A filter bandwidth selection method and apparatus for a raman-fluorescence lidar

Abstract

The application provides a filter bandwidth selection method and device for a Raman-fluorescence laser radar. The method provided by the application comprises the following steps: using a biological optical model to solve the attenuation contribution of pure water and chlorophyll components in a water body to a laser signal, and obtaining water optical parameters; constructing a laser radar signal simulation model based on the water optical parameters; including background light noise into the laser radar signal simulation model to form a complete received signal model; taking the ratio of a target channel exclusive signal to the complete received signal as the target signal ratio of filter bandwidth selection; determining a signal intensity rule; determining a target signal ratio rule; setting a signal intensity lower limit and a target signal ratio lower limit based on the signal intensity rule and the target signal ratio rule, screening out a filter bandwidth range that meets the requirements of both lower limits, and determining the maximum bandwidth in the filter bandwidth range as the optimal filter bandwidth.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bandwidth selection, and particularly relates to a filter bandwidth selection method and device for Raman-fluorescence lidar. BACKGROUND

[0002] The dual-channel observation mode of Raman-fluorescence lidar can obtain rich ocean information by combining Raman signals and fluorescence signals, and the filter bandwidth is a core factor determining the detection performance thereof, and it is crucial to select the bandwidth reasonably. On the one hand, the received signal strength is positively correlated with the filter bandwidth, and the bandwidth directly affects the signal acquisition capability; on the other hand, there is an inherent signal crosstalk problem in dual-channel detection, and the increase of the bandwidth will significantly exacerbate the spectral aliasing between different channels, thereby reducing the signal purity, and therefore it is necessary to balance the contradiction between the signal strength and the detection purity by scientific selection.

[0003] Current filter bandwidth selection mostly depends on signal simulation means, and a quantitative index of spectral aliasing effect is constructed to assist selection, and the core idea is to determine the bandwidth range based on the signal aliasing law. However, the existing methods generally do not consider the background light noise caused by solar radiation in the actual detection environment, and the background light noise can drown the weak echo signal of Raman-fluorescence, thereby causing the signal-to-noise ratio of the received signal to deteriorate and the detection precision to decrease significantly, and the performance requirements of real ocean detection cannot be met.

[0004] Therefore, there is an urgent need for a method that comprehensively considers the signal strength, background light noise and spectral aliasing effect to achieve optimal bandwidth selection. SUMMARY

[0005] Therefore, the present application provides a filter bandwidth selection method and device for Raman-fluorescence lidar, which comprehensively considers the signal strength, background light noise and spectral aliasing effect to achieve optimal bandwidth selection.

[0006] Specifically, the present application is implemented by the following technical solutions:

[0007] The first aspect of the present application provides a filter bandwidth selection method for Raman-fluorescence lidar, and the method comprises:

[0008] The biological optical model is used to calculate the attenuation contribution of pure water and chlorophyll components to the laser signal in the water body under the set chlorophyll concentration, and the water body optical parameters are obtained;

[0009] Based on the water body optical parameters, the lidar system parameters, the environmental transmission parameters and the filter transmission characteristics are integrated to construct a lidar signal simulation model considering the spectral aliasing effect;

[0010] The background light noise from the water body reflecting sunlight is incorporated into the laser radar signal simulation model to form a complete received signal model containing target signals, crosstalk signals and background light noise;

[0011] The ratio of the target channel exclusive signal to the complete received signal is taken as the target signal ratio of the filter bandwidth selection;

[0012] Based on the complete received signal model, a fixed chlorophyll concentration is set, the signal intensity corresponding to different filter bandwidths is simulated, and the signal intensity law is determined; the signal intensity law is the influence law of bandwidth on signal detectability;

[0013] In combination with the water body environment parameter range, the filter bandwidth range and the chlorophyll concentration range are set, the target signal ratio under different combination conditions is simulated, and the target signal ratio law is determined; the target signal ratio law is the synergistic influence law of bandwidth and water body environment on detection purity;

[0014] Based on the signal intensity law and the target signal ratio law, the signal intensity lower limit and the target signal ratio lower limit are set respectively, the filter bandwidth range that meets the requirements of both lower limits is screened out, and the maximum bandwidth in the filter bandwidth range is determined as the optimal filter bandwidth.

[0015] The second aspect of the present application provides a filter bandwidth selection device for a Raman-fluorescence laser radar, the device comprising an acquisition module, a construction module and a determination module;

[0016] The acquisition module is used to calculate the attenuation contribution of pure water and chlorophyll components in the water body to the laser signal under a set chlorophyll concentration by using a bio-optical model, and to acquire water body optical parameters;

[0017] The construction module is used to integrate laser radar system parameters, environmental transmission parameters and filter transmission characteristics based on the water body optical parameters to construct a laser radar signal simulation model considering spectral aliasing effect;

[0018] The construction module is also used to incorporate the background light noise from the water body reflecting sunlight into the laser radar signal simulation model to form a complete received signal model containing target signals, crosstalk signals and background light noise;

[0019] The determination module is used to take the ratio of the target channel exclusive signal to the complete received signal as the target signal ratio of the filter bandwidth selection;

[0020] The determination module is also used to set a fixed chlorophyll concentration based on the complete received signal model, simulate the signal intensity corresponding to different filter bandwidths, and determine the signal intensity law; the signal intensity law is the influence law of bandwidth on signal detectability;

[0021] The determination module is further configured to set a filter bandwidth range and a chlorophyll concentration range in combination with the water body environment parameter range, simulate a target signal proportion under different combinations, and determine a target signal proportion rule; the target signal proportion rule is a rule of the synergistic effect of the bandwidth and the water body environment on the detection purity.

[0022] The determination module is further configured to set a signal intensity lower limit and a target signal proportion lower limit based on the signal intensity rule and the target signal proportion rule, filter out a filter bandwidth range that meets the two lower limit requirements, and determine a maximum bandwidth in the filter bandwidth range as an optimal filter bandwidth.

[0023] The Raman-fluorescence laser radar filter bandwidth selection method and device provided by the application use a biological optical model to solve water body optical parameters, construct a simulation model considering spectral aliasing effects and incorporate background light noise, and simultaneously take into account the effects of spectral aliasing effects and background light noise on signals, making up for the defects of the prior art that only focuses on a single interference factor, completely restoring the real signal composition of "target signal + crosstalk signal + background light noise" in actual detection, avoiding the disconnection of bandwidth selection from the actual scene due to the neglect of any interference, making the subsequent simulation results and bandwidth filtering more credible; at the same time, taking the ratio of the target channel exclusive signal to the complete received signal as the target signal proportion, the interference of spectral aliasing and background light noise is converted into a quantifiable selection index, which not only intuitively reflects the purity of the target signal under different bandwidths, but also clearly presents the synergistic effect of bandwidth changes and water body environment (chlorophyll concentration) on the detection effect, solving the problem of the lack of a unified quantitative standard in traditional selection; on this basis, by setting a fixed chlorophyll concentration simulation signal intensity rule, setting a bandwidth and chlorophyll concentration range simulation target signal proportion rule, and then setting double lower limits to filter the bandwidth and selecting the maximum bandwidth in the range as the optimal solution, the selected bandwidth can meet the requirements of the system on signal detection (signal intensity meets the standard), and the detection purity (target signal proportion meets the standard) is also ensured, achieving a balance between signal intensity and detection accuracy, and providing a flexible and scientific guidance for laser radar system parameter selection, which is suitable for different detection systems and water body environment requirements. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A flowchart of the Raman-fluorescence laser radar filter bandwidth selection method provided by Embodiment One of the application;

[0025] Figure 2 A structural schematic diagram of the Raman-fluorescence laser radar filter bandwidth selection device provided by Embodiment Two of the application. DETAILED DESCRIPTION

[0026] The illustrative embodiments will be described with reference to the accompanying drawings, of which like elements are referred to by like reference numerals. The following detailed description is presented in terms of a number of examples, which are not intended to limit the scope of the application. The following detailed description is presented for the purpose of describing and enabling the examples.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0028] It should be understood that, although the terms first, second, third, etc. can be used herein to describe various information, the information should not be limited to these terms. These terms are only used to distinguish one piece of information from another. For example, a first information can also be termed a second information, and similarly, a second information can also be termed a first information without departing from the scope of the present application. Depending on the context, the word "if' as used herein can be interpreted as meaning "when" or "in response to determining" or "in response to ascertaining".

[0029] The following detailed description will describe specific embodiments of the application with reference to the accompanying drawings.

[0030] Figure 1 A flow chart of the method for selecting the filter bandwidth of the Raman-fluorescence laser radar according to Embodiment One of the present application is shown in FIG. 1. Please refer to Figure 1 The method provided by the present embodiment can include:

[0031] S101, using a bio-optical model, calculating the attenuation contribution of pure water and chlorophyll components to the laser signal in the water body under a set chlorophyll concentration, and obtaining water optical parameters.

[0032] Specifically, the bio-optical model refers to a mathematical model for calculating the contribution of water bodies to the attenuation of laser signals under a set chlorophyll concentration. The core is to quantify the optical parameters of water bodies by superimposing the optical properties of each component. The water body optical parameter refers to a physical quantity representing the ability of water bodies to absorb, scatter, attenuate, and backscatter laser signals, which is calculated by a bio-optical model. The core includes: water beam attenuation coefficient (quantifying the degree of energy attenuation per unit distance caused by absorption and scattering of laser), water absorption coefficient (representing the absorption ability of water to laser, which is superimposed by the absorption contribution of pure water and chlorophyll), water scattering coefficient (representing the scattering ability of water to laser, which is superimposed by the scattering contribution of pure water and chlorophyll), water total backscattering coefficient (quantifying the ability of unit volume of water to scatter laser to 180°, i.e., toward the radar receiver direction, including Raman and fluorescence backscattering coefficients), and water diffuse attenuation coefficient (representing the degree of energy attenuation per unit distance caused by diffuse transmission of laser).

[0033] Optionally, the set chlorophyll concentration range is 0.05-25 mg / m³. From the perspective of the authenticity of the marine environment, this concentration interval completely covers the common chlorophyll concentration range of global oceans. 0.05 mg / m³ corresponds to the background concentration level of low-nutrient salt sea areas such as open oceans, and 25 mg / m³ covers the high-concentration scenarios of eutrophic sea areas such as coastal areas, estuaries, and upwelling areas, which can simulate the water optical environment that may be encountered in most actual detection, ensuring the universality of the filter band selection result and avoiding the failure of the selection scheme in a specific sea area due to incomplete concentration coverage.

[0034] From the perspective of laser radar detection capability, the laser radar detection wavelength of the present application is 532 nm (blue-green waveband), which has good transmission characteristics in water bodies with a chlorophyll concentration of 0.05-25 mg / m³. At low concentrations, the signal attenuation is weak, and at high concentrations, although the attenuation is intensified, effective signals can still be captured by reasonable bandwidth selection; if the concentration is lower than 0.05 mg / m³, the optical properties of the water body tend to be close to pure water, the signal crosstalk and noise interference are extremely weak, and the bandwidth selection has little effect on the detection performance, so there is no need for additional optimization; if the concentration is higher than 25 mg / m³, the water beam attenuation coefficient will increase sharply, and the laser signal will be quickly absorbed and attenuated, making it difficult to obtain effective target signals even by adjusting the filter bandwidth, which exceeds the actual detection capability boundary of the laser radar system.

[0035] From the scope of application of the bio-optical model, the core logic of the bio-optical model used in the present application is to superimpose the optical properties (absorption, scattering coefficients) of pure water and chlorophyll to solve the overall optical parameters of the water body. The model has been verified to accurately quantify the attenuation contribution of the two within the range of 0.05-25 mg / m³; beyond this range, the optical influence of other components such as suspended solids, colored soluble organic matter, and other components in the water body will significantly increase, and the model simplification assumption will no longer hold, which will lead to a large error in the solution of the optical parameters of the water body, and further affect the accuracy of subsequent signal simulation and bandwidth selection.

[0036] In a specific implementation, the water optical parameters include water diffuse attenuation coefficient, water beam attenuation coefficient, and water total backscattering coefficient. The bio-optical model is used to solve the attenuation contribution of pure water and chlorophyll components in the water body under a given chlorophyll concentration to the laser signal, and to obtain the water optical parameters, including: based on the bio-optical model, respectively determining the pure water absorption coefficient, the chlorophyll absorption coefficient, and the pure water scattering coefficient, and the chlorophyll scattering coefficient; superimposing the pure water absorption coefficient and the chlorophyll absorption coefficient to obtain the total water absorption coefficient, and superimposing the pure water scattering coefficient and the chlorophyll scattering coefficient to obtain the total water scattering coefficient; adding the total water absorption coefficient and the total water scattering coefficient to obtain the water beam attenuation coefficient; extracting the water Raman backscattering coefficient and the chlorophyll fluorescence backscattering coefficient respectively, superimposing the two types of backscattering coefficients to obtain the total water backscattering coefficient at 180°; taking the water beam attenuation coefficient and the total water backscattering coefficient as the core basic parameters, combining the water radiation transmission characteristics corresponding to the laser radar detection wavelength, and obtaining the water diffuse attenuation coefficient through the correlation derivation of the bio-optical model.

[0037] Specifically, based on a bio-optical model with an applicable range of 0.05-25 mg / m³, the pure water absorption coefficient and the chlorophyll absorption coefficient corresponding to the laser radar detection wavelength (532 nm) are determined respectively, and the pure water scattering coefficient and the chlorophyll scattering coefficient are determined respectively; the determined pure water absorption coefficient and the chlorophyll absorption coefficient are added to obtain the total water absorption coefficient representing the overall absorption capacity of the water body, and the pure water scattering coefficient and the chlorophyll scattering coefficient are added to obtain the total water scattering coefficient representing the overall scattering capacity of the water body; then the calculated total water absorption coefficient and the total water scattering coefficient are added to obtain the water beam attenuation coefficient quantifying the overall attenuation degree of the water body to the laser signal due to absorption and scattering; then the Raman backscattering coefficient of water and the fluorescence backscattering coefficient of chlorophyll are extracted respectively, and the two types of backscattering coefficients are superimposed to obtain the total backscattering coefficient of the water body at 180° (the coefficient directly reflects the scattering contribution of the water body to the laser signal towards the radar receiver); finally, the water beam attenuation coefficient and the total water backscattering coefficient calculated before are taken as the core basic parameters, the water body radiation transmission characteristics corresponding to the 532 nm laser radar detection wavelength are combined, and the water body diffuse attenuation coefficient representing the diffuse transmission attenuation law of the laser signal in the water body is obtained through the correlation derivation of the bio-optical model, and finally the water body optical parameters including the water body diffuse attenuation coefficient, the water beam attenuation coefficient and the total water backscattering coefficient are obtained.

[0038] For example, in an embodiment, the calculation process of the water body optical parameters can be represented as:

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] wherein, is the water beam attenuation coefficient; is the water absorption coefficient; is the water scattering coefficient; is the water absorption coefficient at the wavelength ; is the pure water absorption coefficient at the wavelength ; is the pure water scattering coefficient at the wavelength the chlorophyll absorption coefficient at wavelength is the wavelength the water scattering coefficient at wavelength is the wavelength the pure water scattering coefficient at wavelength is the wavelength the chlorophyll scattering coefficient at wavelength is the coefficient related to wavelength is the coefficient related to wavelength is the water chlorophyll concentration is the index related to wavelength is the index related to wavelength is the water backscattering coefficient at wavelength is the index related to chlorophyll concentration is the index related to chlorophyll concentration is the water diffuse attenuation coefficient.

[0047] S102, based on the water optical parameters, integrating the laser radar system parameters, environmental transmission parameters and filter transmission characteristics, constructing a laser radar signal simulation model considering the spectral aliasing effect.

[0048] Specifically, the laser radar system parameters refer to the parameters related to the hardware and working settings of the Raman-fluorescence laser radar, which directly determine the basic ability of laser signal emission, transmission and reception, including: emission end parameters (laser emission energy, emission laser wavelength, emission optical efficiency), receiver parameters (receiver area, receiving optical efficiency, loss factor caused by telescope field of view), geometric parameters (working height, water refractive index, angle of transmission radiation incident to air-water interface and refraction angle).

[0049] The environmental transmission parameters refer to the parameters of the laser signal in the atmosphere-water transmission link affected by the external environment, which are used to quantify the energy attenuation in the signal transmission process, including: bidirectional atmospheric loss (atmospheric transmission loss of laser from the radar emission end to the water surface, and then reflected from the water surface to the receiving end), water surface transmission loss (energy loss caused by reflection and refraction when laser passes through the air-water interface, related to the incident angle and water refractive index), water optical parameters.

[0050] The filter transmittance characteristic refers to the selective transmittance degree of the filter to different wavelength optical signals, and is a key characteristic for distinguishing target signals and crosstalk signals. The transmittance function is quantified, and specifically includes: core parameters and a transmittance function. The core parameters include a filter full width at half maximum (FWHM, i.e., a bandwidth, determining a passband wavelength range), and a center wavelength (matching a target signal wavelength, such as a Raman signal or a fluorescence signal corresponding wavelength). The transmittance function is normally distributed with the center wavelength as a reference, and represents the proportion of different wavelength signals passing through the filter. The transmittance of the target wavelength signal is high, and the transmittance of non-target wavelengths (such as another channel crosstalk signal, background light) is low. The greater the bandwidth, the wider the wavelength range covered by the transmittance function, and the easier it is to introduce crosstalk signals. Conversely, the stronger the signal screening ability is, but the target signal strength may be reduced.

[0051] The spectral aliasing effect refers to a phenomenon that, when a Raman-fluorescence lidar dual-channel is detected, due to the overlap of the wavelength redistribution function curves of the Raman signal and the fluorescence signal, and the filter cannot completely isolate the non-target wavelength signal, the target signal is mixed into another channel signal when one channel receives the target signal. The lidar signal simulation model refers to a mathematical model for simulating the received signal of the Raman-fluorescence lidar, and the core purpose is to quantify the intensity relationship between the target signal and the crosstalk signal under different filter bandwidths.

[0052] In a specific implementation, the difference between the water beam attenuation coefficient and the water diffuse attenuation coefficient is multiplied by a natural exponential term, and the sum of the product and the water diffuse attenuation coefficient is determined as the attenuation coefficient of the lidar signal; wherein the natural exponential term is an exponential term related to the spot diameter of the lidar on the water surface; based on the standard deviation corresponding to the center wavelength and the full width at half maximum of the filter, a normal distribution function is used to construct a filter transmittance function; first, the convolution of the emission energy, the vacuum light speed, the bidirectional atmospheric loss, the receiver area, the optical efficiency, 1 minus the square of the water surface transmission loss, the loss factor caused by the telescope field of view, the total backscattering coefficient of the water, and the filter transmittance function are multiplied, and then the product result is multiplied by the natural exponential term, the natural exponential term is the integral of the attenuation coefficient of the lidar signal in the detection depth range divided by the inverse value of the cosine of the water detection angle, and finally the obtained result is sequentially divided by 2, the refractive index of water, the refractive index of water multiplied by the working height divided by the cosine of the detection angle, plus the detection depth divided by the cosine of the detection angle of water, to obtain the aliasing signal.

[0053] For example, in an embodiment, the process of constructing the lidar signal simulation model can be represented as:

[0054] ;

[0055] ;

[0056] ;

[0057] ;

[0058] wherein, is the attenuation coefficient of the lidar signal; is the diffuse attenuation coefficient of the water body; is the beam attenuation coefficient of the water body; is the corresponding spot diameter of the lidar on the water surface; is the receiver area; is the working height; is the receiving field of view; is the filter transmittance function; is the standard deviation corresponding to the full width at half maximum of the filter; is the wavelength of the received signal corresponding to the current channel; is the wavelength; is the aliasing signal received by the lidar at the detection depth ; is the emission energy of the Raman-fluorescence lidar system; is the propagation speed of light in vacuum; is the bidirectional atmospheric loss; and are the optical efficiencies of emission and reception, respectively; is the transmission loss through the water surface; is the loss factor caused by the field of view of the telescope; is the total backscattering coefficient at 180°, including the Raman backscattering coefficient of water (defined as ) and the fluorescence backscattering coefficient of chlorophyll (defined as ) corresponding to the target signal of the Raman channel and the fluorescence channel, respectively; is the refraction angle of light in the water medium according to Snell's law; is the refractive index of water; is the angle at which the transmitted radiation is incident to the air-water interface.

[0059] S103, background light noise derived from the reflection of sunlight by the water body is incorporated into the lidar signal simulation model to form a complete received signal model containing target signals, crosstalk signals and background light noise.

[0060] Specifically, the background light noise refers to the noise formed by the sunlight reflected by the water body in the actual ocean detection scene of the Raman-fluorescence lidar, which is a key environmental interference factor affecting the purity of the received signal of the lidar. Since the target signal (Raman / fluorescence signal) received by the Raman-fluorescence lidar itself is weak in intensity, and the background light noise formed by the sunlight has a high base, if the background light noise is not included in the lidar signal simulation model, the signal intensity obtained by simulation will be greatly different from the actual received signal, and the signal intensity may meet the detection threshold in simulation, but the signal-to-noise ratio is deteriorated due to the superposition of the background light noise, and the target signal is completely submerged, thereby reducing the detection accuracy. Moreover, the background light noise is related to the filter bandwidth (the greater the bandwidth, the wider the wavelength range allowed to pass through the filter, and the more the background light noise entering the receiving system), and if the correlation is ignored, only the bandwidth selected based on the spectral aliasing effect, there may be a problem of “excessive bandwidth leading to a sharp increase in background light noise” or “insufficient signal intensity due to insufficient bandwidth”, which cannot balance the relationship between signal intensity, signal purity and noise interference.

[0061] In a specific implementation, core parameters of the background light noise are determined; the core parameters include sunlight intensity reflected by the water body, a receiver shielding rate, a receiving field of view angle, and a receiving efficiency, a receiver area, and an atmospheric transmittance of the lidar system; the sunlight intensity reflected by the water body is multiplied by the atmospheric transmittance, the receiver area, 1 minus the square of the receiver shielding rate, the square of the tangent value of the half field of view angle of the receiver, and the optical efficiency of the receiver, and then combined with the transmittance characteristic of the filter to obtain a specific value of the background light noise; and the calculated background light noise value is included in the lidar signal simulation model to form a complete received signal model.

[0062] Specifically, first, core parameters required for calculating the background light noise are determined, including sunlight intensity reflected by the water body, a receiver shielding rate, a receiving field of view angle, and a receiving efficiency, a receiver area, and an atmospheric transmittance of the lidar system; then, the sunlight intensity reflected by the water body is multiplied by the atmospheric transmittance to obtain the noise base light intensity after atmospheric transmission, and then the result is multiplied by the receiver area, 1 minus the square of the receiver shielding rate (to correct the blocking effect of the shielding structure on the noise), the square of the tangent value of the half field of view angle of the receiver (a related calculation item converted based on the field of view angle characteristic), and the optical efficiency of the receiver, thereby obtaining a basic noise value without considering the transmittance characteristic of the filter; then, the transmittance characteristic of the filter is combined (that is, the transmittance characteristic of the filter is used to modify the basic noise value, and the transmittance characteristic of the filter is represented by a transmittance function and is related to the bandwidth and the center wavelength), and finally the specific value of the background light noise is calculated; and finally, the background light noise value is superimposed into the previously constructed lidar signal simulation model to obtain a complete received signal model.

[0063] For example, in an embodiment, the process of forming a complete received signal model can be represented as:

[0064] ;

[0065] ;

[0066] wherein, is background light noise; is sunlight reflected by the water body; is bidirectional atmospheric loss; is receiver area; is receiver obscuration; is received field of view angle; is received optical efficiency; is filter transmittance function, is standard deviation corresponding to full width at half maximum of the filter; is wavelength; is total received signal; is an aliasing signal received by the laser radar at a detection depth .

[0067] The method provided by the embodiment can truly restore the signal composition of "target signal + crosstalk signal + background light noise" in actual detection by calculating the background light noise and integrating it into a laser radar signal simulation model to obtain a complete received signal model, and can make up for the defects of the prior art of ignoring the background light noise, so that the signal intensity and target signal proportion data output by the model are consistent with the actual reception of the laser radar, and the bandwidth selection deviation caused by only considering the spectral aliasing effect is avoided. Based on the complete model, the target signal proportion (a core index for selection) under the combination of different filter bandwidths and chlorophyll concentrations can be accurately simulated subsequently, the contradictory relationship between the increase of the bandwidth and the background light noise and crosstalk is clearly presented, accurate quantitative basis for setting a reasonable lower limit of the signal intensity and target signal proportion is provided, and then an effective bandwidth range that meets the minimum detectable signal requirement of the system and guarantees the purity of the target signal is screened out, and finally the optimal bandwidth is determined, so that the selected bandwidth can balance the signal stability, detection accuracy and anti-interference ability in actual marine detection, truly adapts to the laser radar system parameters and actual detection environment, and provides scientific guidance for the optimization of the laser radar system parameters.

[0068] S104, taking the ratio of the target channel exclusive signal to the complete received signal as the target signal proportion for filter bandwidth selection.

[0069] Specifically, the target channel exclusive signal refers to a core signal expected to be captured by a specific receiving channel (Raman channel or fluorescence channel) of the Raman-fluorescence lidar, and specifically includes: the target channel exclusive signal of the Raman channel is a Raman signal corresponding to the Raman backscattering coefficient of water, and the target channel exclusive signal of the fluorescence channel is a fluorescence signal corresponding to the fluorescence backscattering coefficient of chlorophyll, which directly reflects the optical characteristics of the detection target and is not interfered by the signal of another channel. The complete receiving signal refers to the total signal received by the lidar in the actual detection scene, which is a total signal integrating the effective signal, the crosstalk signal and the environmental noise.

[0070] In a specific implementation, based on the lidar signal simulation model, a target channel exclusive signal type is determined; the target channel exclusive signal type includes an exclusive target signal of the Raman channel and an exclusive target signal of the fluorescence channel, the exclusive target signal of the Raman channel corresponds to the Raman backscattering of water contained in the total backscattering at 180° in the lidar signal simulation model, and the exclusive target signal of the fluorescence channel corresponds to the fluorescence backscattering of chlorophyll contained in the total backscattering; the composition of the complete receiving signal is determined in combination with the aliasing signal and the background light noise; the complete receiving signal is an aliasing signal and a background light noise; and the target signal proportion is obtained by calculating the intensity ratio of the target channel exclusive signal and the complete receiving signal.

[0071] Specifically, based on the constructed lidar signal simulation model, the type and corresponding source of the target channel exclusive signal are first determined, wherein the exclusive target signal of the Raman channel corresponds to the Raman backscattering of water contained in the total backscattering at 180° in the model, and the exclusive target signal of the fluorescence channel corresponds to the fluorescence backscattering of chlorophyll contained in the total backscattering; then the composition of the complete receiving signal is determined, and the aliasing signal (including the exclusive target signal of the Raman channel and the crosstalk signal of the fluorescence channel, or the exclusive target signal of the fluorescence channel and the crosstalk signal of the Raman channel) output by the model is superimposed with the background light noise calculated in the foregoing, and the superimposed signal is the complete receiving signal; finally, the intensities of the exclusive target signals of the Raman channel and the fluorescence channel and the corresponding intensities of the complete receiving signals are extracted, and the target signal proportions of the Raman channel and the fluorescence channel are obtained by calculating the intensity ratio of the exclusive target signal of the Raman channel and the corresponding complete receiving signal and the intensity ratio of the exclusive target signal of the fluorescence channel and the corresponding complete receiving signal.

[0072] For example, in an embodiment, the calculation process of the target signal proportion can be represented as:

[0073] ;

[0074] wherein, is the target signal proportion; is the intensity of the target channel exclusive signal, a target channel exclusive signal in the complete received signal; a backscattering coefficient corresponding to the target channel, a transmittance function of a current channel filter; a part of background light noise passing through the current channel filter, a base intensity of the background light noise, a backscattering coefficient corresponding to the emitted laser; an intensity of another channel crosstalk signal.

[0075] The method provided by the embodiment calculates the target signal proportion by the ratio of the target channel exclusive signal to the complete received signal, converts the spectral aliasing interference and the background light noise influence, which are originally difficult to quantify, into an intuitive and comparable index, completely restores the influence of the bandwidth change on the signal composition in actual detection, clearly presents the purity of the target signal in the form of the ratio, and lays a foundation for directly comparing the signal quality under different bandwidths and different chlorophyll concentrations; based on the index, simulation can accurately present the rules that "the larger the bandwidth, the lower the target signal proportion" and "the higher the chlorophyll concentration, the higher the target signal proportion in the fluorescence channel under the same bandwidth", provides a scientific basis for setting a reasonable lower limit of the target signal proportion, and then the lower limit of the signal intensity and the lower limit of the target signal proportion can be matched in the bandwidth screening, so that an effective bandwidth range that meets the minimum detectable signal requirement of the laser radar system and guarantees the detection accuracy is effectively screened out, and finally the optimal bandwidth is determined, so that the selected bandwidth balances the signal stability, the anti-interference ability and the detection accuracy in actual marine detection, and solves the problem that the bandwidth selection in the prior art is one-sided and cannot adapt to the actual detection requirement due to the lack of a comprehensive quantitative index, and provides reliable guidance for the parameter optimization of the laser radar system.

[0076] S105, based on the complete received signal model, setting a fixed chlorophyll concentration, simulating signal intensities corresponding to different filter bandwidths, and determining a signal intensity rule.

[0077] The signal intensity rule is a bandwidth influence rule on signal detectability.

[0078] Optionally, the set fixed chlorophyll concentration is 0.5 mg / m³, and the set range of the filter bandwidth is 5-50 nm.

[0079] Optionally, the filter bandwidth and the signal detectability have a positive correlation gradual change rule, when the bandwidth increases, the total amount of light signals passing through the filter increases, and the signal intensity improves; when the bandwidth decreases, the total amount of light signals passing through the filter decreases, and the signal intensity decreases.

[0080] Specifically, based on a complete received signal model including a target signal, a crosstalk signal and a background light noise, a fixed chlorophyll concentration (such as 0.5 mg / m³) is selected from an applicable concentration range of 0.05-25 mg / m³, laser radar system parameters (transmission energy, receiver area, transmission and reception optical efficiency, etc.), environmental transmission parameters (bidirectional atmospheric loss, water surface transmission loss, water refractive index, etc.) and background light noise related core parameters (water body reflected sunlight intensity, receiver shielding rate, receiving field of view angle, etc.) are kept unchanged, a filter bandwidth range (such as 5-50 nm) covering the actual application scenario is set, and a plurality of different bandwidth values (such as 5 nm, 10 nm, 15 nm, 20 nm, 30 nm and 50 nm) are selected at fixed intervals within the range; for each selected filter bandwidth value, the corresponding filter transmittance characteristic (standard deviation is calculated according to the bandwidth, and a transmittance function is constructed based on a normal distribution function) is combined and substituted into the complete received signal model for calculation to obtain the complete received signal intensity corresponding to each bandwidth value; after the signal intensity corresponding to all bandwidth values is calculated, all data are recorded and sorted, and the correlation data of different bandwidths and corresponding signal intensities are compared to summarize the influence law of the filter bandwidth on the signal detectability, that is, the received signal intensity increases with the increase of the filter bandwidth. The specific implementation process of the signal simulation can be referred to the description in the related art, which will not be repeated here.

[0081] In S106, the filter bandwidth range and the chlorophyll concentration range are set in combination with the water body environment parameter range, the target signal proportion under different combination conditions is simulated, and the target signal proportion law is determined.

[0082] The target signal proportion law is the cooperative influence law of the bandwidth and the water body environment on the detection purity.

[0083] Optionally, the detection purity is determined by the spectral screening ability of the bandwidth and the optical characteristics of the water body environment, and a narrow-band filter is matched in a first chlorophyll concentration water body environment, a wide-band filter is matched in a second chlorophyll concentration water body environment, and the first chlorophyll concentration is much greater than the second chlorophyll concentration.

[0084] Specifically, first, the water environment parameter range is determined, wherein the chlorophyll concentration range is set to 0.05-25 mg / m³ (covering low, medium and high concentration scenarios), and the filter bandwidth range (such as 5-50 nm, covering narrow bandwidth to wide bandwidth interval) is determined; then, multiple gradient concentration values (such as 0.05 mg / m³, 0.5 mg / m³, 5 mg / m³, 25 mg / m³) are selected from the set chlorophyll concentration range, and multiple gradient bandwidth values (such as 5 nm, 10 nm, 15 nm, 20 nm, 30 nm, 50 nm) are selected from the filter bandwidth range, forming multiple sets of combination conditions of "different bandwidth-different chlorophyll concentration"; for each set of combination conditions, based on the complete received signal model containing the target signal, the crosstalk signal and the background light noise, the water optical parameters (water beam attenuation coefficient, total backscatter coefficient, diffuse attenuation coefficient) under the corresponding chlorophyll concentration are first calculated by the bio-optical model, and then the target channel exclusive signal intensity and the complete received signal intensity are calculated in combination with the transmittance function (calculated according to the bandwidth standard deviation, based on the normal distribution function) corresponding to the filter bandwidth in the combination, and then the target signal proportion (detection purity related index) under the combination condition is obtained; after the target signal proportions of all combination conditions are calculated, all data are recorded and sorted, the data law is analyzed, and the synergistic influence law of bandwidth and water environment on detection purity is determined, for example, for the fluorescence channel, when narrow bandwidth filters (such as 5-10 nm) are matched in the first chlorophyll concentration (such as 25 mg / m³, high concentration) water environment, and wide bandwidth filters (such as 30-50 nm) are matched in the second chlorophyll concentration (such as 0.05 mg / m³, low concentration) water environment, the law of better detection purity.

[0085] S107, based on the signal intensity law and the target signal proportion law, the signal intensity lower limit and the target signal proportion lower limit are set respectively, the filter bandwidth range that meets the requirements of both lower limits is screened out, and the maximum bandwidth in the filter bandwidth range is determined as the optimal filter bandwidth.

[0086] Specifically, from the signal simulation results, the corresponding law of different filter bandwidths and signal strengths is extracted to determine the increasing trend of signal strength when the bandwidth increases and the signal strength distribution interval under different bandwidths; from the target signal proportion simulation results, the correlation law of filter bandwidth, chlorophyll concentration and target signal proportion is extracted to determine the decreasing trend of target signal proportion when the bandwidth increases and the proportion distribution interval under different bandwidth-chlorophyll concentration combinations; based on the signal strength law, combined with the minimum detection signal threshold of the laser radar system and the signal-to-noise ratio requirement of data processing, a lower limit value is set in the signal strength distribution interval; the lower limit value covers the lowest detection signal strength level under the set chlorophyll concentration; based on the target signal proportion law, combined with the actual detection accuracy requirement of signal purity, considering the worst case in the chlorophyll concentration range, a lower limit value is set in the proportion distribution interval; the signal strength and target signal proportion corresponding to all selected filter bandwidths are compared with the two set lower limits respectively, and all bandwidth values with signal strength not lower than the signal strength lower limit and target signal proportion not lower than the target signal proportion lower limit are selected to form the filter bandwidth range.

[0087] In specific implementation, first, from the completed signal simulation data, the complete received signal strength data corresponding to all selected filter bandwidths is extracted, and through sorting and analysis, it is clear that the signal strength presents an increasing trend when the filter bandwidth increases, and at the same time, the specific distribution interval of the signal strength corresponding to different bandwidths is accurately defined (for example, when the bandwidth is 5nm, the signal strength is in the interval of 1x10 -7 ~1x10 -5 W, when the bandwidth is 50nm, the signal strength is in the interval of 1x10 -6 ~1x10 -4 W); then, from the target signal proportion simulation data, the target signal proportion data corresponding to all filter bandwidth-chlorophyll concentration combinations is extracted, it is found that the target signal proportion presents a decreasing trend when the filter bandwidth increases, and the higher the chlorophyll concentration under the same bandwidth, the lower the target signal proportion, and then the distribution interval of the target signal proportion under different bandwidth-chlorophyll concentration combinations is determined (for example, for the Raman channel, when the bandwidth is 10nm and the chlorophyll concentration is 0.05mg / m³, the proportion is in the interval of 70%~75%, and when the bandwidth is 50nm and the chlorophyll concentration is 25mg / m³, the proportion is in the interval of 5%~10%); then, based on the increasing trend and distribution interval of the signal strength, combined with the minimum detection signal threshold of the laser radar system (such as 1x10 -15 W), the lowest detection signal strength level under the set chlorophyll concentration (such as the lowest detection signal strength is 1.4x10 -7 W when the set chlorophyll concentration is 0.5mg / m³) is referred to, and a reasonable signal strength lower limit value (such as 2x10 -7W); then based on the decreasing trend of the target signal ratio, the ratio distribution interval under different combinations, combined with the actual detection accuracy requirement of signal purity, fully considering the worst case in the range of chlorophyll concentration (for example, for the Raman channel, the scene of chlorophyll concentration is the highest value 25mg / m³), the appropriate lower limit value of the target signal ratio (such as 50%) is set in the target signal ratio distribution interval; finally, the signal intensity and target signal ratio data corresponding to all the selected filter bandwidths (such as 5nm, 10nm, 15nm, 20nm, 30nm, 50nm, etc.) are collected, and each selected bandwidth is compared one by one, both checking whether the signal intensity is not lower than the set signal intensity lower limit and verifying whether the target signal ratio is not lower than the set target signal ratio lower limit, and all the bandwidth values that meet the two conditions are selected, which together constitute the final filter bandwidth range (such as 10~15nm). Further, the maximum bandwidth (i.e. 15nm) in the filter bandwidth range is determined as the optimal filter bandwidth.

[0088] The method provided by the embodiment, in the first aspect, uses a biological optical model to calculate water optical parameters, constructs a simulation model considering the spectral aliasing effect and incorporates background light noise, and at the same time, the influence of the spectral aliasing effect and the background light noise on the signal is considered, which makes up for the defects of the prior art that only focuses on a single interference factor, completely restores the real signal composition of the actual detection "target signal + crosstalk signal + background light noise", avoids the disconnection between the bandwidth selection and the actual scene caused by ignoring any interference, and makes the subsequent simulation results and bandwidth selection more credible. In the second aspect, the ratio of the target channel exclusive signal to the complete received signal is taken as the target signal ratio, the interference of the spectral aliasing and the background light noise is converted into a quantifiable selection index, which not only directly reflects the purity of the target signal under different bandwidths, but also clearly presents the cooperative influence of the bandwidth change and the water environment (chlorophyll concentration) on the detection effect, and solves the problem of lacking a unified quantitative standard in the traditional selection; on this basis, by setting the simulation signal intensity law of the fixed chlorophyll concentration, setting the simulation target signal ratio law of the bandwidth and the chlorophyll concentration range, and then setting the double lower limit to filter the bandwidth and selecting the maximum bandwidth in the range as the optimal solution, both the selected bandwidth can meet the requirement of the system on the signal detection (the signal intensity meets the standard), and the detection purity (the target signal ratio meets the standard) is ensured, the balance between the signal intensity and the detection accuracy is realized, and a scientific guidance that can be flexibly adjusted is provided for the selection of the parameters of the laser radar system, which is suitable for different detection systems and water environment requirements.

[0089] Corresponding to the foregoing embodiment of the filter bandwidth selection method of the Raman-fluorescence laser radar, the present application also provides an embodiment of a filter bandwidth selection device of a Raman-fluorescence laser radar.

[0090] Figure 2A structure diagram of a filter bandwidth selection device of a Raman-fluorescence lidar is provided for Embodiment Two of the present application. Please refer to Figure 2 The device provided in the embodiment comprises an acquisition module 210, a construction module 220, and a determination module 230.

[0091] The acquisition module 210 is configured to use a bio-optical model to calculate the attenuation contribution of pure water and chlorophyll components to a laser signal in a water body with a set chlorophyll concentration, and to acquire water body optical parameters.

[0092] The construction module 220 is configured to integrate lidar system parameters, environmental transmission parameters, and filter transmission characteristics based on the water body optical parameters, and to construct a lidar signal simulation model considering spectral aliasing effects.

[0093] The construction module 220 is further configured to incorporate background light noise from water body reflected sunlight into the lidar signal simulation model, and to form a complete received signal model containing target signals, crosstalk signals, and background light noise.

[0094] The determination module 230 is configured to use the ratio of target channel exclusive signals to the complete received signals as the target signal ratio of filter bandwidth selection.

[0095] The determination module 230 is further configured to set a fixed chlorophyll concentration based on the complete received signal model, to simulate signal intensities corresponding to different filter bandwidths, and to determine a signal intensity law; the signal intensity law is a law of the influence of bandwidth on signal detectability.

[0096] The determination module 230 is further configured to set a filter bandwidth range and a chlorophyll concentration range in combination with a water body environmental parameter range, to simulate target signal ratios under different combination conditions, and to determine a target signal ratio law; the target signal ratio law is a law of the synergistic influence of bandwidth and water body environment on detection purity.

[0097] The determination module 230 is further configured to set a signal intensity lower limit and a target signal ratio lower limit based on the signal intensity law and the target signal ratio law, to screen out a filter bandwidth range that meets the requirements of both lower limits, and to determine the maximum bandwidth in the filter bandwidth range as the optimal filter bandwidth.

[0098] The device of the embodiment can be used to execute Figure 1 The steps of the method embodiment shown are similar in implementation principle and process to the above-described device, and thus will not be described here in detail.

[0099] The implementation processes of the functions and roles of each unit in the above-described device are specifically described in the implementation processes of the corresponding steps in the above-described method, and thus will not be described here in detail.

[0100] For the apparatus embodiment, since it basically corresponds to the method embodiment, the relevant part can be seen from the part of the method embodiment. The apparatus embodiment described above is only illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the application according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0101] The above only describes the preferred embodiments of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A filter bandwidth selection method for a Raman- fluorescence lidar, characterized by, The method comprises: Solving the attenuation contribution of pure water and chlorophyll component in water body to laser signal under the set chlorophyll concentration by using a bio-optical model to obtain water body optical parameters; Based on the water body optical parameters, integrating the laser radar system parameters, environmental transmission parameters and the light filter transmission characteristics to build a laser radar signal simulation model considering the spectral aliasing effect; The background light noise from the water body reflecting sunlight is included in the laser radar signal simulation model to form a complete received signal model containing target signal, crosstalk signal and background light noise; The ratio of target channel exclusive signal to complete received signal is used as the target signal ratio of light filter bandwidth selection; Based on the complete received signal model, the signal intensity corresponding to different light filter bandwidths is simulated under the condition of fixed chlorophyll concentration to determine the signal intensity law; the signal intensity law is the influence law of bandwidth on signal detection performance; Combined with the range of water body environmental parameters, the range of light filter bandwidth and the range of chlorophyll concentration are set to simulate the target signal ratio under different combination conditions to determine the target signal ratio law; the target signal ratio law is the synergistic influence law of bandwidth and water body environment on detection purity; Based on the signal intensity law and the target signal ratio law, the lower limit of signal intensity and the lower limit of target signal ratio are set respectively, and the light filter bandwidth range that meets the requirements of both lower limits is screened out, and the maximum bandwidth in the light filter bandwidth range is determined as the optimal light filter bandwidth.

2. The method of claim 1, wherein, The ratio of target channel exclusive signal to complete received signal is used as the target signal ratio of light filter bandwidth selection, which includes: Based on the laser radar signal simulation model, the type of target channel exclusive signal is determined; the target channel exclusive signal type includes the exclusive target signal of Raman channel and the exclusive target signal of fluorescence channel, the exclusive target signal of Raman channel corresponds to the Raman backscattering of water contained in the total backscattering at 180° in the laser radar signal simulation model, and the exclusive target signal of fluorescence channel corresponds to the fluorescence backscattering of chlorophyll contained in the total backscattering; Combined with the aliasing signal and the background light noise, the composition of complete received signal is determined; the complete received signal is the superposition signal of aliasing signal and background light noise; The target signal ratio is obtained by calculating the intensity ratio of target channel exclusive signal to complete received signal.

3. The method of claim 1, wherein, The background light noise from the water body reflecting sunlight is included in the laser radar signal simulation model, which includes: The core parameters of background light noise are determined; the core parameters include the intensity of sunlight reflected by water body, the shielding rate of receiver, the receiving field angle, and the receiving efficiency, the area of receiver, and the atmospheric transmittance of laser radar system; First, the intensity of sunlight reflected by water body is multiplied by the atmospheric transmittance, the area of receiver, 1 minus the square of the shielding rate of receiver, the square of the tangent value of the half field angle of receiver, and the optical efficiency of receiver, and then combined with the light filter transmission characteristics to obtain the specific value of background light noise; The calculated background light noise value is included in the laser radar signal simulation model to form a complete received signal model.

4. The method of claim 1, wherein, Based on the signal strength rule and the target signal proportion rule, a signal strength lower limit and a target signal proportion lower limit are set respectively, and a filter bandwidth range that meets the requirements of both lower limits is screened out, including: From the signal simulation results, the corresponding rules of different filter bandwidths and signal strengths are extracted, and the increasing trend of signal strength with increasing bandwidth and the signal strength distribution interval under different bandwidths are determined; From the target signal proportion simulation results, the correlation rule of filter bandwidth, chlorophyll concentration and target signal proportion is extracted, and the decreasing trend of target signal proportion with increasing bandwidth and the proportion distribution interval under different bandwidth-chlorophyll concentration combinations are determined; Based on the signal strength rule, combined with the minimum detection signal threshold of the laser radar system and the signal-to-noise ratio requirement of data processing, a lower limit value is set in the signal strength distribution interval; the lower limit value covers the lowest detection signal strength level under the set chlorophyll concentration; Based on the target signal proportion rule, combined with the actual detection accuracy requirement of signal purity, considering the worst case in the chlorophyll concentration range, a lower limit value is set in the proportion distribution interval; The signal strength and target signal proportion corresponding to all candidate filter bandwidths are compared with the two set lower limits respectively, and all bandwidth values with signal strength not lower than the signal strength lower limit and target signal proportion not lower than the target signal proportion lower limit are screened out to form a filter bandwidth range.

5. The method of claim 1, wherein, The water body optical parameters include water body diffuse attenuation coefficient, water body beam attenuation coefficient and water body total backscattering coefficient, and the attenuation contribution of pure water and chlorophyll components in the water body under the set chlorophyll concentration to the laser signal is calculated by using a bio-optical model to obtain the water body optical parameters, including: Based on the bio-optical model, the pure water absorption coefficient, the chlorophyll absorption coefficient, the pure water scattering coefficient and the chlorophyll scattering coefficient are determined respectively; The pure water absorption coefficient and the chlorophyll absorption coefficient are superimposed to obtain the total water absorption coefficient, and the pure water scattering coefficient and the chlorophyll scattering coefficient are superimposed to obtain the total water scattering coefficient; The total water absorption coefficient and the total water scattering coefficient are added to obtain the water body beam attenuation coefficient; The water Raman backscattering coefficient and the chlorophyll fluorescence backscattering coefficient are extracted respectively, and the two types of backscattering coefficients are superimposed to obtain the water body total backscattering coefficient at 180°; Taking the water body beam attenuation coefficient and the water body total backscattering coefficient as the core basic parameters, combined with the water body radiation transmission characteristics corresponding to the laser radar detection wavelength, the water body diffuse attenuation coefficient is obtained through the correlation derivation of the bio-optical model.

6. The method of claim 1, wherein, Based on the water body optical parameters, the laser radar signal simulation model considering the spectral aliasing effect is constructed by integrating the laser radar system parameters, environmental transmission parameters and filter transmittance characteristics, including: The product of the difference value of the water body beam attenuation coefficient and the water body diffuse attenuation coefficient and the natural exponential term is calculated, and the sum of the product and the water body diffuse attenuation coefficient is determined as the attenuation coefficient of the laser radar signal; wherein the natural exponential term is an exponential term about the spot diameter of the laser radar on the water surface; Based on the standard deviation corresponding to the set filter center wavelength and full width at half maximum, a normal distribution function is used to construct a filter transmittance function; The laser radar signal is obtained by multiplying the emission energy, the vacuum light speed, the bidirectional atmospheric loss, the receiver area, the optical efficiency, 1 minus the square of the water body surface transmission loss, the loss factor caused by the telescope field of view, the total backscattering coefficient of the water body and the convolution of the filter transmittance function, then multiplying the product result by the natural exponential term, the natural exponential term is the integral of the attenuation coefficient of the laser radar signal in the detection depth range divided by the inverse value of the cosine of the water detection angle, and finally dividing the obtained result by 2, the refractive index of water, the refractive index of water multiplied by the working height divided by the cosine of the detection angle plus the detection depth divided by the cosine of the detection angle of water to obtain the aliasing signal.

7. The method of claim 1, wherein, The filter bandwidth and the signal detectivity have a positive correlation gradient law, when the bandwidth increases, the total amount of light signals passing through the filter increases, and the signal strength improves, when the bandwidth decreases, the total amount of light signals passing through the filter decreases, and the signal strength decreases; The detection purity is jointly determined by the spectral screening ability of the bandwidth and the optical characteristics of the water environment, a narrow bandwidth filter is matched in a first chlorophyll concentration water environment, a wide bandwidth filter is matched in a second chlorophyll concentration water environment, and the first chlorophyll concentration is much larger than the second chlorophyll concentration.

8. The method of claim 1, wherein, The set chlorophyll concentration range is 0.05-25 mg / m³.

9. The method of claim 1, wherein, The set fixed chlorophyll concentration is 0.5 mg / m³, and the set range of the filter bandwidth is 5-50 nm.

10. A filter bandwidth selection device for a Raman- fluorescence lidar, characterized by The device comprises an acquisition module, a construction module and a determination module; The acquisition module is configured to use a biological optical model to calculate the attenuation contribution of pure water and chlorophyll components in a water body to a laser signal at a set chlorophyll concentration, and to acquire water optical parameters; The construction module is configured to integrate laser radar system parameters, environmental transmission parameters and filter transmittance characteristics based on the water optical parameters, and to construct a laser radar signal simulation model considering spectral aliasing effects; The construction module is further configured to include background light noise from water body reflected sunlight into the laser radar signal simulation model, and to form a complete received signal model comprising target signals, crosstalk signals and background light noise; The determination module is configured to use the ratio of target channel exclusive signals to the complete received signals as the target signal ratio of filter bandwidth selection; The determination module is further configured to set a fixed chlorophyll concentration based on the complete received signal model, to simulate signal intensities corresponding to different filter bandwidths, and to determine a signal intensity law; the signal intensity law is the influence law of bandwidth on signal detectivity; The determination module is further configured to set a filter bandwidth range and a chlorophyll concentration range in combination with a water environment parameter range, to simulate target signal ratios under different combination conditions, and to determine a target signal ratio law; the target signal ratio law is the cooperative influence law of bandwidth and water environment on detection purity; The determination module is further configured to set a signal intensity lower limit and a target signal ratio lower limit based on the signal intensity law and the target signal ratio law, to screen out a filter bandwidth range that meets the requirements of both lower limits, and to determine the maximum bandwidth in the filter bandwidth range as the optimal filter bandwidth.

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