Method, System, Device and Storage Medium for Inverting Diffuse Attenuation Coefficient of Water Body Based on Underwater Signals

Abstract

The present invention discloses a method, system, device and storage medium for inverting the diffuse attenuation coefficient of water based on underwater signals, belonging to the field of lidar remote sensing technology. The method includes obtaining lidar parameter data, measured lidar point cloud data of the target water area and target water area environment data; extracting underwater sounding points from the measured lidar point cloud data; calculating the underwater photon counting rate based on the underwater sounding points; calculating the effective water depth and the angle between the corrected underwater sounding point and the beam direction by correcting the water depth error of the underwater sounding points; constructing an underwater signal model based on the lidar parameter data, target water area environment data, underwater photon counting rate, effective water depth and the angle between the corrected underwater sounding point and the beam direction, and calculating the diffuse attenuation coefficient of the water body through the underwater signal model. The present invention calculates the diffuse attenuation coefficient of the water body through underwater sounding points, has strong anti-noise ability, and is beneficial to improving the monitoring accuracy of the water quality in the nearshore waters.

Description

Technical Field

[0001] The present invention belongs to the technical field of lidar remote sensing, and particularly relates to a method, system, device and storage medium for inverting the diffuse attenuation coefficient of water based on underwater signals. Background Art

[0002] Water quality monitoring plays a key role in evaluating the health of the marine environment, warning of pollution risks, and ensuring the sustainability of the marine ecosystem. As one of the core indicators for measuring water turbidity, the diffuse attenuation coefficient can effectively characterize the optical properties of seawater and provide important data support for in-depth research on the dynamic changes of the marine ecosystem. With the continuous improvement of the performance of water color sensors and the continuous growth of marine observation requirements, passive optical satellites have provided rich observation data and operational marine water color products globally. However, passive radiation measurement is restricted by the satellite orbit inclination and solar radiation, making it difficult to achieve full coverage of high-latitude regions and only able to obtain effective information during the day.

[0003] In contrast, active lidar has a reduced dependence on observation conditions and can well make up for the deficiencies of passive remote sensing. Existing algorithms for inverting the diffuse attenuation coefficient of water using photon counting lidar rely on the attenuation profile data of the water body. However, the water body signal point cloud is sparse and seriously interfered by system after-pulses and solar background noise, resulting in limitations in the application of existing algorithms in coastal waters. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, system, device and storage medium for inverting the diffuse attenuation coefficient of water based on underwater signals, which is applicable to water quality monitoring in coastal waters and helps to improve the accuracy of water quality monitoring in coastal waters.

[0005] The present invention provides the following technical solutions:

[0006] In the first aspect, a method for inverting the diffuse attenuation coefficient of water based on underwater signals is provided, including: obtaining lidar parameter data, lidar measured point cloud data of the target water area, and target water area environment data; extracting underwater sounding points according to the lidar measured point cloud data; calculating the underwater photon counting rate based on the underwater sounding points; calculating the effective water depth and the angle between the corrected underwater sounding point and the beam direction by correcting the water depth error of the underwater sounding points; constructing an underwater signal model based on the lidar parameter data, target water area environment data, underwater photon counting rate, effective water depth, and the angle between the corrected underwater sounding point and the beam direction, and calculating the diffuse attenuation coefficient of the water body through the underwater signal model.

[0007] As an alternative technical solution of the present invention, the lidar parameter data includes the quantum efficiency of the lidar detector, the lidar flight altitude, the lidar radiation correction coefficient, the optical efficiency of the lidar receiver, the laser frequency, and the effective area of the telescope; the target water area environment data includes the sea surface atmospheric pressure, the sea surface wind speed, and the aerosol optical thickness.

[0008] As an alternative technical solution of the present invention, extracting the underwater sounding points from the actually measured lidar point cloud data includes:

[0009] An ellipse is established with the photon point p as the center, and the distance between any photon point q and the ellipse center p is expressed as:

[0010]

[0011] where d(p,q) represents the distance between any photon point q and the ellipse center p, and r x represents the semi-major axis of the ellipse, and r y represents the semi-minor axis of the ellipse, x q , y q respectively represent the horizontal and vertical coordinate values of the photon point q, and x p , y p respectively represent the horizontal and vertical coordinate values of the ellipse center p;

[0012] When d(p,q) < 1, the photon point q is inside the ellipse, and the number of photon points inside the ellipse is used as the point cloud density N p of the ellipse center p, and the noise density N noise of the noise area is used as the extraction threshold for the signal point cloud;

[0013] The target water area is segmented according to a set distance, and the point cloud density of the ellipse center and its corresponding extraction threshold are statistically calculated for each segment. The ellipse center with a point cloud density higher than the extraction threshold is used as the signal point cloud;

[0014] The signal point cloud includes the water surface signal point cloud; the pulse width of the water surface signal point cloud is expressed as:

[0015]

[0016] where σ represents the pulse width of the water surface signal point cloud, and μ c represents the initial elevation value of the water surface signal point cloud, and μ t represents the position corresponding to the half decrease of the water surface peak;

[0017] The elevation range of the water surface signal point cloud is [μ c -3σ, μ c +3σ], and the signal point cloud with an elevation outside this range is used as the underwater sounding point.

[0018] As an alternative technical solution of the present invention, calculating the underwater photon counting rate includes:

[0019] Calculating the average number of pulsed photons N at the bottom of the water in each segment, c , expressed as:

[0020] N c = n c / W c ;

[0021] where n c represents the number of underwater sounding points, and W c represents the number of pulses;

[0022] The underwater photon counting rate is expressed as:

[0023] N b = N c - A;

[0024] where N b represents the underwater photon counting rate, and A represents the background noise rate.

[0025] As an alternative technical solution of the present invention, the effective water depth is expressed as:

[0026]

[0027] where z represents the effective water depth, z p represents the water depth before correction, n 1 represents the air refractive index, n 2 represents the water body refractive index, L m represents the mean sea level, and L c represents the current water level.

[0028] As an alternative technical solution of the present invention, calculating the angle between the corrected underwater sounding point and the light beam direction includes:

[0029] Segmenting the target water area according to a set distance, calculating the average coordinates (x i , y i ) of all the corrected underwater sounding points in each segment, and taking the angle between the tangent direction of the point (x i , y i ) and the vertical direction as the angle θ b between the corrected underwater sounding point and the light beam direction.

[0030] As an alternative technical solution of the present invention, the underwater signal model is expressed as:

[0031]

[0032] The diffuse attenuation coefficient of the water body is expressed as:

[0033]

[0034] where K d represents the diffuse attenuation coefficient of the water body, η q represents the quantum efficiency of the lidar detector, η r represents the optical efficiency of the lidar receiver, E t represents the single-pulse laser emission energy, A r represents the effective area of the telescope, n w represents the refractive index of the water body, h represents Planck's constant, υ represents the laser frequency, R h represents the flight altitude of the lidar, ρ bot represents the bottom reflectivity, z represents the effective water depth, K d represents the diffuse attenuation coefficient of the water body, F represents the lidar radiation correction coefficient, T w represents the attenuation coefficient when the light beam passes through the water surface, T a represents the attenuation coefficient when the light beam passes through the atmosphere, N b represents the bottom photon count rate, θ b represents the angle between the corrected bottom sounding point and the light beam direction;

[0035] The attenuation coefficient when the light beam passes through the water surface is expressed as:

[0036] T w =(1 - W)·(1 - ρ s );

[0037] where T w represents the attenuation coefficient when the light beam passes through the water surface, ρ s represents the white foam reflectivity, W represents the white foam ratio, U 10 represents the 10m wind speed over the sea surface;

[0038] The attenuation coefficient when the light beam passes through the atmosphere is expressed as:

[0039] T a = exp(-τ);

[0040] where T a represents the attenuation coefficient when the light beam passes through the atmosphere, τ represents the total optical thickness, τ = τ R + τ o3 + τ a τ R represents the Rayleigh optical thickness, τ o3 represents the ozone layer optical thickness, τ a represents the aerosol optical thickness;

[0041] The Rayleigh optical thickness τ R is expressed as:

[0042]

[0043] where P represents the sea surface atmospheric pressure, and P 0 represents the standard sea surface atmospheric pressure; τ R0 represents the Rayleigh optical thickness under the standard sea surface atmospheric pressure P 0 and λ represents the wavelength;

[0044] The ozone layer optical thickness τ o3 is expressed as:

[0045] τ O3 = χ(λ)·q;

[0046] where χ(λ) represents the ozone absorption coefficient and q represents the atmospheric ozone thickness.

[0047] In a second aspect, a system for inverting the diffuse attenuation coefficient of water based on underwater signals is provided, including: a data acquisition module for acquiring lidar parameter data, measured lidar point cloud data of a target water area, and target water area environment data;

[0048] an underwater sounding point extraction module for extracting underwater sounding points according to the measured lidar point cloud data;

[0049] an underwater photon counting rate calculation module for calculating the underwater photon counting rate based on the underwater sounding points;

[0050] a correction module for calculating the effective water depth and the angle between the corrected underwater sounding point and the beam direction by correcting the water depth error of the underwater sounding points;

[0051] a model construction module for constructing an underwater signal model based on the lidar parameter data, target water area environment data, underwater photon counting rate, effective water depth, and the angle between the corrected underwater sounding point and the beam direction, and calculating the diffuse attenuation coefficient of water through the underwater signal model.

[0052] In a third aspect, a device for inverting the diffuse attenuation coefficient of water based on underwater signals is provided, including a processor and a storage medium; the storage medium is used for storing instructions; the processor is used for operating according to the instructions to execute the steps of the method for inverting the diffuse attenuation coefficient of water based on underwater signals described in the first aspect.

[0053] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of the method for inverting the diffuse attenuation coefficient of water based on underwater signals described in the first aspect are implemented.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] A method for inverting the diffuse attenuation coefficient of water based on underwater signals provided by the present invention obtains the diffuse attenuation coefficient of water through the reflected signals of underwater sounding points, has strong anti-noise ability, and can be applied under the interference of strong solar background noise and system after-pulses; at the same time, this method is applicable to nearshore waters and helps to improve the water quality monitoring accuracy of nearshore waters. Description of the Drawings

[0056] Figure 1 is a flowchart of the method for inverting the diffuse attenuation coefficient of water based on underwater signals in the embodiments of the present invention;

[0057] Figure 2 is a result diagram of the extraction of underwater sounding points of the single-track sample data near Exmouth Gulf of ICESat-2 in the embodiments of the present invention;

[0058] Figure 3 is a result diagram of the inversion of the diffuse attenuation coefficient of water for 95-track data in the research area of Exmouth Gulf of ICESat-2 in the embodiments of the present invention. Detailed Embodiments

[0059] The present invention will be further described below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be used to limit the protection scope of the present invention.

[0060] Embodiment 1

[0061] This embodiment provides a method for inverting the diffuse attenuation coefficient of water based on underwater signals. As Figure 1 shown, the specific steps are as follows:

[0062] Step 1: Obtain lidar parameter data, lidar measured point cloud data of the target water area, and target water area environment data.

[0063] Specifically, the lidar parameter data includes the quantum efficiency of the lidar detector, the lidar flight altitude, the lidar radiation correction coefficient, the optical efficiency of the lidar receiver, the laser frequency, and the effective area of the telescope. The target water area environment data includes the sea surface atmospheric pressure, the sea surface wind speed, and the aerosol optical thickness.

[0064] In this embodiment, the lidar uses the new generation photon counting lidar ICESat-2, and the target water area is the waters of Exmouth Gulf. ICESat-2 is equipped with the photon counting lidar ATLAS, which can realize the measurement and recording at the single photon level, making it possible for the laser payload on the satellite platform to directly obtain the weak signal reflected from the water bottom. The wavelength of the ATLAS laser pulse is 532 nm. The laser pulse energy emitted by the laser is divided into three groups, each group contains a strong beam and a weak beam, and the interval between the strong and weak beams in the same group in the direction perpendicular to the orbital direction is 90 m.

[0065] In this embodiment, 95-track data of ICESat-2 flying over Exmouth Gulf from November 20, 2018 to October 22, 2022 are selected. The ICESat-2 ATL03 dataset provides the measured lidar point cloud data detected along the satellite flight trajectory (including specific time, longitude and latitude, elevation information, etc.), and the ATL09 dataset provides the environmental data of the target sea area, including the aerosol optical depth τ a , the sea surface atmospheric pressure P and the sea surface 10 m wind speed U 10

[0066] Step 2: Extract the water bottom sounding points according to the measured lidar point cloud data.

[0067] 2.1 Calculate the density value of the measured lidar point cloud.

[0068] Specifically, an ellipse is established with the photon point p as the center. Then the distance between any photon point q and the ellipse center p is expressed as:

[0069]

[0070] where d(p,q) represents the distance between any photon point q and the ellipse center p, r x represents the semi-major axis of the ellipse, r y represents the semi-minor axis of the ellipse, x q , y q respectively represent the horizontal and vertical coordinate values of the photon point q, and x p , y p respectively represent the horizontal and vertical coordinate values of the ellipse center p.

[0071] When d(p,q) < 1, the photon point q is inside the ellipse. The number of photon points inside the ellipse is used as the point cloud density N p of the ellipse center p, and the noise density N noise of the noise area is used as the extraction threshold of the signal point cloud.

[0072] 2.2 Extract the signal point cloud.

[0073] Segment the target water area according to the set distance, count the point cloud density of the ellipse center and its corresponding extraction threshold under each segment, and take the ellipse center with the point cloud density higher than the extraction threshold as the signal point cloud.

[0074] In this embodiment, segment according to the set distance of 100 m along the track, and construct an ellipse within each segment with the semi-major axis r x = 20 m and the semi-minor axis r y = 1 m.

[0075] 2.3. Extract the underwater sounding points.

[0076] The signal point cloud includes the water surface signal point cloud and the underwater signal point cloud. Affected by water attenuation, the density of the water surface signal point cloud is greater than that of the underwater signal point cloud. Therefore, the extracted signal point cloud is statistically analyzed by cumulative histogram according to elevation, where the elevation accumulation interval is selected as 0.015 m, and the elevation initial value μ c .

[0077] The pulse width of the water surface signal point cloud is expressed as:

[0078]

[0079] where σ represents the pulse width of the water surface signal point cloud, μ c represents the elevation initial value of the water surface signal point cloud, and μ t represents the position corresponding to the water surface peak dropping by half.

[0080] The elevation range of the water surface signal point cloud is [μ c - 3σ, μ c + 3σ], and the signal point cloud with an elevation not within this range is used as the underwater sounding point, that is, the underwater signal point cloud. Each segment along the track contains multiple underwater sounding points.

[0081] Step three: Calculate the underwater photon counting rate based on the underwater sounding points.

[0082] 3.1. Since the number of underwater sounding points is relatively small, to reduce the influence of random error on the result, segment according to the set distance of 100 m. Calculate the average number of underwater pulse photons N c in each segment, which is expressed as:

[0083] N c = n c / W c ;

[0084] where n c represents the number of underwater sounding points, and W c represents the number of pulses.

[0085] 3.2. The underwater photon counting rate is expressed as:

[0086] N b = N c - A;

[0087] where N b represents the underwater photon counting rate, and A represents the background noise rate. Due to the interference of background light noise, there is a large amount of random background light noise in the signal point cloud obtained by lidar during the day, which will contaminate the inversion result of the diffuse attenuation coefficient of water bodies. Therefore, it is necessary to subtract the background noise rate from the average number of pulsed photons at the bottom of the water.

[0088] In this embodiment, when the water depth is very shallow, the propagation distance of the laser in water is short, and the attenuation effect of the water body on the underwater signal is small, which may cause a large error in the inversion of the diffuse attenuation coefficient of the water body. Therefore, only the data with the underwater photon counting rate less than or equal to 1 is retained.

[0089] Step 4: Calculate the effective water depth and the angle between the corrected underwater sounding point and the beam direction by correcting the water depth error of the underwater sounding point.

[0090] 4.1. To obtain the effective water depth z, it is necessary to correct the water depth error of the underwater sounding point received by the lidar, that is, to correct the water body refraction effect and the fluctuation effect on the sea surface.

[0091] The effective water depth is expressed as:

[0092]

[0093] where z represents the effective water depth, z p represents the water depth before correction, n 1 represents the air refractive index, n 2 represents the water body refractive index, L m represents the mean sea level, L c represents the current water level.

[0094] As Figure 2 shown, the corrected underwater sounding point (represented as underwater photons in the figure) is shown.

[0095] 4.2. A steep underwater slope will cause the laser beam to deviate from the beam direction, and part of the laser may be scattered, thus deviating out of the receiving range of the lidar, resulting in a weakening or even loss of the laser echo signal. To ensure the effectiveness and integrity of the radiation information of the lidar reaching the bottom of the water, it is necessary to calculate the angle θ b between the beam and the seabed, and use it as the input for inverting the diffuse attenuation coefficient of the water body. The spatial coordinates of the corrected underwater sounding point are (x, y), where x is the along-track distance and y is the corrected water depth.

[0096] Segment the target water area according to the set distance of 100 m, and calculate the average coordinates (x i , y i ) of all the corrected underwater sounding points within each segment, and use the angle between the tangent direction and the vertical direction of the point (x i , y i ) as the angle θ between the corrected underwater sounding point and the beam direction b .

[0097] Step Five: Based on the lidar parameter data, the target water area environment data, the underwater photon counting rate, the effective water depth, and the angle between the corrected underwater sounding point and the beam direction, construct an underwater signal model, and calculate the diffuse attenuation coefficient of the water body through the underwater signal model.

[0098] 5.1. The underwater signal model is expressed as:

[0099]

[0100] where η q represents the quantum efficiency of the lidar detector, η r represents the optical efficiency of the lidar receiver, E t represents the single-pulse laser emission energy, A r represents the effective area of the telescope, n w represents the refractive index of the water body, h represents Planck's constant, υ represents the laser frequency, R h represents the lidar flight altitude, ρ bot represents the bottom reflectivity, z represents the effective water depth, K d represents the diffuse attenuation coefficient of the water body, F represents the lidar radiation correction coefficient, T w represents the attenuation coefficient when the beam passes through the water surface, T a represents the attenuation coefficient when the beam passes through the atmosphere, N b represents the underwater photon counting rate, and θ b represents the angle between the corrected underwater sounding point and the beam direction.

[0101] Furthermore, the attenuation coefficient when the beam passes through the water surface is expressed as:

[0102] T w =(1 - W)·(1 - ρ s );

[0103] where T w represents the attenuation coefficient when the beam passes through the water surface, ρ s represents the white foam reflectivity, which is 0.0205 at 532 nm. W represents the white foam ratio, which is calculated according to the sea surface 10 m wind speed U10 data and is expressed as:

[0104] Furthermore, the attenuation coefficient of the light beam passing through the atmosphere is expressed as:

[0105] T a = exp(-τ);

[0106] where T a represents the attenuation coefficient of the light beam passing through the atmosphere, τ represents the total optical thickness, τ = τ R + τ o3 + τ a , τ R represents the Rayleigh optical thickness, τ o3 represents the ozone layer optical thickness, τ a represents the aerosol optical thickness.

[0107] The Rayleigh optical thickness τ R , is expressed as:

[0108]

[0109] where P represents the sea surface atmospheric pressure, P 0 represents the standard sea surface atmospheric pressure, taken as 1013.25 hPa, τ R0 represents the Rayleigh optical thickness under the standard sea surface atmospheric pressure P 0 and takes 0.1112 at 532 nm, λ represents the wavelength.

[0110] The optical thickness τ o3 absorbed by the ozone layer, is expressed as:

[0111] τ O3 (λ) = χ(λ)·q;

[0112] where χ(λ) represents the ozone absorption coefficient, which is 0.065 cm -1 at 532 nm. q represents the atmospheric ozone thickness, taken as 0.3 cm.

[0113] 5.2. The diffuse attenuation coefficient of the water body is expressed as:

[0114]

[0115] where K d represents the diffuse attenuation coefficient of the water body, F = 0.52, n w = 1.333, R h = 500 km, η q = 0.15, η r = 0.4, v = 3e 8 / 532e -9 , A r = 0.41 m2 For the strong beam, E t = 9×10 7 . N b , z, θ b , T a , T w Obtained by calculation according to the foregoing steps, ρ bot The bottom reflectivity is 0.15.

[0116] In this embodiment, the 95-track data of the ICESat-2 spaceborne photon counting lidar flying over Exmouth Gulf and other relevant parameters are used to realize the inversion of the diffuse attenuation coefficient in the coastal waters. The diffuse attenuation coefficient inverted by ICESat-2 is compared and verified with the passive optical measurement data (obtained from the MODIS water color dataset). As Figure 3 shown, the horizontal axis is the ICESat-2 diffuse attenuation coefficient K d calculated according to this patent method, and the vertical axis is the MODIS diffuse attenuation coefficient K d . The root mean square error between the two is 0.060 m -1 , and the average relative difference is 31.9%, further indicating the feasibility of this method.

[0117] Embodiment 2

[0118] This embodiment provides a system for inverting the diffuse attenuation coefficient of water based on the bottom signal, including:

[0119] A data acquisition module for acquiring lidar parameter data, the measured lidar point cloud data of the target water area, and the target water area environment data.

[0120] A bottom sounding point extraction module for extracting bottom sounding points according to the measured lidar point cloud data.

[0121] A bottom photon counting rate calculation module for calculating the bottom photon counting rate based on the bottom sounding points.

[0122] A correction module for calculating the effective water depth and the angle between the corrected bottom sounding point and the beam direction by correcting the water depth error of the bottom sounding points.

[0123] A model construction module for constructing a bottom signal model based on the lidar parameter data, the target water area environment data, the bottom photon counting rate, the effective water depth, and the angle between the corrected bottom sounding point and the beam direction, and calculating the diffuse attenuation coefficient of the water through the bottom signal model.

[0124] Embodiment 3

[0125] This embodiment provides a device for inverting the diffuse attenuation coefficient of water based on underwater signals, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method for inverting the diffuse attenuation coefficient of water based on underwater signals described in Embodiment 1.

[0126] Embodiment 4

[0127] This embodiment provides a computer-readable storage medium with a computer program stored thereon, and when the program is executed by a processor, it implements the steps of the method for inverting the diffuse attenuation coefficient of water based on underwater signals described in Embodiment 1.

[0128] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0130] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide for implementing the specified functions in Figure 1One process or multiple processes and / or boxes Figure 1 Steps of the functions specified in one box or multiple boxes.

[0132] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for inverting water diffuse attenuation coefficient based on bottom signals, characterized in that: include: Obtain laser radar parameter data, laser radar measured point cloud data of target waters, and target waters environmental data; Extracting underwater sounding points according to the laser radar measured point cloud data; Calculating the bottom photon counting rate based on the bottom sounding point; By performing water depth error correction on the water bottom sounding point, the effective water depth and the angle between the corrected water bottom sounding point and the light beam direction are calculated; Based on the laser radar parameter data, target water environment data, underwater photon count rate, effective water depth and the corrected angle between the underwater sounding point and the light beam direction, an underwater signal model is constructed, and the water body diffuse attenuation coefficient is calculated through the underwater signal model; The step of extracting the underwater sounding points according to the laser radar measured point cloud data includes: An ellipse is established with the photon point p as the center, and the distance between any photon point q and the ellipse center p is expressed as: Among them, d(p,q) represents the distance between any photon point q and the center of the ellipse p, r x represents the semi-major axis of the ellipse, r y represents the semi-minor axis of the ellipse, x q ,y q Respectively represent the horizontal and vertical coordinate values ​​of the photon point q, x p ,y p Respectively represent the horizontal and vertical coordinate values ​​of the ellipse center p; When d(p,q)<1, the photon point q is located inside the ellipse, and the number of photon points inside the ellipse is taken as the point cloud density N at the center p of the ellipse. p , and the noise density N in the noise region noise As the extraction threshold of the signal point cloud; The target waters are segmented according to the set distance, the point cloud density of the ellipse center under each segment and its corresponding extraction threshold are counted, and the ellipse center with a point cloud density higher than the extraction threshold is taken as a signal point cloud; The signal point cloud includes a water surface signal point cloud; the pulse width of the water surface signal point cloud is expressed as: Among them, σ represents the pulse width of the water surface signal point cloud, μ c Represents the initial value of the elevation of the water surface signal point cloud, μ t Indicates the position corresponding to the drop of half of the peak water level; The elevation range of the water surface signal point cloud is [μ c -3σ,μ c +3σ], the signal point cloud whose elevation is not within this range is regarded as the bottom sounding point; The calculation of the corrected angle between the bottom sounding point and the light beam direction includes: The target water area is segmented according to the set distance, and the average coordinates (x i ,y i ), and point (x i ,y i ) The angle between the tangent direction and the vertical direction is taken as the corrected angle between the bottom sounding point and the beam direction θ b .

2. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 1 is characterized in that: The laser radar parameter data includes the laser radar detector quantum efficiency, the laser radar flight altitude, the laser radar radiation correction coefficient, the laser radar receiver optical efficiency, the laser frequency and the telescope effective area; The target water area environmental data include sea surface atmospheric pressure, sea surface wind speed and aerosol optical thickness.

3. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 1 is characterized in that: The calculating of the underwater photon counting rate comprises: Calculate the average number of pulse photons N under the water in each segment c , expressed as: N c =n c / W c ; Among them, n c Indicates the number of bottom sounding points, W c Indicates the number of pulses; The underwater photon count rate is expressed as: N b =N c -A; Among them, N b represents the underwater photon counting rate, and A represents the background noise rate.

4. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 1 is characterized in that: The effective water depth is expressed as: Where z represents the effective water depth, z p represents the water depth before correction, n1 represents the air refractive index, n2 represents the water refractive index, L m represents the mean sea level, L c Indicates the current water level.

5. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 1 is characterized in that: The underwater signal model is expressed as: The water body diffuse attenuation coefficient is expressed as: Among them, K d represents the water diffuse attenuation coefficient, η q represents the quantum efficiency of the lidar detector, η r represents the laser radar receiver optical efficiency, E t represents the single pulse laser emission energy, A r represents the effective area of ​​the telescope, n w represents the refractive index of water, h represents Planck's constant, υ represents the laser frequency, R h represents the flying altitude of the laser radar, ρ bot represents the bottom reflectivity, z represents the effective water depth, K d represents the water diffuse attenuation coefficient, F represents the laser radar radiation correction coefficient, T w It represents the attenuation coefficient of the light beam when it passes through the water surface, T a It represents the attenuation coefficient of the light beam when passing through the atmosphere, N b represents the underwater photon count rate, θ b Indicates the angle between the corrected bottom sounding point and the light beam direction; The attenuation coefficient of the light beam when passing through the water surface is expressed as: T w =(1-W)·(1-ρ s ); Among them, T w represents the attenuation coefficient of the light beam when it passes through the water surface, ρ s represents the white foam reflectivity, W represents the white foam ratio, U 10 Indicates the wind speed at 10m above sea level; The attenuation coefficient of the light beam when passing through the atmosphere is expressed as: T a =exp(-τ); Among them, T a represents the attenuation coefficient of the light beam when it passes through the atmosphere, τ represents the total optical thickness, τ = τ R +τ o3 +τ a , τ R is the Rayleigh optical thickness, τ o3 represents the optical thickness of the ozone layer, τ a represents the aerosol optical depth; The Rayleigh optical thickness τ R , expressed as: Where P represents the atmospheric pressure at sea surface, P0 represents the standard atmospheric pressure at sea surface; τ R0 represents the Rayleigh optical thickness at the standard atmospheric pressure P0 on the sea surface, and λ represents the wavelength; The optical thickness of the ozone layer τ o3 , expressed as: Where χ(λ) represents the ozone absorption coefficient and q represents the atmospheric ozone thickness.

6. A water diffuse attenuation coefficient inversion system based on bottom signals, characterized in that: include: A data acquisition module is used to obtain laser radar parameter data, laser radar measured point cloud data of the target water area, and target water area environment data; A bottom sounding point extraction module, used to extract the bottom sounding points according to the laser radar measured point cloud data; A water bottom photon counting rate calculation module, used to calculate the water bottom photon counting rate based on the water bottom sounding point; A correction module, used to calculate the effective water depth and the angle between the corrected bottom sounding point and the light beam direction by performing water depth error correction on the bottom sounding point; A model building module is used to build an underwater signal model based on the laser radar parameter data, target water environment data, underwater photon count rate, effective water depth, and the corrected angle between the underwater sounding point and the light beam direction, and calculate the water body diffuse attenuation coefficient through the underwater signal model; The step of extracting the underwater sounding points according to the laser radar measured point cloud data includes: An ellipse is established with the photon point p as the center, and the distance between any photon point q and the ellipse center p is expressed as: Among them, d(p,q) represents the distance between any photon point q and the center of the ellipse p, r x represents the semi-major axis of the ellipse, r y represents the semi-minor axis of the ellipse, x q ,y q Respectively represent the horizontal and vertical coordinate values ​​of the photon point q, x p ,y p Respectively represent the horizontal and vertical coordinate values ​​of the ellipse center p; When d(p,q)<1, the photon point q is located inside the ellipse, and the number of photon points inside the ellipse is taken as the point cloud density N at the center p of the ellipse. p , and the noise density N in the noise region noise As the extraction threshold of the signal point cloud; The target waters are segmented according to the set distance, the point cloud density of the ellipse center under each segment and its corresponding extraction threshold are counted, and the ellipse center with a point cloud density higher than the extraction threshold is taken as a signal point cloud; The signal point cloud includes a water surface signal point cloud; the pulse width of the water surface signal point cloud is expressed as: Among them, σ represents the pulse width of the water surface signal point cloud, μ c Represents the initial value of the elevation of the water surface signal point cloud, μ t Indicates the position corresponding to the drop of half of the peak water level; The elevation range of the water surface signal point cloud is [μ c -3σ,μ c +3σ], the signal point cloud whose elevation is not within this range is regarded as the bottom sounding point; The calculation of the corrected angle between the bottom sounding point and the light beam direction includes: The target water area is segmented according to the set distance, and the average coordinates (x i ,y i ), and point (x i ,y i ) The angle between the tangent direction and the vertical direction is taken as the corrected angle between the bottom sounding point and the beam direction θ b .

7. A device for inverting water diffuse attenuation coefficient based on bottom signals, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method for inverting the water diffuse attenuation coefficient based on the bottom signal according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for inverting the water body diffuse attenuation coefficient based on the bottom signal as described in any one of claims 1 to 5 are implemented.

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