators pointing to the maximum and minimum values, thereby determining the maximum value f(v max ) and the minimum value f(v min ).

[0019] In a possible design scheme, the method of the first aspect further includes calculating a half-height value based on the maximum value and the minimum value of the function model, including:

[0020] Based on the maximum value of the function model f(v max ) and the minimum value f(v min ), through the formula Calculate the half-height value f(v Half).

[0021] A possible design scheme, the method of the first aspect further includes, based on the function model and the half-height value, calculating two frequency points, the absolute value of the difference between the two frequency points being the main peak spectral line width, including:

[0022] The half-height value f(v Half ) into the function model, we get Calculate two unequal roots v1 and v2 of the equation where

[0023] The absolute value of the difference between the two frequency points v1 and v2 is the spectral line width of the main peak, that is, Δ W =|v1-v2|.

[0024] In a second aspect, the present application provides a weak signal data fitting system, the system comprising: an acquisition module, a processing module and a calculation module; wherein:

[0025] An acquisition module, used for acquiring fluorescence signals;

[0026] A processing module, used for performing microwave scanning of different frequencies on the fluorescent signal according to a preset microwave frequency scanning range and step value, obtaining the number of fluorescent signals at different frequencies, and then drawing a scatter plot of the frequency and the number of fluorescent signals, for performing nonlinear fitting on the data on the scatter plot using a mathematical model, obtaining a function model and fitting data, for calculating the center frequency of the function model based on the function model, and for storing the fitting data in a container of a standard library, and determining the maximum and minimum values ​​of the function model using the function of the standard library;

[0027] The calculation module is used to calculate the half-height value based on the maximum and minimum values ​​of the function model, and is also used to calculate two frequency points based on the function model and the half-height value, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

[0028] In a third aspect, a data fitting device for a weak signal is provided, wherein the data fitting device for a weak signal comprises a module for executing the method of the first aspect.

[0029] In a possible design scheme, the data fitting device for weak signals of the third aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver may be used for the data fitting device for weak signals of the third aspect to communicate with other devices.

[0030] In a possible design scheme, the data fitting device for weak signals of the third aspect may further include a memory. The memory may be integrated with the processor or may be separately provided. The memory may be used to store instructions involved in the method of the first aspect.

[0031] In a fourth aspect, a data fitting device for a weak signal is provided. The data fitting device for a weak signal comprises: a processor coupled to a memory, the processor being configured to execute instructions stored in the memory so that the data fitting device for a weak signal executes the method described in the first aspect.

[0032] In a possible design scheme, the data fitting device for weak signals described in the fourth aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver may be used for the data fitting device for weak signals described in the fourth aspect to communicate with other devices.

[0033] In a fifth aspect, a data fitting device for a weak signal is provided, comprising: a processor and a memory; the memory is used to store instructions, and when the processor executes the instructions, the data fitting device for the weak signal executes the method described in the first aspect.

[0034] In a possible design scheme, the data fitting device for weak signals described in the fifth aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver may be used for the data fitting device for weak signals described in the fifth aspect to communicate with other devices.

[0035] In a sixth aspect, a computer-readable storage medium is provided, which includes a computer program or instruction stored therein. When the computer program or instruction is executed, the data fitting method for weak signals described in the first aspect is executed.

[0036] In an embodiment of the present application, a nonlinear fitting method is used to process the data based on the number of fluorescence signals and the scanning frequency obtained by microwave scanning. After processing, the frequency and fluorescence signal number model coefficients can be obtained. Based on the fitting conclusion, the accurate center frequency and spectral line width of the data can be calculated, which provides a basis for subsequent microwave source settings and frequency hopping settings, and helps to realize the development of high-performance new atomic frequency standards.

[0037] Other features and advantages of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 A schematic diagram of a flow chart of a data fitting method for weak signals provided in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of the structure of a weak signal data fitting device provided in an embodiment of the present application Figure 1 ;

[0041] Figure 3 A schematic diagram of the structure of a weak signal data fitting device provided in an embodiment of the present application Figure 2 . DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application. At the same time, in the description of the embodiments of the present application, the terms "first", "second", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0043] Figure 1 A flow chart of a data fitting method for weak signals provided in an embodiment of the present application. The data fitting method for weak signals is applicable to the case where the mercury ion microwave frequency standard is pumped by a mercury lamp, and its noise is tens to hundreds of times that of the signal. The data needs to be fitted to obtain the center frequency and spectral line width, or other possible scenarios, which are not limited here. To facilitate the understanding of this application, the following mainly uses the mercury ion microwave frequency standard scenario as an example for introduction.

[0044] The process of the data fitting method for the weak signal is as follows:

[0045] Step S101 , obtaining a fluorescence signal, and performing microwave scanning of different frequencies on the fluorescence signal according to a preset microwave frequency scanning range and step value, to obtain the number of fluorescence signals at different frequencies, and then draw a scatter plot of frequency and the number of fluorescence signals.

[0046] It can be understood that after the mercury ions are stably trapped in the ion trap, they are prepared by the mercury lamp to make them transition from the ground state to the excited state, and then they spontaneously radiate from the excited state to the ground state. 2 S 1 / 2 After the state preparation is completed, the ground state hyperfine structure F = 1 state is evacuated, and finally almost all ions fall into 2 S 1 / 2 F=0 state; at this time, 40.5GHz microwaves are applied (this frequency is the ground state2 S 1 / 2 The ions undergo resonant absorption and transition from the F=0 state to the F=1 state, increasing the number of ions in the F=1 state and pumping them back to the excited state. At this time, the spontaneous fluorescence becomes stronger, and the fluorescence signal is obtained by using a photomultiplier tube (PMT) in conjunction with the collection optical path. The signal intensity here is very weak relative to the noise floor. If the voltage data of the photomultiplier tube is used as the basis for the fluorescence signal conversion, the signal will be submerged. Therefore, single photon counting is required for collection, and a certain integration time is set to perform photon counting to obtain the fluorescence signal.

[0047] After that, the microwave frequency scanning range is preset, and the starting point of the range is F start , the stop point is F stop , attenuation Att, step value s, after starting the microwave source, the current frequency and photon count value (that is, the number of fluorescence signals at the current frequency) are recorded through self-compiled software. In addition, since the microwave frequency will be scanned and changed according to the step value, the number of ions transitioning from the F=0 state to the F=1 state is different, so the fluorescence signal value obtained is also different. When the microwave source frequency changes to the stop point, the microwave scan stops.

[0048] After the scanning is completed, a scatter plot of frequency and the number of fluorescent signals is drawn. The scatter plot is a two-dimensional data graph, with the horizontal axis being the frequency and the vertical axis being the number of fluorescent signals.

[0049] For example, a set of fluorescence signal data, with the increase of microwave frequency, the change of fluorescence signal intensity is shown in Table 1.

[0050] Microwave frequency (v) Number of fluorescent signals (y) 0.0 1 0.1 2 0.2 3 0.3 5 0.4 7 0.5 6 0.6 4 0.7 3 0.8 2

[0051] Table 1

[0052] According to the frequency and number of fluorescence signals in Table 1, a corresponding scatter plot can be drawn.

[0053] Step S102, using a mathematical model to perform nonlinear fitting on the data on the scatter plot to obtain a function model and fitting data.

[0054] It can be understood that according to the distribution characteristics of the data, an appropriate nonlinear model is selected, for example: common nonlinear models include exponential models, polynomial models, logarithmic models, power function models, etc., which are not limited here. Subsequently, mathematical methods (such as nonlinear least squares method) can be used to obtain fitting coefficients, and the fitted coefficients are substituted into the selected nonlinear model to obtain a function model.

[0055] In this application, nonlinear fitting is performed on the data on the scatter plot, and the obtained function model is: Among them, W, S0, y0, and v0 are all fitted coefficients, v is the current operating frequency of the microwave source, and f(v) represents the number of fluorescence signals.

[0056] Then you can use the function model to get the fitted data.

[0057] Step S103: Calculate the center frequency of the function model based on the function model.

[0058] In this application, since the variable v is in the denominator in the function model, and the value of v minus v0 is squared, it can be determined that when v takes the value of v0, the function model f(v) reaches the maximum value, and v0 is the center frequency.

[0059] In addition, for other possible function models, in order to determine the value of the variable and the maximum value of f(v), it may be necessary to use derivatives, iterative methods, graphical methods, the use of functions in software and programming language libraries, etc., to determine the value of the variable and the maximum value of f(v). These are not elaborated here.

[0060] Step S104, storing the fitting data in a container of a standard library, and using the functions of the standard library to determine the maximum and minimum values ​​of the function model.

[0061] Store the fitted data in a container, such as std::vector or std::array. Then, use the C++ standard library <algorithm>The max_element function and min_element function provided by the header file traverse the container and return iterators pointing to the maximum and minimum values, thereby determining the maximum value f(v max ) and the minimum value f(v min ).

[0062] Step S105, calculating the half-height value based on the maximum value and the minimum value of the function model.

[0063] Based on the maximum value of the function model f(v max ) and the minimum value f(v min ), through the formula Calculate the half-height value f(v Half ).

[0064] Step S106, based on the function model and the half-height value, two frequency points are calculated, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

[0065] The half-height value f(v Half ) into the function model, we get Calculate two unequal roots v1 and v2 of the equation where

[0066] The absolute value of the difference between the two frequency points v1 and v2 is the spectral line width of the main peak, that is, Δ W =|v1-v2|.

[0067] In summary, based on the number of fluorescence signals and the sweep frequency obtained by microwave sweeping, the data is processed using a nonlinear fitting method. After processing, the frequency and fluorescence signal quantity model coefficients can be obtained. Based on the fitting conclusion, the accurate center frequency and spectral line width of the data can be calculated, which provides a basis for the subsequent microwave source setting and frequency hopping setting, and is conducive to the development of high-performance new atomic frequency standards.

[0068] Combination of the above Figure 1 The data fitting method for weak signals provided in the embodiment of the present application is described in detail. The data fitting system for weak signals provided in the embodiment of the present application is described in detail below.

[0069] The system specifically includes: an acquisition module, a processing module and a calculation module, as shown below.

[0070] An acquisition module, used for acquiring fluorescence signals;

[0071] A processing module, used for performing microwave scanning of different frequencies on the fluorescent signal according to a preset microwave frequency scanning range and step value, obtaining the number of fluorescent signals at different frequencies, and then drawing a scatter plot of the frequency and the number of fluorescent signals, and for performing nonlinear fitting on the data on the scatter plot using a mathematical model to obtain a function model and fitting data, and for calculating the central frequency of the function model based on the function model, and for storing the fitting data in a container of a standard library, and determining the maximum and minimum values ​​of the function model using the function of the standard library;

[0072] The calculation module is used to calculate the half-height value based on the maximum and minimum values ​​of the function model, and is also used to calculate two frequency points based on the function model and the half-height value, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

[0073] In addition, for the above-mentioned specific implementation of the system, since it is basically similar to the method implementation, the description is relatively simple, and the relevant parts can be referred to the partial description of the method implementation. Moreover, it should be noted that in each module of the system of the present application, the components therein are logically divided according to the functions to be implemented, but the present application is not limited thereto, and the components can be re-divided or combined as needed.

[0074] The above describes the weak signal data fitting method and system provided by the embodiments of the present application. Figure 2-Figure 3 A data fitting device for executing a weak signal provided in an embodiment of the present application is described in detail.

[0075] Figure 2 The structure of the data fitting device for weak signals provided in the embodiment of the present application is shown in FIG. Figure 1 For example, Figure 2 As shown, the weak signal data fitting device 200 includes: a transceiver module 201 and a processing module 202. For ease of description, Figure 2 Only the main components of the data fitting apparatus for this weak signal are shown.

[0076] The transceiver module 201 is used to perform the transceiver function of the weak signal data fitting method, and the processing module 202 is used to perform other functions of the weak signal data fitting method except the transceiver function.

[0077] Optionally, the transceiver module 201 may include a sending module ( Figure 2 ) and a receiving module ( Figure 2 (not shown in the figure). The sending module is used to implement the sending function of the data fitting device 200 for weak signals, and the receiving module is used to implement the receiving function of the data fitting device 200 for weak signals.

[0078] Optionally, the weak signal data fitting device 200 may further include a storage module ( Figure 2 (not shown), the storage module stores a program or instruction. When the processing module 202 executes the program or instruction, the weak signal data fitting device 200 can perform the weak signal data fitting method in the embodiment of the present application.

[0079] Combine the following Figure 3 Each component of the weak signal data fitting device 300 is specifically introduced:

[0080] The processor 301 is the control center of the weak signal data fitting device 300, which can be a processor or a general term for multiple processing elements. For example, the processor 301 is one or more central processing units (CPUs), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (field programmable gate arrays, FPGAs).

[0081] Optionally, the processor 301 can execute various functions of the weak signal data fitting device 300 by running or executing a software program stored in the memory 302 and calling data stored in the memory 302, such as executing the weak signal data fitting method in the embodiment of the present application.

[0082] In a specific implementation, as an embodiment, the processor 301 may include one or more CPUs, such as Figure 3 CPU0 and CPU1 are shown in FIG.

[0083] In a specific implementation, as an embodiment, the weak signal data fitting device 300 may also include multiple processors, such as Figure 3 The processor 301 and processor 304 shown in . Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions). Among them, the memory 302 is used to store the software program for executing the solution of the present application, and the execution is controlled by the processor 301. The specific implementation method can refer to the above method embodiment, which will not be repeated here.

[0084] Optionally, the memory 302 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 302 may be integrated with the processor 301, or may exist independently, and may be connected to the processor 301 through the interface circuit ( Figure 3 (not shown) is coupled to the processor 301, which is not specifically limited in the embodiment of the present application.

[0085] The transceiver 303 is used for communication with other communication devices. For example, the weak signal data fitting device 300 is a first device, and the transceiver 303 can be used for communication with a second device or a third device.

[0086] Optionally, the transceiver 303 may include a receiver and a transmitter ( Figure 3 The receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0087] Optionally, the transceiver 303 may be integrated with the processor 301, or may exist independently, and communicate with the weak signal data fitting device 300 through an interface circuit ( Figure 3 (not shown) is coupled to the processor 301, which is not specifically limited in the embodiment of the present application.

[0088] Understandably, Figure 3 The structure of the weak signal data fitting device 300 shown in the figure does not constitute a limitation on the weak signal data fitting device. The actual weak signal data fitting device may include more or fewer components than those shown in the figure, or combine certain components, or arrange the components differently.

[0089] In addition, the technical effects of the weak signal data fitting device 300 can refer to the technical effects of the methods described in the above method embodiments, which will not be repeated here.

[0090] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0091] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0092] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.< / algorithm>

Claims

1. A data fitting method for weak signals, characterized in that: The method comprises: Acquire a fluorescence signal, and perform microwave scanning of different frequencies on the fluorescence signal according to a preset microwave frequency scanning range and step value to obtain the number of fluorescence signals at different frequencies, and then draw a scatter plot of frequency and number of fluorescence signals; Perform nonlinear fitting on the data on the scatter plot using a mathematical model to obtain a function model and fitting data; Based on the function model, calculating the center frequency of the function model; Storing the fitting data in a container of a standard library, and using the function of the standard library to determine the maximum and minimum values ​​of the function model; Calculating a half-height value based on the maximum and minimum values ​​of the function model; Based on the function model and the half-height value, two frequency points are calculated, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

2. The data fitting method for weak signals according to claim 1, characterized in that: The scatter plot of frequency and the number of fluorescent signals is a two-dimensional data graph, with the horizontal axis being the frequency and the vertical axis being the number of fluorescent signals.

3. The data fitting method for weak signals according to claim 1, characterized in that: The method of using a mathematical model to perform nonlinear fitting on the data on the scatter plot to obtain a function model and fitting data includes: The function model is: Among them, W, S0, y0, 0 are all fitted coefficients, is the current working frequency of the microwave source, and f() represents the number of fluorescence signals.

4. The data fitting method for weak signals according to claim 3, characterized in that: The step of calculating the center frequency of the function model based on the function model includes: Based on the function model, it is determined that when the value is 0, the function model f() obtains a maximum value, and 0 is the center frequency.

5. The data fitting method for weak signals according to claim 4, characterized in that: The step of storing the fitting data in a container of a standard library and using a function of the standard library to determine a maximum value and a minimum value of the function model comprises: The fitting data is stored in a container of a standard library, and the container is traversed using the max_element function and the min_element function in the standard library, and iterators pointing to the maximum and minimum values ​​are returned, thereby determining the maximum value f( max ) and the minimum value f( min ).

6. The data fitting method for weak signals according to claim 5, characterized in that: The calculating of the half-height value based on the maximum value and the minimum value of the function model includes: Based on the maximum value f( max ) and the minimum value f( min ), through the formula Calculate the half-height value ().

7. The data fitting method for weak signals according to claim 6, characterized in that: The step of calculating two frequency points based on the function model and the half-height value, wherein the absolute value of the difference between the two frequency points is the main peak spectral line width, comprises: Substituting the half-height value () into the function model, we get Calculate two unequal roots 1 and 2 of the equation, where The absolute value of the difference between the two frequency points 1 and 2 is the spectral line width of the main peak, that is, W =| 12 |.

8. A data fitting system for weak signals, characterized in that: The system comprises: an acquisition module, a processing module and a calculation module; The acquisition module is used to acquire the fluorescence signal; The processing module is used to perform microwave scanning of different frequencies on the fluorescent signal according to a preset microwave frequency scanning range and step value to obtain the number of fluorescent signals at different frequencies, and then draw a scatter plot of the frequency and the number of fluorescent signals, and to use a mathematical model to perform nonlinear fitting on the data on the scatter plot to obtain a function model and fitting data, and to calculate the center frequency of the function model based on the function model, and to store the fitting data in a container of a standard library, and to determine the maximum and minimum values ​​of the function model using the function of the standard library; The calculation module is used to calculate the half-height value based on the maximum value and the minimum value of the function model, and is also used to calculate two frequency points based on the function model and the half-height value, and the absolute value of the difference between the two frequency points is the main peak spectral line width.

9. A data fitting device for weak signals, characterized in that: The apparatus comprises: a module for executing the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a computer program or instruction stored therein, and when the computer program or instruction is executed, the method according to any one of claims 1 to 7 is performed.

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