A fluorescence lifetime characteristic value extraction method and system based on a scattering and fluorescence emission dual-channel signal

Abstract

The application discloses a fluorescence lifetime characteristic value extraction method and system based on a Mie scattering and fluorescence emission dual-channel signal, and relates to the field of atmospheric pollutant detection.The method comprises the following steps: acquiring a dual-channel signal; the dual-channel signal comprises an original Mie scattering signal and an original fluorescence emission signal; constructing a simulation model; setting a fluorescence lifetime; taking the original Mie scattering signal and the set fluorescence lifetime as inputs of the simulation model to obtain a predicted fluorescence emission signal; determining the deviation between the original fluorescence emission signal and the predicted fluorescence emission signal, and returning to the step of setting the fluorescence lifetime until the set number of iterations is reached, and then taking the fluorescence lifetime corresponding to the minimum deviation as the fluorescence lifetime characteristic value extraction result.The application can break through the limitation that a nanosecond long-pulse laser cannot measure the fluorescence lifetime characteristic value, and greatly improve the robustness of a laser radar system to meteorological conditions and system parameter changes.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of atmospheric pollutant detection, in particular to a fluorescence lifetime characteristic value extraction method and system based on a dual-channel signal of Mie scattering and fluorescence emission. BACKGROUND

[0002] In atmospheric pollutant detection, time-resolved fluorescence lifetime measurement technology extracts fluorescence lifetime characteristic values by measuring the change curve of fluorescence intensity with time through picosecond-level ultra-narrow pulse laser. This kind of technology usually uses a signal sequence at one waveband to extract the fluorescence lifetime, and requires that the pulse width of the excitation pulse light is much smaller than the fluorescence lifetime value of the target to be measured.

[0003] In the application scenario of laser radar remote sensing measurement, the pulse width of the pulsed laser is usually large and cannot meet the requirement of time resolution for fluorescence lifetime measurement, so it is impossible to measure the fluorescence lifetime characteristic value. SUMMARY

[0004] The purpose of the present application is to provide a fluorescence lifetime characteristic value extraction method and system based on a dual-channel signal of Mie scattering and fluorescence emission, which can break through the limitation that nanosecond-level long pulse width pulsed laser cannot measure the fluorescence lifetime characteristic value, and greatly improve the robustness of the laser radar system to meteorological conditions and system parameter changes.

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] In a first aspect, the present application provides a fluorescence lifetime characteristic value extraction method based on a dual-channel signal of Mie scattering and fluorescence emission, comprising:

[0007] Obtaining a dual-channel signal; the dual-channel signal is obtained by detecting atmospheric pollutants using a laser radar system; the dual-channel signal includes an original Mie scattering signal and an original fluorescence emission signal;

[0008] Constructing a simulation model;

[0009] Setting a fluorescence lifetime;

[0010] Taking the original Mie scattering signal and the set fluorescence lifetime as inputs of the simulation model to obtain a predicted fluorescence emission signal;

[0011] Determining the deviation between the original fluorescence emission signal and the predicted fluorescence emission signal, and returning to the step of setting the fluorescence lifetime until a set number of iterations is reached, and taking the fluorescence lifetime corresponding to the minimum deviation as the fluorescence lifetime characteristic value extraction result.

[0012] Optionally, obtaining a dual-channel signal comprises:

[0013] The laser radar system is used to detect atmospheric pollutants to obtain a Mie scattering echo power signal and a fluorescence emission echo power signal;

[0014] The Mie scattering echo power signal is used to generate a Mie scattering echo intensity based on a Mie scattering principle;

[0015] The Mie scattering echo intensity is arranged according to sampling points to obtain the original Mie scattering signal;

[0016] The fluorescence emission echo power signal is used to generate a fluorescence echo intensity based on a fluorescence emission principle;

[0017] The fluorescence echo intensity is arranged according to sampling points to obtain the original fluorescence emission signal.

[0018] Optionally, the Mie scattering echo power signal is represented as:

[0019]

[0020] In the formula, P Mie represents the Mie scattering echo power signal detected by the laser radar system at t = 2R / c, R represents a detection distance, λ represents an echo wavelength, c represents a light speed, T r represents a transmission efficiency of the laser radar system, (A r ) / R 2 represents a solid angle, A r represents an effective receiving area of a telescope, T(λ, R) represents an atmospheric transmittance, and ξ(R) represents a geometric overlap factor. E (R) represents a cross-sectional area of a laser beam at the detection distance R, represents a particle backscattering differential cross section, λ l represents an emission laser wavelength, and I(R) represents an average light intensity of pulsed light. represents a laser radar distance resolution, τ l represents a rectangular laser pulse width, and N0(R) represents a ground state particle number density when a laser pulse front arrives at the detection distance R.

[0021] Optionally, the fluorescence emission echo power signal is represented as:

[0022]

[0023] In the formula, P Fluorescence represents the fluorescence emission echo power signal detected by the laser radar system at t = 2R / c, R represents a detection distance, λ represents an echo wavelength, c represents a light speed, A r represents an effective receiving area of a telescope, K r(λ) represents the proportion of the energy in the wavelength range received by the lidar system to the total energy in the wavelength range, L F (λ) represents the spectral distribution function of the fluorescent substance, σ F (λ l ) represents the total effective fluorescence scattering cross section, λ l represents the emission laser wavelength, ξ(R) represents the geometric overlap factor, N0 represents the ground state particle number, T(λ, R) represents the atmospheric transmittance, τ represents the apparent fluorescence lifetime of the fluorescent particles, the time experienced after the laser pulse front reaches R', I(R', x) represents the laser irradiance at R' after x time after the laser pulse front reaches R', and R' represents the distance corresponding to the target at R.

[0024] Optionally, the variance of the original fluorescence emission signal and the predicted fluorescence emission signal is taken as the deviation.

[0025] Optionally, the deviation between the original fluorescence emission signal and the predicted fluorescence emission signal is determined, and the step of setting the fluorescence lifetime is returned to be executed until a set number of iterations is reached, and the fluorescence lifetime corresponding to the minimum deviation is taken as the fluorescence lifetime characteristic value extraction result, comprising:

[0026] A nonlinear optimization algorithm is used to search for the fluorescence lifetime corresponding to the minimum deviation in a preset range with a preset search precision.

[0027] Optionally, the nonlinear optimization algorithm at least includes a global optimization algorithm and a multi-objective optimization algorithm.

[0028] In a second aspect, the present application provides a fluorescence lifetime characteristic value extraction system based on Mie scattering and fluorescence emission dual-channel signals, comprising:

[0029] A lidar system is used to detect atmospheric pollutants to obtain dual-channel signals; the dual-channel signals include original Mie scattering signals and original fluorescence emission signals;

[0030] A processing system is connected with the lidar system, and is used to implement the fluorescence lifetime characteristic value extraction method provided above based on the dual-channel signals to obtain a fluorescence lifetime characteristic value extraction result.

[0031] Optionally, the processing system is a computer.

[0032] Optionally, the processing system includes a touch screen.

[0033] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0034] The application provides a fluorescence lifetime characteristic value extraction method and system based on a Mie scattering and fluorescence emission dual-channel signal. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0036] Figure 1 A flowchart of a fluorescence lifetime characteristic value extraction method based on a Mie scattering and fluorescence emission dual-channel signal is provided for an embodiment of the present application.

[0037] Figure 2 A structural diagram of a computer device is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0039] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail with reference to the drawings and specific embodiments.

[0040] In an exemplary embodiment, as shown in Figure 1 A fluorescence lifetime characteristic value extraction method based on a Mie scattering and fluorescence emission dual-channel signal is provided, which is executed by a computer device, specifically, can be executed by a terminal or a server, or can be executed by a terminal and a server. In the embodiments of the present application, the method is applied to a server as an example, which includes:

[0041] Step 100: Obtain a dual-channel signal. The dual-channel signal is obtained by detecting atmospheric pollutants by a laser radar system. The dual-channel signal includes a raw Mie scattering signal and a raw fluorescence emission signal.

[0042] Step 101: Construct a simulation model.

[0043] Step 102: Set a fluorescence lifetime.

[0044] Step 103: Take the raw Mie scattering signal and the set fluorescence lifetime as inputs of the simulation model to obtain a predicted fluorescence emission signal.

[0045] Step 104: Determine a deviation between the raw fluorescence emission signal and the predicted fluorescence emission signal, and return to execute Step 102 until a set number of iterations is reached, and take the fluorescence lifetime corresponding to the minimum deviation as a fluorescence lifetime feature value extraction result.

[0046] This step is an iterative process of determining a fluorescence lifetime calculation deviation. The raw Mie scattering signal is taken as an input parameter of the simulation model, and a guessed fluorescence channel intensity sequence (i.e., a predicted fluorescence emission signal) is output by the simulation model by simultaneously inputting the set fluorescence lifetime. The raw fluorescence emission signal obtained by collection is taken as a standard answer, and a deviation is calculated between the raw fluorescence emission signal and the guessed fluorescence channel intensity sequence output by the simulation model, to obtain a sequence intensity deviation (i.e., a deviation) corresponding to the fluorescence lifetime. Finally, the fluorescence lifetime input when the minimum deviation is searched is taken as a final fluorescence lifetime feature value extraction result.

[0047] In another exemplary embodiment of the present application, the implementation process of Step 100 can be described as follows:

[0048] Step 1001: Detect atmospheric pollutants by a radar system to obtain a Mie scattering echo power signal and a fluorescence emission echo power signal.

[0049] The Mie scattering echo power signal is described by a laser radar equation as follows:

[0050]

[0051] In the formula, P Mie (λ, R) represents the Mie scattering echo power signal detected by the laser radar system at t = 2R / c, R represents a detection distance, λ represents an echo wavelength, and c represents a light speed. T r (λ) represents a transmission efficiency of the laser radar system, which is dimensionless. (A r ) / R 2 represents a solid angle, which represents a solid angle of a unit volume of a target substance corresponding to a receiving system, and has a unit of sr . A rrepresents the effective receiving area of the telescope, T(λ, R) represents the atmospheric transmittance, which represents the ratio of the signal strength of the echo signal at wavelength λ after passing through the atmospheric medium at detection distance R to the initial signal strength, dimensionless. ξ(R) represents the geometric overlap factor, which represents the proportion of the effective echo signal received by the receiving system, dimensionless. A E (R) represents the cross-sectional area of the laser beam at detection distance R, with units of m 2 , A E (R)ΔR is the surface element. represents the particle body backscattering differential cross section, λ l represents the emission laser wavelength, I(R) represents the average light intensity of the pulsed light, represents the laser radar distance resolution, τ l represents the rectangular laser pulse width, N0(R) represents the ground state particle number density when the laser pulse front arrives at the detection distance R.

[0052] The fluorescence emission echo power signal is described by the laser radar equation combined with the fluorescence emission expression as:

[0053]

[0054] In the formula, P Fluorescence (λ, R) represents the fluorescence emission echo power signal detected by the laser radar system at t = 2R / c, and R represents the detection distance. K r (λ) represents the proportion of the energy received by the laser radar system in the wavelength range to the total wavelength range energy, L F (λ) represents the spectral distribution function of the fluorescent substance, σ F (λ l ) represents the total effective fluorescence scattering cross section, ξ(R) represents the geometric overlap factor, N0 represents the ground state particle number, T(λ, R) represents the atmospheric transmittance, τ represents the apparent fluorescence lifetime of the fluorescent particles, x represents the time experienced after the laser pulse front arrives at R', I(R', x) represents the laser irradiance at R' after x time after the laser pulse front arrives at R', and R' represents the corresponding distance of the target before R.

[0055] Step 1002: Based on the Mie scattering echo power signal, the Mie scattering echo intensity is generated based on the Mie scattering principle.

[0056] Step 1003: Arrange the Mie scattering echo intensity according to the sampling points to obtain the original Mie scattering signal.

[0057] Step 1004: Based on the fluorescence emission echo power signal, the fluorescence echo intensity is generated based on the fluorescence emission principle.

[0058] Step 1005: arrange the fluorescence echo intensity according to the sampling points to obtain the original fluorescence emission signal.

[0059] In another exemplary embodiment of the present application, variance is used as an evaluation function of the deviation between the original fluorescence emission signal and the predicted fluorescence emission signal, and has:

[0060]

[0061] In the formula, i represents the point number of the signal sequence, n is the length of the signal sequence, X i represents the original fluorescence emission signal sequence, Y i represents the predicted fluorescence emission signal sequence, and E represents the deviation.

[0062] Further, in this embodiment, the original fluorescence emission signal sequence is replaced by the Mie scattering signal sequence, and the predicted fluorescence emission signal sequence is replaced by the original fluorescence emission signal sequence. Then, the above evaluation function can be used as an evaluation function of the sequence deviation between the Mie scattering signal and the fluorescence emission signal.

[0063] In another exemplary embodiment of the present application, a nonlinear optimization algorithm can be used to search for a unique fluorescence lifetime within a preset range with a preset search precision, so that the deviation between the corresponding output sequence and the fluorescence channel intensity sequence is minimized. Then, the fluorescence lifetime is the final extraction result. The nonlinear optimization algorithm includes but is not limited to global optimization algorithm and multi-objective optimization algorithm.

[0064] In another exemplary embodiment of the present application, the fluorescence lifetime characteristic value extraction method provided by the present application comprises the following 5 steps:

[0065] Step 000: acquire the dual-channel signal.

[0066] For example, the original dual-channel signal is obtained by using a laser radar system to detect a target. The dual-channel signal includes (1) Mie signal: a sequence of Mie scattering echo intensity arranged according to sampling points. (2) Fluorescence signal: a sequence of fluorescence emission echo intensity arranged according to sampling points.

[0067] Step 001: establish a simulation model. The core of the simulation model is an equation describing the physical process combining the laser radar equation and the expression of the number of fluorescence particles. The input of the simulation model can be simplified as the Mie scattering signal and the fluorescence lifetime, and the output of the simulation model is the fluorescence emission signal.

[0068] In actual application, the simulation model calculates the Mie scattering signal and the fluorescence signal according to formula (1) and formula (2). The parameters in formula (1) and formula (2) are divided into two parts:

[0069] 1) Constant: atmospheric parameters or system parameters, part of the parameters are fixed values, and do not affect the normalization result of the simulation model output.

[0070] 2) Variable: laser pulse shape function, fluorescence lifetime, fluorescence lifetime depends on the properties of the target to be detected, and the value of the laser pulse shape function and the fluorescence lifetime changes will change the output result.

[0071] Combined with formula (1) and formula (2), the above simulation model can be obtained.

[0072] Step 002: Define the calculation formula for comparing the deviation of the two intensity signal sequences

as shown in formula (3)

[0073] Step 003: Use the defined calculation formula to iterate the fluorescence lifetime calculation deviation.

[0074] In actual application process, the iteration of fluorescence lifetime calculation deviation process has 2 steps:

[0075] (1) The original signal of the M channel (i.e. the original M scattering signal) is used as the input parameter of the simulation model, and the preset or guessed fluorescence lifetime is simultaneously inputted, and the simulation model will simulate and calculate to generate a guessed fluorescence channel intensity sequence output (i.e. the predicted fluorescence emission signal).

[0076] (2) The original signal of the fluorescence channel (i.e. the original fluorescence emission signal) is regarded as the standard answer, and the guessed fluorescence channel intensity sequence output by the simulation model is used for deviation calculation, so as to obtain the corresponding sequence intensity deviation under this fluorescence lifetime.

[0077] Step 004: Search for the input fluorescence lifetime when the minimum deviation is obtained.

[0078] In actual application process, a nonlinear optimization algorithm can be used to search for the unique fluorescence lifetime in the preset range with a preset search accuracy, so that the deviation between the corresponding output sequence and the fluorescence channel intensity sequence is minimized, and then the fluorescence lifetime is the final extraction result.

[0079] Based on the above description, the difference between the double-channel signals in the time dimension is introduced, which can break through the requirement of time resolution measurement method for short pulse width (usually picosecond level) of pulsed light, so that long pulse width laser light source (nanosecond level) can still realize the measurement of fluorescence lifetime in the application scene of laser radar remote sensing detection of atmospheric pollutants. At the same time, since the difference between the double-channel signals does not change with the change of meteorological conditions and system constants, the detection of the laser radar has higher stability.

[0080] Based on the same inventive concept, the application further provides a fluorescence lifetime characteristic value extraction system based on the Mie scattering and fluorescence emission dual-channel signal for implementing the fluorescence lifetime characteristic value extraction method described above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method, so the specific limitations in one or more fluorescence lifetime characteristic value extraction system embodiments based on the Mie scattering and fluorescence emission dual-channel signal provided below can be referred to the limitations of the fluorescence lifetime characteristic value extraction method based on the Mie scattering and fluorescence emission dual-channel signal in the above, which will not be repeated here.

[0081] In an exemplary embodiment, a fluorescence lifetime characteristic value extraction system based on the Mie scattering and fluorescence emission dual-channel signal is provided, comprising:

[0082] A laser radar system is used to detect atmospheric pollutants to obtain a dual-channel signal. The dual-channel signal includes an original Mie scattering signal and an original fluorescence emission signal.

[0083] A processing system is connected to the laser radar system and is used to implement the fluorescence lifetime characteristic value extraction method provided above based on the dual-channel signal to obtain a fluorescence lifetime characteristic value extraction result.

[0084] As an optional implementation, the processing system is a computer to store a host computer control system to control the laser radar slave computer, and to store and run the fluorescence lifetime characteristic value extraction algorithm.

[0085] In this implementation, a touch screen can be provided in the processing system.

[0086] As an optional implementation, the laser radar system includes a laser emission module, an optical receiving module, an optical splitting module, a photoelectric conversion module, and a data acquisition module.

[0087] The laser emission module emits pulsed laser in the ultraviolet band into the atmosphere, so that the pulsed laser interacts with the atmospheric pollutants in the path. The optical receiving module receives the total return light generated by the interaction of the laser and the substance and converges to the splitting module. The optical splitting module includes a splitting module and a filtering module to split the total return light into an ultraviolet band and a fluorescence band. Among them, the return signal in the ultraviolet band is the Mie scattering signal, and the return signal in the fluorescence band is the fluorescence emission signal, which constitutes the dual-channel signal.

[0088] The photoelectric conversion module is connected to the optical splitting module to convert the dual-channel signal into an electrical signal,

[0089] The data acquisition module is connected to the photoelectric conversion module to read the electrical signal as a digital signal, and each time one channel is acquired to obtain an intensity sequence arranged according to the sampling point number.

[0090] Based on the above description, the application adopts a fluorescence laser radar system to detect atmospheric pollutants with fluorescence effect, collects Mie scattering and fluorescence emission echo signals of interaction between laser and detection targets as original data, analyzes fluorescence lifetime characteristic values representing the detection targets according to time delay of the Mie and fluorescence dual-channel signals, breaks through the limitation that nanosecond long pulse laser cannot measure the fluorescence lifetime characteristic values, and greatly improves the robustness of the laser radar system to meteorological conditions and system parameter changes.

[0091] In an exemplary embodiment, a computer device, which can be a server or a terminal, is provided, and an internal structure diagram of the computer device can be as shown in Figure 2 The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store video tag processing data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement a video tag processing method.

[0092] Those skilled in the art can understand that Figure 2 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the application, and does not constitute a limitation on the computer device to which the scheme of the application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0093] In an exemplary embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0094] In an exemplary embodiment, a computer program product is provided, which includes a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0095] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0096] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of each method can be included. In the embodiments provided in the present application, any reference to memory, database or other medium can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc.

[0097] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0098] The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, but as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0099] The principles and implementations of the present application are described in detail with specific examples in this paper, and the above examples are only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation and application range will be changed. Therefore, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for extracting fluorescence lifetime characteristic values ​​based on dual-channel signals of Mie scattering and fluorescence emission, characterized in that, The fluorescence lifetime feature value extraction method based on Mie scattering and fluorescence emission dual-channel signals includes: Acquire dual-channel signals; the dual-channel signals are obtained by detecting atmospheric pollutants using a lidar system; the dual-channel signals include raw Mie scattering signals and raw fluorescence emission signals. The process of acquiring dual-channel signals includes: using a lidar system to detect atmospheric pollutants and obtaining Mie scattering echo power signals and fluorescence emission echo power signals; using the Mie scattering principle, generating Mie scattering echo intensity based on the Mie scattering echo power signals; arranging the Mie scattering echo intensities according to sampling points to obtain the original Mie scattering signal; using the fluorescence emission principle, generating fluorescence echo intensity based on the fluorescence emission echo power signals; arranging the fluorescence echo intensities according to sampling points to obtain the original fluorescence emission signal. The Mie scattering echo power signal is described by the lidar equation as follows: In the formula, P Mie (λ,R) represents the Mie scattering echo power signal detected by the lidar system at time t = 2R / c, where R represents the detection distance, λ represents the echo wavelength, c represents the speed of light, and T... r (λ) represents the transmission efficiency of the lidar system, (A) r ) / R 2 Represents a solid angle, A r Let T(λ,R) represent the effective receiving area of ​​the telescope, T(λ,R) represent the atmospheric transmittance, ξ(R) represent the geometric overlap factor, and A represent the effective receiving area of ​​the telescope. E (R) represents the cross-sectional area of ​​the laser beam at a detection distance R. λ represents the differential cross section for particle backscattering. l I(R) represents the emitted laser wavelength, and I(R) represents the average intensity of the pulsed light. τ represents the range resolution of the lidar. l N0(R) represents the rectangular laser pulse width, and N0(R) represents the ground state particle number density when the laser pulse leading edge reaches the detection distance R. The fluorescence emission echo power signal is described by combining the lidar equation with the fluorescence emission expression: In the formula, P Fluorescence (λ,R) represents the fluorescence emission echo power signal detected by the lidar system at time t = 2R / c, K r (λ) represents the proportion of energy received within the band range by the lidar system to the total energy within the band range, L F (λ) represents the spectral distribution function of the fluorescent substance, σ F (λ l The cross section represents the total effective fluorescence scattering cross section, and N0 represents the number of ground-state particles. τ represents the apparent fluorescence lifetime of the fluorescent particles, x represents the time elapsed after the laser pulse front reaches R′, I(R′,x) represents the laser illuminance at R′ after time x elapsed after the laser pulse front reaches R′, and R′ represents the distance to the target at R. A simulation model is constructed. The core of the simulation model is an equation describing the physical process that combines the lidar equation and the expression for the number of fluorescent particles. The input of the simulation model is the Mie scattering signal and the fluorescence lifetime, and the output of the simulation model is the fluorescence emission signal. The simulation model is obtained by combining formula (1) and formula (2). Set fluorescence lifetime; The original Mie scattering signal and the set fluorescence lifetime are used as inputs to the simulation model to obtain the predicted fluorescence emission signal; The deviation between the original fluorescence emission signal and the predicted fluorescence emission signal is determined, and the process returns to the step of setting the fluorescence lifetime until the set number of iterations is reached. The fluorescence lifetime corresponding to the minimum deviation is then used as the fluorescence lifetime feature value extraction result.

2. The method for extracting fluorescence lifetime characteristic values ​​based on dual-channel signals of Mie scattering and fluorescence emission according to claim 1, characterized in that, The variance between the original fluorescence emission signal and the predicted fluorescence emission signal is used as the deviation.

3. The method for extracting fluorescence lifetime characteristic values ​​based on dual-channel signals of Mie scattering and fluorescence emission according to claim 1, characterized in that, Determine the deviation between the original fluorescence emission signal and the predicted fluorescence emission signal, and return to the step of setting the fluorescence lifetime until the set number of iterations is reached. Then, use the fluorescence lifetime corresponding to the minimum deviation as the fluorescence lifetime feature value extraction result, including: A nonlinear optimization algorithm is used to search for the fluorescence lifetime corresponding to the minimum deviation within a preset range and with a preset search precision.

4. The method for extracting fluorescence lifetime characteristic values ​​based on dual-channel signals of Mie scattering and fluorescence emission according to claim 3, characterized in that, The nonlinear optimization algorithm includes at least a global optimization algorithm and a multi-objective optimization algorithm.

5. A fluorescence lifetime characteristic value extraction system based on dual-channel signals of Mie scattering and fluorescence emission, characterized in that, The fluorescence lifetime feature extraction system based on dual-channel signals of Mie scattering and fluorescence emission includes: A lidar system is used to detect atmospheric pollutants and obtain dual-channel signals; the dual-channel signals include raw Mie scattering signals and raw fluorescence emission signals. The processing system, connected to the lidar system, is used to implement the fluorescence lifetime feature value extraction method based on Mie scattering and fluorescence emission dual-channel signals as described in any one of claims 1-4, based on the dual-channel signals, to obtain the fluorescence lifetime feature value extraction result.

6. The fluorescence lifetime characteristic value extraction system based on dual-channel signals of Mie scattering and fluorescence emission according to claim 5, characterized in that, The processing system is a computer.

7. The fluorescence lifetime characteristic value extraction system based on dual-channel signals of Mie scattering and fluorescence emission according to claim 5, characterized in that, The processing system includes a touchscreen.

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