Water body diffusion attenuation coefficient inversion method, system and device based on underwater signal and storage medium

Abstract

The invention discloses a water body diffusion attenuation coefficient inversion method, system and device based on an underwater signal, and a storage medium, and belongs to the technical field of laser remote sensing. The method comprises the following steps: acquiring laser radar parameter data, laser radar actual measurement point cloud data of a target water area and target water area environment data; extracting a water bottom sounding point according to the point cloud data measured by the laser radar; calculating a water bottom photon counting rate based on the water bottom sounding point; water depth error correction is carried out on the water bottom sounding point, and the effective water depth and the included angle between the corrected water bottom sounding point and the light beam direction are calculated; and constructing a water bottom signal model based on the laser radar parameter data, the target water area environment data, the water bottom photon counting rate, the effective water depth and the corrected included angle between the water bottom sounding point and the light beam direction, and calculating a water body diffusion attenuation coefficient through the water bottom signal model. The diffusion attenuation coefficient of the water body is calculated through the water bottom sounding point, the anti-noise capability is high, and the monitoring precision of the water quality of the near-shore water area can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser remote sensing, and in particular relates to a method, system, device and storage medium for inverting a water body diffuse attenuation coefficient based on a water bottom signal. Background Art

[0002] Water quality monitoring plays a key role in assessing the health of the marine environment, warning of pollution risks, and ensuring the sustainability of marine ecosystems. 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 marine ecosystems. With the continuous improvement of water color sensor performance and the continued growth in demand for ocean observations, passive optical satellites have provided rich observation data and operational ocean color products worldwide. However, passive radiation measurements are subject to the constraints of satellite orbit inclination and solar radiation, making it difficult to achieve comprehensive coverage of high-latitude areas, and effective information can only be obtained during the day.

[0003] In contrast, active lidar has a lower dependence on observation conditions and can make up for the shortcomings of passive remote sensing. The existing algorithms for inverting the diffuse attenuation coefficient of water bodies using photon counting lidar rely on the attenuation profile data of water bodies, but the water body signal point cloud is sparse and is seriously interfered by the system afterpulses and solar background noise, which limits the application of existing algorithms in nearshore waters. Summary of the invention

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

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

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

[0007] As an optional technical solution of the present invention, 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 environment data includes the sea surface atmospheric pressure, the sea surface wind speed and the aerosol optical thickness.

[0008] As an optional technical solution of the present invention, the extraction of underwater sounding points according to the laser radar measured 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] 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;

[0012] 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 area noise As the extraction threshold of signal point cloud;

[0013] 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;

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

[0015]

[0016] 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;

[0017] The elevation range of the water surface signal point cloud is [μ c -3σ,μ c +3σ], and the signal point cloud whose elevation is not within this range is taken as the bottom sounding point.

[0018] As an optional technical solution of the present invention, the calculation of the underwater photon count rate includes:

[0019] Calculate the average number of pulse photons N under the water in each segment c , expressed as:

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

[0021] Among them, n c Indicates the number of bottom sounding points, W c Indicates the number of pulses;

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

[0023] N b =N c -A;

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

[0025] As an optional 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, 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.

[0028] As an optional technical solution of the present invention, the calculation of the corrected angle between the bottom sounding point and the light beam direction includes:

[0029] 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 .

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

[0031]

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

[0033]

[0034] 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 it passes 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;

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

[0036] T w =(1-W)·(1-ρ s );

[0037] 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;

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

[0039] T a =exp(-τ);

[0040] 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 represents the Rayleigh optical thickness, τ o3 represents the optical thickness of the ozone layer, τ a represents the aerosol optical depth;

[0041] The Rayleigh optical thickness τR , expressed as:

[0042]

[0043] 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;

[0044] The optical thickness of the ozone layer τ o3 , 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 water diffuse attenuation coefficient inversion system based on underwater signals is provided, including: a data acquisition module for acquiring laser radar parameter data, laser radar measured point cloud data of a target water area, and target water area environment data;

[0048] A bottom sounding point extraction module, used to extract the bottom sounding points according to the laser radar measured point cloud data;

[0049] A water bottom photon counting rate calculation module, used to calculate the water bottom photon counting rate based on the water bottom sounding point;

[0050] 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;

[0051] The model building module is used to build an underwater signal model based on the lidar parameter data, target water environment data, underwater photon counting 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.

[0052] In a third aspect, a device for inverting the water diffuse attenuation coefficient based on bottom signals is provided, comprising 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 water diffuse attenuation coefficient based on bottom 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 water body diffuse attenuation coefficient based on the bottom signal described in the first aspect are implemented.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention provides a method for inverting the water diffuse attenuation coefficient based on underwater signals, which obtains the water diffuse attenuation coefficient by inverting the reflection signal of the underwater sounding point. The method has strong anti-noise ability and can be applied under the interference of strong solar background noise and system post-pulse. At the same time, the method is suitable for nearshore waters and helps to improve the accuracy of water quality monitoring in nearshore waters. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of a method for inverting a water body diffuse attenuation coefficient based on a bottom signal in an embodiment of the present invention;

[0057] Figure 2 is a diagram of the extraction results of the bottom bathymetric points of the single-track sample data of ICESat-2 near Exmouth Bay in an embodiment of the present invention;

[0058] Figure 3 This is a diagram of the inversion result of the water diffuse attenuation coefficient of the 95-track data of the ICESat-2 Exmouth Bay study area in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0060] Example 1

[0061] This embodiment provides a method for inverting the water diffuse attenuation coefficient based on the bottom signal. Figure 1 As shown, the specific steps include:

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

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

[0064] In this embodiment, the laser radar uses the new generation photon counting laser radar ICESat-2, and the target waters are the waters of Exmouth Bay. ICESat-2 is equipped with a photon counting laser radar ATLAS, which can measure and record the single photon level, making it possible for the laser payload of the satellite platform to directly obtain the weak signal reflected from the bottom of the water. The ATLAS laser pulse wavelength is 532nm, and 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 strong and weak beams of the same group are spaced 90m apart in the vertical orbit direction.

[0065] In this example, 95 tracks of ICESat-2 laser radar flying over Exmouth Bay from November 20, 2018 to October 22, 2022 are selected. The ICESat-2ATL03 dataset provides the laser radar measured point cloud data detected along the satellite flight track (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 thickness τ a , sea surface atmospheric pressure P and sea surface 10m wind speed U 10

[0066] Step 2: Extracting underwater sounding points based on the laser radar measured point cloud data.

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

[0068] Specifically, 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:

[0069]

[0070] 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 They respectively represent the horizontal and vertical coordinate values ​​of the ellipse center p.

[0071] 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 area noise As the extraction threshold of signal point cloud.

[0072] 2.2. Extract signal point cloud.

[0073] 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.

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

[0075] 2.3. Extract the bottom bathymetric points.

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

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

[0078]

[0079] 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 where the water surface peak drops 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 whose elevation is not within this range is regarded as the bottom sounding point, that is, the bottom signal point cloud. Each along-track segment contains multiple bottom sounding points.

[0081] Step 3: Calculate the underwater photon count rate based on the underwater sounding point.

[0082] 3.1. Since the number of underwater sounding points is relatively small, in order to reduce the impact of random errors on the results, the water is divided into sections according to the set distance of 100m. Calculate the average number of underwater pulse photons N in each section c , expressed as:

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

[0084] Among them, n c Indicates the number of bottom sounding points, W c Indicates the number of pulses.

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

[0086] N b =N c -A;

[0087] Among them, N b represents the photon count rate at the bottom of the water, 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 the lidar during the day, which will contaminate the inversion result of the water diffuse attenuation coefficient, so it is necessary to subtract the background noise rate from the average pulse photon number at the bottom of the water.

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

[0089] Step 4: By correcting the water depth error of the bottom sounding point, the effective water depth and the angle between the corrected bottom sounding point and the light beam direction are calculated.

[0090] 4.1. In order to obtain the effective water depth z, it is necessary to correct the water depth error of the bottom sounding points received by the lidar, that is, to correct the refraction effect of the water body and the wave 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, 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.

[0094] like Figure 2 As shown, the corrected bottom sounding points (represented as bottom photons in the figure) are displayed.

[0095] 4.2. The steep bottom slope will cause the laser beam to deviate from the beam direction. Part of the laser may be scattered, thus deviating from the receiving range of the laser radar, causing the laser echo signal to weaken or even be lost. In order to ensure the effectiveness and integrity of the radiation information reaching the bottom of the water by the laser radar, it is necessary to calculate the angle θ between the beam and the seabed. b , and used as the input for inverting the diffuse attenuation coefficient of the water body. The spatial coordinates of the corrected bottom sounding point are (x, y), where x is the distance along the track and y is the corrected water depth.

[0096] The target waters are segmented according to a set distance of 100 m, 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 .

[0097] Step 5: Construct an underwater signal model based on the lidar 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.

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

[0099]

[0100] Among them, 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.

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

[0102] T w =(1-W)·(1-ρ s );

[0103] Among them, T w represents the attenuation coefficient of the light beam when it passes through the water surface, ρ s It represents the white foam reflectivity, which is 0.0205 at 532nm. W represents the white foam ratio, which is calculated based on the wind speed U10 data at 10m above the sea surface and is expressed as:

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

[0105] T a =exp(-τ);

[0106] 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 represents the Rayleigh optical thickness, τ o3 represents the optical thickness of the ozone layer, τ a represents the aerosol optical depth.

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

[0108]

[0109] Among them, P represents the atmospheric pressure at sea surface, P0 represents the standard atmospheric pressure at sea surface, which is 1013.25hpa, τ R0 It represents the Rayleigh optical thickness at the standard atmospheric pressure P0 on the sea surface, which is 0.1112 at 532nm, and λ represents the wavelength.

[0110] The optical thickness of the ozone layer absorption τ o3 , expressed as:

[0111] τ O3 (λ) = χ(λ)·q;

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

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

[0114]

[0115] Among them, K d Indicates the water diffuse attenuation coefficient, F = 0.52, n w =1.333, R h =500km,η q =0.15,η r =0.4, v = 3e 8 / 532e -9 , A r =0.41m 2 For strong beams, E t =9×107 . N b , z, θ b , T a , T w According to the above steps, we can calculate and obtain bot The bottom reflectivity is 0.15.

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

[0117] Example 2

[0118] This embodiment provides a water diffuse attenuation coefficient inversion system based on bottom signals, including:

[0119] The data acquisition module is used to obtain the laser radar parameter data, the laser radar measured point cloud data of the target water area and the target water area environment data.

[0120] The underwater sounding point extraction module is used to extract the underwater sounding points according to the laser radar measured point cloud data.

[0121] The underwater photon counting rate calculation module is used to calculate the underwater photon counting rate based on the underwater sounding point.

[0122] The correction module is used to calculate the effective water depth and the angle between the corrected bottom depth measuring point and the light beam direction by performing water depth error correction on the bottom depth measuring point.

[0123] The model building module is used to build an underwater signal model based on the lidar parameter data, target water environment data, underwater photon counting 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.

[0124] Example 3

[0125] This embodiment provides a device for inverting the water diffuse attenuation coefficient based on bottom 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 water diffuse attenuation coefficient inversion method based on bottom signals described in Example 1.

[0126] Example 4

[0127] This embodiment provides a computer-readable storage medium on which a computer program is stored. 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 described in Embodiment 1 are implemented.

[0128] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt 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.) that contain computer-usable program code.

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

[0130] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0132] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection 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; An underwater signal model is constructed based on the lidar parameter data, target water environment data, underwater photon counting rate, effective water depth and the corrected angle between the underwater sounding point and the light beam direction, and the water body diffuse attenuation coefficient is calculated through the underwater signal model.

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 method 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], and the signal point cloud whose elevation is not within this range is taken as the bottom sounding point.

4. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 3 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.

5. 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.

6. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 3 is characterized in that: 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. The method for inverting the water diffuse attenuation coefficient based on the bottom signal according to claim 1, 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: t O3 =x(λ)·q; Where χ(λ) represents the ozone absorption coefficient and q represents the atmospheric ozone thickness.

8. 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; The model building module is used to build an underwater signal model based on the lidar parameter data, target water environment data, underwater photon counting 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.

9. 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 7.

10. 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 7 are implemented.

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