Atmospheric visibility calculation method

Abstract

The invention discloses an atmospheric visibility calculation method, and relates to the field of environmental monitoring, and the method comprises the steps: inputting a laser radar echo signal containing multiple scattering photons and single scattering photons into a time convolution network, and obtaining an apparent extinction coefficient; obtaining an initial scattering free path of photons during first iteration according to the apparent extinction coefficient, and performing multiple scattering simulation based on the initial scattering free path, the initial transmission direction and the initial transmission position during the first iteration to obtain an initial multiple scattering factor and an initial simulation photon number; when the error between the theoretical photon number and the initial simulation photon number is larger than a preset threshold value, multiple times of scattering simulation are conducted again through the initial scattering free path, the initial transmission position and the initial transmission direction of photons during second iteration till a target multiple scattering factor and a target simulation photon number are obtained; and obtaining the atmospheric visibility through an actual extinction coefficient determined by the apparent extinction coefficient and the target multiple scattering factor. According to the invention, the visibility detection precision under complex atmospheric conditions is improved.

Description

Technical Field

[0001] The invention relates to the field of environmental monitoring, and relates to but is not limited to an atmospheric visibility calculation method. Background Art

[0002] Accurate measurement of atmospheric visibility is directly related to flight safety, traffic efficiency, and environmental quality assessment. For example, in the aviation field, visibility is an important parameter that determines flight conditions; in transportation, low visibility may lead to serious traffic accidents; in environmental monitoring, changes in visibility reflect the concentration and distribution of aerosol particles in the atmosphere. As a tool with high precision, strong real-time performance, and a wide detection range, lidar has become an important technical means for visibility measurement. It can quickly provide information on atmospheric transparency under complex meteorological conditions, providing strong support for environmental monitoring in various scenarios.

[0003] In the related technology, the extinction coefficient is obtained through the direct inversion method, and then the atmospheric visibility is calculated. However, the signal received by the lidar is significantly affected by multiple scattering. The result of direct inversion is the apparent extinction coefficient rather than the actual extinction coefficient, which will lead to the problem of low visibility detection accuracy under complex atmospheric conditions.

[0004] Therefore, how to improve the visibility detection accuracy under complex atmospheric conditions has become an urgent problem to be solved. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides an atmospheric visibility calculation method, which at least solves the problem of low visibility detection accuracy under complex atmospheric conditions in related technologies.

[0006] According to a first aspect of an embodiment of the present invention, there is provided a method for calculating atmospheric visibility, comprising:

[0007] Inputting the received laser radar echo signal into the time convolution network to obtain the apparent extinction coefficient; the laser radar echo signal includes multiple scattered photons and single scattered photons;

[0008] Obtaining a first initial scattering free path of photons in a first iteration according to the apparent extinction coefficient, and performing multiple scattering simulation based on the first initial scattering free path, the obtained first initial transmission direction and the first initial transmission position to obtain an initial multiple scattering factor and an initial simulated photon number; the photons are generated by a laser radar;

[0009] Acquire a theoretical number of photons based on the laser radar echo signal, and when an error between the theoretical number of photons and the initial simulated number of photons is greater than a preset threshold, acquire a second initial scattering free path, a second initial transmission position, and a second initial transmission direction of the photons in a second iteration;

[0010] performing multiple scattering simulation again based on the second initial scattering free path, the second initial transmission position, and the second initial transmission direction until a target multiple scattering factor and a target simulated photon number are obtained; and an error between the target simulated photon number and the theoretical photon number is not greater than the preset threshold;

[0011] An actual extinction coefficient is determined based on the apparent extinction coefficient and the target multiple scattering factor, and atmospheric visibility is acquired based on the actual extinction coefficient.

[0012] According to a second aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; the memory is used to store at least one executable instruction, wherein the executable instruction enables the processor to perform an operation corresponding to the method described in the first aspect.

[0013] According to a third aspect of an embodiment of the present invention, there is provided a computer storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first aspect is implemented.

[0014] According to the solution provided by the embodiment of the present invention, the received laser radar echo signal is input into the time convolution network to obtain the apparent extinction coefficient; the laser radar echo signal includes multiple scattered photons and single scattered photons; the received laser radar echo signal is input into the time convolution network to obtain the apparent extinction coefficient, thereby ensuring the accuracy and stability of the estimation of the apparent extinction coefficient. The first initial scattering free path of the photon at the first iteration is obtained according to the apparent extinction coefficient, and multiple scattering simulation is performed based on the first initial scattering free path, the obtained first initial transmission direction and the first initial transmission position to obtain the initial multiple scattering factor and the initial simulated photon number; the photon is generated by the laser radar. The theoretical number of photons is obtained based on the laser radar echo signal, and when the error between the theoretical number of photons and the simulated number of photons is greater than the preset threshold, the second initial scattering free path, the second initial transmission position and the second initial transmission direction of the photons are obtained in the second iteration; multiple scattering simulation is performed again based on the second initial scattering free path, the second initial transmission position and the second initial transmission direction until the target multiple scattering factor and the target simulated number of photons are obtained; the error between the target simulated number of photons and the theoretical number of photons is not greater than the preset threshold; the actual extinction coefficient is determined based on the apparent extinction coefficient and the target multiple scattering factor. This process is iterated continuously until the error is less than the set threshold. Through the precise iterative solution of multiple scattering, the calculation accuracy of the actual extinction coefficient is improved. Atmospheric visibility is obtained based on the actual extinction coefficient, which improves the visibility detection accuracy under complex atmospheric conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0016] Figure 1 A schematic diagram of a flow chart of an atmospheric visibility calculation method provided by an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of the effect of a temporal convolutional network provided by an embodiment of the present invention;

[0018] Figure 3 A schematic diagram of the effect of multiple scattering provided by an embodiment of the present invention;

[0019] Figure 4 is the scattering diagram when the first initial transmission direction is along the positive direction of the z-axis;

[0020] Figure 5 A schematic diagram of the changing trend of the total number of simulated photons and the number of single scattered photons provided by an embodiment of the present invention;

[0021] Figure 6 A schematic diagram showing the effects of different methods for calculating the apparent extinction coefficient provided by the embodiments of the present invention;

[0022] Figure 7 A schematic diagram of the effect of the change trend of the multiple scattering factor provided by an embodiment of the present invention;

[0023] Figure 8 A schematic diagram of the effect of the iteration of the laser radar echo signal provided by an embodiment of the present invention;

[0024] Fig. 9 A schematic diagram of the effect of actual extinction coefficient obtained by different methods is provided for the embodiment of the present invention;

[0025] Fig.10 A schematic diagram of the effect of simulating a laser radar echo signal provided in an embodiment of the present invention;

[0026] Fig.11 A schematic diagram of the effect of the apparent extinction coefficient obtained by different methods provided in the embodiments of the present invention;

[0027] Fig.12 A schematic diagram showing the effect of a simulated laser radar echo signal approaching a theoretical value provided by an embodiment of the present invention;

[0028] Fig.13 A schematic diagram showing the effect of the multiple scattering factor provided by an embodiment of the present invention approaching the theoretical value;

[0029] Fig.14 A schematic diagram of the effect of actual extinction coefficient obtained by different methods provided in the embodiments of the present invention;

[0030] Fig.15 A schematic diagram of the effect of actual extinction coefficient obtained by different methods provided in the embodiments of the present invention;

[0031] Fig.16 A schematic diagram showing the effects of comparing and analyzing the measured signals of group A using different methods provided in an embodiment of the present invention;

[0032] Fig.17 A schematic diagram showing the effects of comparing and analyzing the measured signals of group B using different methods provided in an embodiment of the present invention;

[0033] Fig.18 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0036] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0037] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the field to which the embodiments of the present invention belong. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0038] Figure 1 A flow chart of an atmospheric visibility calculation method provided in an embodiment of the present invention. The atmospheric visibility calculation method provided in an embodiment of the present invention can be executed by an electronic device, and the electronic device can be, for example, a computer, a server, etc.

[0039] like Figure 1 As shown, the atmospheric visibility calculation method includes:

[0040] S101. Input the received laser radar echo signal into a time convolution network to obtain an apparent extinction coefficient; the laser radar echo signal includes multiply scattered photons and single scattered photons.

[0041] In an embodiment of the present invention, the laser radar measures the environment by emitting laser light and receiving the light signal scattered back after reflection. Ideally, it should only receive photons directly scattered back from the target, that is, single scattered photons, but in reality, especially under complex atmospheric conditions such as fog and haze, some laser light will be scattered multiple times and eventually return to the laser radar, but they bring additional and inaccurate information, so the laser radar echo signal obtained ultimately contains the contribution of multiple scattering, and the direct inversion only obtains the apparent extinction coefficient, not the actual extinction coefficient.

[0042] In an embodiment of the present invention, in complex weather, the lidar echo signal received by the laser receiver contains multiple scattered photons and single scattered photons. The lidar echo signal is input into a trained time convolutional network to obtain an apparent extinction coefficient, which is a parameter used to measure the absorption and scattering effects of particulate matter in the air on light.

[0043] In an embodiment of the present invention, Figure 2 As shown, Figure 2 A schematic diagram of the effect of a temporal convolutional network provided by an embodiment of the present invention, in Figure 2In the , the temporal convolutional network (TCN) includes an input layer, two stacks and a fully connected layer. The two stacks are divided into the first stack and the second stack. The first stack includes the first temporal convolution layer, the second temporal convolution layer, and the third temporal convolution layer. The second stack includes temporal convolution layer 1, temporal convolution layer 2, and temporal convolution layer 3. Among them, the input layer is connected to the first temporal convolution layer, the first temporal convolution layer is connected to the second temporal convolution layer, the second temporal convolution layer is connected to the third temporal convolution layer, the third temporal convolution layer is connected to convolution layer 1, convolution layer 1 is connected to convolution layer 2, convolution layer 2 is connected to convolution layer 3, and convolution layer 3 is connected to the fully connected layer. The regression prediction task of the time series is completed by gradually transferring features between the layers.

[0044] Furthermore, the input layer receives time series data of shape (5, 1), where each sample represents five consecutive lidar echo signal measurements, each measurement corresponds to a time point, and each time step has only one feature value, such as echo intensity or distance information. The input data is first convolved through the first time convolution layer of the first stack, using 64 convolution kernels, a convolution kernel size of 2, and a dilation rate of 1. In order to achieve causal convolution and keep the output length unchanged, a zero padding is added to the time dimension before the convolution operation, and the input shape is padded from 64×5 to 64×6. After convolution, the output shape remains 64×5. Next, the output of the first time convolution layer of the first stack is passed to the second time convolution layer, which still uses 64 convolution kernels and a dilation rate of 1. At this time, another zero is padded before the convolution, and the shape is padded from 64×5 to 64×6. After convolution, the output shape is still 64×5. The third temporal convolution layer uses 64 convolution kernels, the dilation rate is increased to 2, and two zeros are padded before the convolution, the shape is padded from 64×5 to 64×7. After the dilated convolution, the output shape remains 64×5, further expanding the receptive field to capture medium-term temporal dependencies. Finally, the output of the third temporal convolution layer is passed to the first temporal convolution layer of the second stack, which uses 64 convolution kernels, the dilation rate is increased to 4, and four zeros are padded before the convolution, the shape is padded from 64×5 to 64×9. After the convolution, the output shape remains 64×5, further capturing long-term temporal dependencies. After completing the three-layer TCN processing of the first stack, the output shape remains 64×5 and is passed to the second stack. The structure and operation of the second stack are exactly the same as the first stack. It is processed by three layers of temporal convolution layers. In the process, zeros are padded to 64×6, 64×7, and 64×9 in turn according to the dilation rate, and the final output shape is still 64×5. The final output of the second stack is passed to the fully connected layer, which maps the 64×5 feature to a scalar value, representing the estimated result of the middle time step (the third time step) of the five time steps in the input sequence. By adding an appropriate amount of zero padding according to the dilation rate before each layer of convolution (1 padding for dilation rate 1, 2 padding for dilation rate 2, and 4 padding for dilation rate 4), the model ensures that the output length of each layer is always kept at 64×5, thereby effectively capturing the time-dependent features from short-term to long-term by using multiple layers of dilated convolution while maintaining causality, and ultimately achieving accurate prediction of the intermediate time steps.

[0045] For example, Figure 3 As shown, Figure 3 A schematic diagram of the effect of multiple scattering provided by an embodiment of the present invention. Figure 3 In the process, the laser beam emitted by the lidar will be scattered when it interacts with the air particles in the air. Some of the backscattered photons will be received, including single backscattered photons and multiple backscattered photons.

[0046] S102. Obtain the first initial scattering free path of photons in the first iteration according to the apparent extinction coefficient, and perform multiple scattering simulation based on the first initial scattering free path, the obtained first initial transmission direction and the first transmission position to obtain an initial multiple scattering factor and an initial simulated photon number; the photons are generated by a laser radar.

[0047] In an embodiment of the present invention, the scattering free path refers to the distance from the emission point to the first scattering point when the photon propagates in the medium. Multiple scattering simulation refers to the process of simulating multiple scattering of photons with medium particles when the photons propagate in the medium. The initial multiple scattering factor and the initial simulated photon number refer to the multiple scattering factor and the simulated photon number obtained from the laser receiver after the first iteration. In the multiple scattering simulation, due to the lack of the actual extinction coefficient, the apparent extinction coefficient estimated by the time convolution network is used to determine the first initial scattering free path, and the first initial transmission direction can be set to [0,0,1], and the first initial transmission position can be obtained according to formula (2), and multiple scattering simulation is performed on the first initial scattering free path, the first initial transmission position and the first initial transmission direction to complete the first iteration of the photon. After the iteration is completed, the initial multiple scattering factor and the initial simulated photon number can be obtained through the laser receiver.

[0048] In an embodiment of the present invention, the cross-sectional light intensity of photons generated by the laser radar is determined by the following formula (2):

[0049]

[0050] In the above formula (2), E is the cross-sectional light intensity of the photon; E0 is the maximum light intensity at the center point of the photon; a is the distance between the center point of the photon and the center of the circle; w is the standard deviation of the photon; and the initial propagation direction of the photon is set to be consistent with the laser transmission axis.

[0051] S103, obtaining a theoretical number of photons based on the laser radar echo signal, and when the error between the theoretical number of photons and the initial simulated number of photons is greater than a preset threshold, obtaining a second initial scattering free path, a second initial transmission position, and a second initial transmission direction of the photons in a second iteration.

[0052] In the embodiments of the present invention, the theoretical number of photons generally refers to the number of photons predicted or calculated under a certain theoretical model or assumption. The theoretical number of photons is obtained by receiving the laser radar echo signal, and the error between the theoretical number of photons and the simulated number of photons is calculated. When the error is greater than a preset threshold, the photons are iterated for the second time to obtain the second initial scattering free path, the second initial transmission position and the second initial transmission direction of the photons at the second iteration. The second initial scattering free path, the second initial transmission position and the second initial transmission direction are obtained in the same manner as the first simulation, and the photons are a large number of photons.

[0053] S104, performing multiple scattering simulation again based on the second initial scattering free path, the second initial transmission position and the second initial transmission direction until a target multiple scattering factor and a target simulated photon number are obtained; and the error between the target simulated photon number and the theoretical photon number is not greater than a preset threshold.

[0054] In an embodiment of the present invention, multiple scattering simulation is performed again based on the acquired second initial scattering free path, the second initial transmission position and the second initial transmission direction to obtain the multiple scattering factor and the simulated photon number at the end of the second iteration. When the error between the simulated photon number and the theoretical photon number is not greater than a preset threshold, the multiple scattering factor at the end of the second iteration is used as the target simulated photon number. When the error between the simulated photon number and the theoretical photon number is greater than the preset threshold, the third iteration is continued until the target multiple scattering factor and the target simulated photon number are obtained, so that the error between the target simulated photon number and the theoretical photon number is not greater than the preset threshold.

[0055] S105. Determine an actual extinction coefficient based on the apparent extinction coefficient and the target multiple scattering factor, and obtain atmospheric visibility based on the actual extinction coefficient.

[0056] In an embodiment of the present invention, a preset coefficient calculation formula can be proposed, and the apparent extinction coefficient and the target multiple scattering factor are brought into the preset coefficient calculation formula to obtain the actual extinction coefficient, and the atmospheric visibility is further obtained through the actual extinction coefficient. Among them, when the actual extinction coefficient increases, the atmospheric visibility decreases, which means that the more particulate matter there is in the air (whether due to pollution, fog, haze, etc.), the more the light is absorbed and scattered, and the lower the atmospheric visibility. The preset coefficient calculation formula is as follows:

[0057]

[0058] In the above formula (1), σ is the actual extinction coefficient, R is the laser radar detection distance, m is the target multiple scattering factor, which represents the ratio of the energy of multiple scattered photons to that of single scattered photons, m' is the derivative of the target multiple scattering factor, and σ t is the apparent extinction coefficient.

[0059] Among them, the traditional single scattering lidar equation does not consider the influence of multiple scattering. The lidar equation directly used for inversion is not the actual atmospheric extinction coefficient, but the apparent extinction coefficient that includes the influence of multiple scattering. The lidar equation constructed based on the apparent extinction coefficient is:

[0060]

[0061] In the above formula (3), P is the echo signal received by the laser radar; C is the system constant; β is the backscattering coefficient, and r takes a value from 0 to R, which is a known value.

[0062] Among them, in the photon counting mode, the signal received by the lidar contains single scattered photons and multiple scattered photons, so the received energy is greater than the energy of single scattering. According to the literature, the multiple scattering lidar equation is as follows:

[0063]

[0064] According to the above formulas (3) and (4), the relationship between the multiple scattering factor, the actual extinction coefficient and the apparent extinction coefficient can be obtained, as shown in the following formula (5):

[0065]

[0066] Formula (1) is obtained by deriving the above formula (5).

[0067] It can be understood that in an embodiment of the present invention, the received lidar echo signal is input into a time convolution network to obtain an apparent extinction coefficient; the lidar echo signal includes multiple scattered photons and single scattered photons; the apparent extinction coefficient is obtained by inputting the received lidar echo signal into a time convolution network, thereby ensuring the accuracy and stability of the apparent extinction coefficient estimation. The initial scattering free path of the photons in the first iteration is obtained according to the apparent extinction coefficient, and multiple scattering simulation is performed based on the first initial scattering free path, the first initial transmission direction and the first initial transmission position to obtain the initial multiple scattering factor and the initial simulated photon number; the theoretical photon number is obtained based on the laser radar echo signal, and when the error between the theoretical photon number and the simulated photon number is greater than the preset threshold, the second initial scattering free path, the second initial transmission position and the second initial transmission direction of the photons in the second iteration are obtained; multiple scattering simulation is performed again based on the second initial scattering free path, the second initial transmission position and the second initial transmission direction until the target multiple scattering factor and the target simulated photon number are obtained; the error between the target simulated photon number and the theoretical photon number is not greater than the preset threshold; the actual extinction coefficient is determined based on the apparent extinction coefficient and the target multiple scattering factor. This process is iterated continuously until the error is less than the set threshold. Through the accurate iterative solution of multiple scattering, the calculation accuracy of the actual extinction coefficient is improved. Atmospheric visibility is obtained based on the actual extinction coefficient, which improves the visibility detection accuracy under complex atmospheric conditions.

[0068] In some embodiments of the present invention, performing multiple scattering simulation based on the first initial scattering free path, the acquired first initial transmission direction and the first initial transmission position in S102 to obtain the initial multiple scattering factor and the initial simulated photon number can be described by the following steps.

[0069] S1021. Acquire a second transmission direction at a first moment based on the first initial direction and the first moment.

[0070] In some embodiments of the present invention, a rotation matrix is ​​first obtained, and the rotation matrix, the first initial transmission direction and the first moment are brought into a direction calculation formula to calculate the second transmission direction at the first moment. The direction calculation formula is:

[0071]

[0072] In the above formula (6), n is the time, which is the first time here, and D0 is the first initial transmission direction [0,0,1] T , define the direction vector D of the photon after scattering at the nth moment n for xn ,u yn ,u zn ] Τ , x, y and z are coordinate axes in different directions, u is the vector value of vectors in different directions, and the second transmission direction at the first moment can be calculated by the above direction calculation formula (6). θ is the angle between the scattered photons and the direction of the photons to be received by the original laser receiver, which is determined by the scattering phase function. is determined randomly between 0 and 2π.

[0073] In some embodiments of the present invention, during the forward and backward transmission of multiple scattering, photons are basically unidirectional. For scattering at a small angle close to 0°, the HG phase function is used to describe it. This function can effectively simulate the scattering characteristics of photons when they deviate from the propagation direction at a small angle. For scattering at a large angle close to 180°, the RHG phase function is used. This function is closer to the large-angle backscattering characteristics of Mie scattering and is more suitable for describing multiple scattering behavior in complex media, as shown in the following formulas (7) and (8):

[0074]

[0075] In the above formulas (7) and (8), P HG , P RHG is the scattering probability density function at different angles; g is the asymmetry factor.

[0076] In some embodiments of the present invention, Figure 4 As shown, Figure 4 is the scattering diagram when the first initial transmission direction is along the positive direction of the z-axis. In Figure 4, there are three directional axes, namely the x-axis, the y-axis and the z-axis. The scattering is isotropic in the plane (xoy) perpendicular to the transmission direction. θ is the angle between the scattered photon and the direction of the photon to be received by the original laser receiver. The azimuth angle Uniformly distributed in the range 0 to 2π.

[0077] S1022. Obtain a second transmission position of the photon at the first moment based on the first initial transmission position, the second transmission direction, the first initial scattering free path, and a position calculation formula.

[0078] In some embodiments of the present invention, after obtaining the first initial scattering free path, the second transmission direction and the first initial transmission position, the first initial scattering free path, the second transmission direction and the first initial transmission position are substituted into the position calculation formula to obtain the second transmission position of the photon at the first moment; wherein the position calculation formula is as follows:

[0079] L n =L n-1 +lD n (9)

[0080] In the above formula (9), L n-1 is the transmission position, here it is the first initial transmission position, L n Here is the second transmission position, l is the scattering free path, and here are all possible scattering free paths l corresponding to the first initial scattering free path distribution.

[0081] S1023. When it is determined through the second transmission position and the second transmission direction that the photons have entered the laser receiver, an initial simulated photon number and an initial multiple scattering factor are obtained through the laser receiver.

[0082] In some embodiments of the present invention, it is determined whether the photon has entered the laser receiver by the second transmission position and the second transmission direction. If the photon has entered the laser receiver, the initial simulated photon number and the initial multiple scattering factor are obtained from the laser receiver. If the photon has not entered the laser receiver, the transmission position and transmission direction of the photon at the next moment are obtained. It can be understood that in some embodiments of the present invention, the second transmission direction at the first moment is obtained based on the first initial transmission direction and the first moment, and the second transmission position of the photon at the first moment is obtained based on the first initial transmission position, the second transmission direction, the first initial scattering free path and the position calculation formula. When it is determined that the photon has entered the laser receiver by the second transmission position and the second transmission direction, the initial simulated photon number and the initial multiple scattering factor are obtained by the laser receiver. In the initial stage of the simulation, the method temporarily determines the first initial scattering free path using the apparent extinction coefficient, and calculates the initial multiple scattering factor based on the first initial scattering free path, thereby improving the accuracy of the calculation result.

[0083] In some embodiments of the present invention, S1022 also includes S201 to S203, which are explained by the following steps.

[0084] S201. When it is determined through the second transmission position and the second transmission direction that the photon has not entered the laser receiver, obtain the second scattering free path at the first moment through the second transmission position and the scattering free path formula.

[0085] In some embodiments of the present invention, photons are divided into forward transmission photons and backward transmission photons. When it is determined that the photons have not entered the laser receiver through the second transmission position and the second transmission direction, the second transmission position is brought into the scattering free path formula to obtain the second scattering free path at the first moment, wherein the scattering formula is:

[0086]

[0087] In the above formulas (10) and (11), z is the transmission position, which is the second transmission position in this case, and f f is the scattering probability of the forward transmission, f b is the scattering probability of backward transmission, r takes values ​​from 0 to 1 and is a known value.

[0088] In some embodiments of the present invention, in the first iteration, the scattering free path formula is the above formula (10) and formula (11), and when it is the second iteration to the nth iteration, the scattering formula is the following formula (12) and formula (13):

[0089]

[0090] In the above formulas (12) and (13), f f ' is the scattering probability of forward transmission, f b ' is the scattering probability of backward transmission, r takes values ​​from 0 to 1 and is a known value.

[0091] In some embodiments of the present invention, the transmission position and transmission direction of the photon are determined by the scattering free path and the scattering phase function, respectively, wherein the scattering free path is determined by the extinction coefficient. According to the Beer-Lambert Law, the atmospheric transmittance can be expressed as the following formula (14):

[0092]

[0093] In the above formula (14), T is the atmospheric transmittance, l is the scattering free path, represents the distance the photon propagates, and r takes values ​​between 0 and l.

[0094] Furthermore, when photons propagate in the distance range of 0 to l, the transmission process includes two parts: transmission and scattering. The atmospheric transmittance T represents the cumulative distribution function of the photon transmission, while the cumulative distribution function F of the photon scattering can be expressed as the following formula (15):

[0095] F(l)=1-T(l)(15)

[0096] Furthermore, the following formula (16) can be obtained from the definition of the cumulative distribution function:

[0097]

[0098] In the above formula (16), f is the probability density function of photon scattering, which is the probability density function of the scattering free path l in the process of multiple scattering. Combining formulas (14), (15) and (16), the probability density function of the scattering free path is obtained as shown in (17):

[0099]

[0100] Furthermore, since the photon includes forward transmission and backward transmission in multiple scattering, the probability density function of the scattering free path can be obtained by formulas (1) and (17) as shown in the following (18):

[0101]

[0102] Furthermore, the probability density functions of the forward and backward transmission scattering free paths at different distances are further obtained by formula (18), that is, the scattering formulas of the above formulas (12) and (13), where r takes a value between 0 and 1.

[0103] In some embodiments of the present invention, in determining whether a photon is received by a laser receiver, it is necessary to ensure that the photon can effectively reach the laser receiver and that its incident angle is smaller than the receiving field of view angle, that is, to ensure that the angle between the direction vector of the photon and the optical fiber interface satisfies the critical total reflection angle of the optical fiber. Whether a photon is received by a laser receiver can be determined by the following formula (19):

[0104]

[0105] In the above formula (19), Φ is the critical total reflection angle.

[0106] S202: Acquire a third transmission position of the photon at a second moment based on the second transmission position, the third transmission direction, the second scattering free path and a position calculation formula.

[0107] S203, again judging whether the photons are received by the laser receiver based on the third transmission direction and the third transmission position, until an initial simulated photon number and an initial multiple scattering factor are obtained through the laser receiver.

[0108] In some embodiments of the present invention, the second transmission position, the third transmission direction and the second scattering free path are substituted into the position calculation formula to obtain the third transmission position of the photon at the second moment, and the third transmission direction and the third transmission position are used to determine whether the photon has entered the laser receiver. If the photon has entered the laser receiver, the initial simulated number of photons and the initial multiple scattering factor are obtained through the laser receiver. If the photon has not entered the laser receiver, the transmission direction and the transmission position at the third moment are calculated again, and the transmission direction and the transmission position at the third moment are used to determine whether the photon has entered the laser receiver. If the photon has entered the laser receiver, the initial simulated number of photons and the initial multiple scattering factor are obtained through the laser receiver. If the photon has not entered the laser receiver, the transmission direction and the transmission position at the fourth moment are calculated again, and this cycle is repeated until the initial simulation number and the initial multiple scattering factor are obtained.

[0109] In some embodiments of the present invention, the temporal convolutional neural network in S101 can be implemented through S10 to S13, which is illustrated by the following steps.

[0110] S10. Obtain a target apparent extinction coefficient based on a sampling result in a preset apparent extinction coefficient range, and use the target apparent extinction coefficient and a laser radar equation to obtain respective corresponding laser radar echo simulation signals.

[0111] In some embodiments of the present invention, as described in Table 1, Table 1 shows the apparent extinction coefficient characteristics under four typical atmospheric conditions provided by embodiments of the present invention, including air pollutant characteristics, apparent extinction coefficient ranges and their height variation trends.

[0112] Table 1 Characteristics of apparent extinction coefficient under four typical atmospheric conditions

[0113]

[0114]

[0115] Random sampling is performed within the apparent extinction coefficient range in Table 1 to obtain a plurality of sampling results of the apparent extinction coefficients, and the plurality of apparent extinction coefficients are substituted into the laser radar equation in formula (2) to obtain the laser radar echo simulation signal.

[0116] S11. Obtain a laser radar echo measured signal and a corresponding measured apparent extinction coefficient, and obtain a corresponding first distance correction signal based on the laser radar echo measured signal.

[0117] In some embodiments of the present invention, a laser radar echo measured signal corresponds to a first distance correction signal. The laser radar echo measured signal is a real laser radar echo signal obtained by actual measurement. The laser radar echo measured signal is substituted into the following formula to obtain the corresponding first distance correction signal.

[0118] X(R)=P(R)R 2 (20)

[0119] In the above formula (20), P is the actual measured signal of the laser radar echo, and X is the first distance correction signal.

[0120] S12. Obtain a corresponding target distance correction signal based on the first distance correction signal, and when the mean square error between the target distance correction signal and the first distance correction signal is less than a preset value, use the laser radar echo measurement signal corresponding to the first distance correction signal as the target laser radar echo measurement signal.

[0121] In some embodiments of the present invention, the target lidar echo measured signal is used to construct a training sample, the first distance correction signal is subjected to a series of processing to obtain a target distance correction signal, and the mean square error between the first distance correction signal and the target distance correction signal is calculated. If the calculated mean square error is less than a preset value, the lidar echo measured signal corresponding to the first distance correction signal is used as the target lidar echo measured signal.

[0122] S13, taking the target lidar echo measured signal, the measured apparent extinction coefficient, the lidar echo simulation signal and the target apparent extinction coefficient as initial training samples, and determining the temporal convolutional network based on the initial training samples.

[0123] In some embodiments of the present invention, the target lidar echo measured signal and its corresponding measured apparent extinction coefficient, the lidar echo simulation signal and its corresponding target apparent extinction coefficient are sampled to obtain initial training samples, and the initial training samples are used to obtain a temporal convolutional network.

[0124] It can be understood that in some embodiments of the present invention, the target apparent extinction coefficient is obtained based on the sampling results in the preset apparent extinction coefficient range; and the target apparent extinction coefficient and the laser radar equation are used to obtain the corresponding laser radar echo simulation signals, the laser radar echo measured signal and the corresponding measured apparent extinction coefficient are obtained, and the first distance correction signal is obtained based on the laser radar echo measured signal, and the corresponding target distance correction signal is obtained based on the first distance correction signal, and when the mean square error between the target distance correction signal and the first distance correction signal is less than a preset value, the laser radar echo measured signal corresponding to the first distance correction signal is used as the target laser radar echo measured signal, and the target laser radar echo measured signal, the measured apparent extinction coefficient, the laser radar echo simulation signal and the target apparent extinction coefficient are used as initial training samples, and the temporal convolution network is determined based on the initial training samples. In this method, the initial training samples are constructed by the target laser radar echo measured signal and the laser radar echo simulation signal, and the laser radar echo simulation signal is generated based on typical atmospheric conditions, providing sufficient samples to enhance the generalization ability of the model. The target LiDAR echo measured signal comes from the real LiDAR echo signal, which helps the model fit the complex actual environment more accurately. By combining the LiDAR echo simulation signal with the target LiDAR echo measured signal, the model is ensured to have both wide adaptability and accurate reflection of the complexity of actual application scenarios.

[0125] In some embodiments of the present invention, obtaining the corresponding target distance correction signal based on the first distance correction signal in S12 can be implemented through S12a and S12b, which is explained through the following steps.

[0126] S12a, processing the first distance correction signal by piecewise linear approximation method and sliding average method to obtain a processed distance correction signal, and determining a first apparent extinction coefficient corresponding to the processed distance correction signal.

[0127] S12b. Obtain a corresponding target distance correction signal through the first apparent extinction coefficient.

[0128] In some embodiments of the present invention, the piecewise linear approximation mainly divides the complex first distance correction signal into several intervals, and then uses a linear function (i.e., a straight line) in each interval to approximate the original signal. The sliding average method is a commonly used signal smoothing processing technology, which takes a window of a fixed length, takes the average value of the first distance correction signal in the window, then translates the window by a fixed step length, and repeats the process of taking the average value at the new position. The first distance correction signal is processed by the piecewise linear approximation method and the sliding average method to obtain a processed distance correction signal, which is smooth and decreasing, and the first apparent extinction coefficient corresponding to the processed distance correction signal is further calculated, and finally the target distance correction signal corresponding to the first apparent extinction coefficient is calculated.

[0129] It can be understood that in some embodiments of the present invention, the first distance correction signal is processed by a piecewise linear approximation method and a sliding average method to obtain a processed distance correction signal, and the first apparent extinction coefficient corresponding to the processed distance correction signal is determined, and the corresponding target distance correction signal is obtained through the first apparent extinction coefficient. This method can effectively filter out samples with large errors.

[0130] In some embodiments of the present invention, determining the temporal convolutional network based on the initial training sample in S13 can be implemented through S13a to S13c, which is explained by the following steps.

[0131] S13a. Based on the logarithmic distance correction signal derivative formula, the derivatives of the logarithmic distance correction signal corresponding to the target lidar echo measured signal and the lidar echo simulation signal are respectively obtained.

[0132] In some embodiments of the present invention, the logarithmic distance correction signal derivative formula is as follows:

[0133]

[0134] In the above formula (21), S' is the derivative of the logarithmic distance correction signal. Substitute the target laser radar echo measured signal and the laser radar echo simulation signal into the above formula (21) respectively to obtain the logarithmic distance correction signals corresponding to the target laser radar echo measured signal and the laser radar echo simulation signal respectively.

[0135] In some embodiments of the present invention, the logarithmic distance correction signal is as follows:

[0136] S(R)=ln[P(R)R 2 ](twenty two)

[0137] In the above formula (22), S is the logarithmic distance correction signal.

[0138] Furthermore, the atmospheric backscattering coefficient β and the atmospheric apparent extinction coefficient σ t The following relationship exists:

[0139] β=C'σ t k (twenty three)

[0140] In the above formula (12), C' is a constant; k is the extinction scattering logarithm ratio, and in the embodiment of the present invention, k=1.0. Formula (21) can be obtained through formulas (3), (22) and (23).

[0141] S13b, construct the target training sample through the derivative of the logarithmic distance correction signal, the target apparent extinction coefficient and the measured apparent extinction coefficient.

[0142] S13c. Train the temporal convolutional network to be trained using target training samples until the training conditions are met, thereby obtaining a temporal convolutional network.

[0143] In some embodiments of the present invention, the derivative of the logarithmic distance correction signal is the derivative of the logarithmic distance correction signal corresponding to the target laser radar echo measured signal, and the derivative of the logarithmic distance correction signal corresponding to the laser radar echo simulation signal. The target training sample is constructed by the derivative of the logarithmic distance correction signal, the target apparent extinction coefficient and the apparent extinction coefficient, and the time convolution network to be trained is trained by the target training sample until the training conditions are met, thereby obtaining the trained time convolution neural network.

[0144] It can be understood that in some embodiments of the present invention, a target training sample is constructed by the derivative of the logarithmic distance correction signal, the target apparent extinction coefficient and the apparent extinction coefficient, and the temporal convolutional network to be trained is trained by the target training sample until the training conditions are met to obtain the temporal convolutional network. Through this method, the estimation ability of the temporal convolutional network for the apparent extinction coefficient is enhanced.

[0145] In an embodiment of the present invention, Example 1 is a process of calculating visibility in complex weather conditions.

[0146] Under low visibility conditions, multiple scattering has a significant impact on the laser radar echo signal. In order to verify the performance of the atmospheric visibility calculation method provided by the embodiment of the present invention, two typical visibility conditions of 100m and 800m are selected to carry out simulation experiments, and the laser radar measured echo signal is used for verification. Among them, 100m visibility is an important standard for road traffic. Under this visibility, the concentration of aerosols and particulate matter is high, and the multiple scattering phenomenon is significant. The simulation sets the atmospheric extinction coefficient to be uniformly distributed in the horizontal direction. 800m visibility is a key criterion for flight decision-making to ensure that the pilot completes the landing operation safely. According to the 3° landing glide angle of the aircraft, the simulation sets the atmospheric extinction coefficient to be non-uniformly distributed in the oblique direction. According to the definition of meteorological optical range (MOR), the actual extinction coefficients under these two visibility conditions are calculated respectively, and used as the input parameters of multiple scattering simulation to obtain the total simulated photon number, that is, the theoretical photon number. In this process, the theoretical value of the multiple scattering factor is also generated to provide a reference for verifying the correctness of the final result. The experimental parameters of multiple scattering simulation were set based on the lidar parameters and low visibility atmospheric conditions, as shown in Table 2.

[0147] Table 2 Multiple scattering simulation parameters

[0148] parameter Numeric Simulated photon number <![CDATA[10 9 ]]> Scattering phase function HG / RHG Receiving lens radius / mm 50 Maximum number of scattering 20 Asymmetry Factor 0.9 Receiving field of view / mrad 1.2 Laser divergence angle / mrad 0.75 Initial laser width / mm 2 Laser wavelength / nm 1064

[0149] (1) 100m atmospheric visibility simulation experiment

[0150] According to the simulation conditions, under the condition of 100m visibility, the actual extinction coefficient is 29.96km-1. In order to clearly show the change trend of the laser radar echo signal with the detection distance, the logarithmic coordinates are used to show the laser radar echo signal containing only single scattered photons and the laser radar echo signal containing multiple scattered photons, respectively. Figure 5 shown. Figure 5 The schematic diagram of the variation trend of the total simulated photon number and the single scattered photon number provided by the embodiment of the present invention. Figure 5 It can be seen that the number of photons in the lidar echo signal gradually decreases with the increase of detection distance, but the total number of photons including multiply scattered photons is always greater than the number of single scattered photons.

[0151] According to the simulation signal, the apparent extinction coefficient is calculated using the time convolution network and the Klett Inversion Method, such as Figure 6 As shown, Figure 6A schematic diagram of the effects of different methods for calculating the apparent extinction coefficient provided in an embodiment of the present invention, wherein the different methods are a time convolutional network and a Klett inversion method. Compared with the Klett inversion method, it can be seen that the estimation result of the time convolutional network exhibits smaller volatility, higher stability and avoids the appearance of negative values. This is mainly due to the fact that the time convolutional network effectively extracts time series features through convolution operations, thereby enhancing the accuracy and robustness of the model, while data screening further improves the reliability of the results. The time convolutional network is used to estimate the apparent extinction coefficient, determine the scattering free path, and then perform multiple scattering simulations, which undergo a total of 4 iterations, and each iteration updates the multiple scattering factor and the number of photons. As shown in FIG. Figure 7 As shown, Figure 7 The effect diagram of the change trend of the multiple scattering factor provided by the embodiment of the present invention is as follows: Figure 8 As shown, Figure 8 Schematic diagram of the effect of the iteration of the laser radar echo signal provided by the embodiment of the present invention. As the number of iterations increases, the multiple scattering factor gradually increases and approaches the theoretical value, and the number of photons in the laser radar echo signal also gradually approaches the theoretical value, indicating that the simulation value provided by the embodiment of the present invention is highly consistent with the theoretical value.

[0152] Traditional visibility inversion algorithms usually ignore the multiple scattering effect and regard the apparent extinction coefficient as the actual extinction coefficient, resulting in the calculated visibility being higher than the actual value. In order to compare the results, the Klett inversion algorithm is used to directly invert the actual extinction coefficient without considering multiple scattering, and the atmospheric visibility calculation method provided by the embodiment of the present invention is used to consider the actual extinction coefficient of multiple scattering, such as Fig. 9 As shown, Fig. 9 The present invention provides a schematic diagram of the effect of the actual extinction coefficient obtained by different methods. The different methods are the time convolution network and the Klett inversion method. As the distance increases, the error between the actual extinction coefficient inverted by the Klett inversion algorithm and the theoretical value becomes larger and larger, while the atmospheric visibility calculation method provided by the embodiment of the present invention maintains a high accuracy. The average values ​​of the actual extinction coefficients calculated by the atmospheric visibility calculation method and the Klett inversion algorithm provided by the embodiment of the present invention are 29.45km and 29.45km, respectively. -1 、25.88km -1, the relative errors of this value and the theoretical value are 1.70% and 11.92% respectively, and the root mean square errors with the theoretical value are 10.49 and 18.63 respectively. Correspondingly, the average visibility calculated by the atmospheric visibility calculation method provided in the embodiment of the present invention is 101.73m, while that obtained by the Klett algorithm is 115.76m. In comparison, the atmospheric visibility calculation method provided in the embodiment of the present invention is closer to the theoretical value, and the calculated atmospheric visibility is more accurate. Overall, under multiple scattering conditions, the traditional algorithm has a large inversion error.

[0153] (2) 800m visibility simulation experiment

[0154] According to the simulation conditions, under the condition of 800m visibility, the average value of the actual extinction coefficient in the slant direction is 3.74km -1 The simulated laser radar echo signal is as follows: Fig.10 As shown, Fig.10 As shown, Fig.10 The present invention provides a schematic diagram of the effect of simulating the laser radar echo signal. Compared with the visibility of 100m, the difference between the total simulated photon number and the single scattered photon number is not obvious. This indicates that under this visibility condition, the number of multiple scattered photons is small.

[0155] In an embodiment of the present invention, Fig.11 Schematic diagram of the effect of the apparent extinction coefficient obtained by different methods provided in the embodiments of the present invention. The different methods are the time convolution network and the Klett inversion method. Unlike the significant fluctuation under the visibility condition of 100m, under the visibility of 800m, the extinction coefficient inverted by the Klett inversion algorithm changes smoothly and has no unreasonable value, so the improvement of the time convolution network is relatively limited. Only one iteration is performed using the atmospheric visibility calculation method provided in the embodiments of the present invention, Fig.12 A schematic diagram showing the effect of the simulated laser radar echo signal approaching the theoretical value provided by an embodiment of the present invention, Fig.13 A schematic diagram of the effect of the multiple scattering factor provided by an embodiment of the present invention approaching the theoretical value.

[0156] In the embodiment of the present invention, under the visibility condition of 800m, the photon scattering probability is greatly reduced, and the apparent extinction coefficient is closer to the actual extinction coefficient. Fig.14 Schematic diagram of the effect of actual extinction coefficient obtained by different methods provided in the embodiments of the present invention. The different methods are time convolution network and Klett inversion method. The average actual extinction coefficient calculated by the atmospheric visibility calculation method provided in the embodiments of the present invention is 3.73 km -1 , Klett algorithm is 3.68 km -1, the relative errors between the actual extinction coefficients and the theoretical values ​​are 0.26% and 1.60%, respectively, and the root mean square errors are 0.27 and 0.30, respectively. Correspondingly, the average visibility calculated by the atmospheric visibility calculation method provided in the embodiment of the present invention is 803.21m, while that calculated by the Klett inversion algorithm is 814.13m. This shows that the atmospheric visibility calculation method provided in the embodiment of the present invention is superior to the Klett inversion algorithm in terms of accuracy. Compared with the visibility condition of 100m, the influence of multiple scattering is reduced under the visibility of 800m, indicating that the influence of multiple scattering on the signal is weakened under high visibility.

[0157] (3) Measured signal experiment

[0158] In the embodiment of the present invention, a laser radar is used to carry out field experiments. The radar uses a semiconductor laser with a laser wavelength of 1064nm, a maximum laser pulse energy of 450μJ, and a maximum detection distance of more than 10km. Two sets of measured laser radar echo signals obtained by using the laser radar on January 31, 2024 were selected, namely Fig.15 , Fig.15 Schematic diagram of the effect of the actual extinction coefficient obtained by different methods provided in the embodiments of the present invention. The different methods are the time convolution network and the Klett inversion method. The radar adopts an off-axis optical system, and is affected by the geometric overlap factor, with a detection blind area of ​​0 to 0.6 km. In low-visibility weather, the atmospheric extinction is obvious, and the laser power decays rapidly. Under the two weather conditions, the effective detection distance of the system is 1.41 km and 4.44 km, respectively. In order to obtain the experimental reference value, the atmospheric transmissometer in the same area is used as a standard measuring instrument, and the visibility of signals A and B is measured to be 1.23 km and 5.93 km, respectively. The atmospheric transmissometer obtains visibility by measuring the atmospheric transmittance, avoiding the problem that the laser radar relies on backscattering and is easily affected by multiple scattering, and can provide more accurate visibility measurement results. In order to verify the effect of the algorithm, the atmospheric visibility calculation method and the Klett inversion algorithm provided in the embodiment of the present invention are used to compare and analyze the two groups of signals A and B. Fig.16 A schematic diagram showing the effects of comparing and analyzing group A signals using different methods provided in an embodiment of the present invention. Fig.17 A schematic diagram showing the effects of comparing and analyzing group B signals using different methods provided in an embodiment of the present invention. Fig.16 and Fig.17The different methods are time convolution network and Klett inversion method. The visibility calculated by the atmospheric visibility calculation method provided in the embodiment of the present invention is 1.22km and 5.99km respectively, and the visibility calculated by the Klett inversion algorithm is 1.26km and 6.06km. For signal A, the relative errors of the atmospheric visibility calculation method and Klett inversion algorithm provided in the embodiment of the present invention and the measured value are 0.81% and 2.44% respectively, and the relative error is reduced by 1.63%, and the reduction is 66.8%. For signal B, the relative errors of the atmospheric visibility calculation method and Klett inversion algorithm provided in the embodiment of the present invention and the measured value are 1.01% and 2.19% respectively, and the relative error is reduced by 1.18%, and the reduction is 53.8%. The results show that the calculation results of the atmospheric visibility calculation method provided in the embodiment of the present invention are more accurate and closer to the measured values. Especially under lower visibility conditions, by considering the multiple scattering effect, the atmospheric visibility calculation method provided in the embodiment of the present invention significantly reduces the calculation error, showing its effectiveness and advantages in complex scattering environments.

[0159] Reference Fig.18 , shows a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. The specific embodiment of the present invention does not limit the specific implementation of the electronic device.

[0160] like Fig.18 As shown, the electronic device may include: a processor (processor) 502, a communication interface (Communications Interface 504, a memory (memory) 506, and a communication bus 508.

[0161] in:

[0162] The processor 502 , the communication interface 504 , and the memory 506 communicate with each other via a communication bus 508 .

[0163] The communication interface 504 is used to communicate with other electronic devices or servers.

[0164] The processor 502 is used to execute the program 510, and specifically can execute the relevant steps in the above method embodiment.

[0165] Specifically, the program 510 may include program codes, which include computer operation instructions.

[0166] The processor 502 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0167] The memory 506 is used to store the program 510. The memory 506 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0168] The program 510 may be specifically used to enable the processor 502 to execute operations corresponding to the methods described in the above method embodiments.

[0169] The specific implementation of each step in program 510 can refer to the corresponding description of the corresponding steps and units in the above method embodiment, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described devices and modules can refer to the corresponding process description in the above method embodiment, which will not be repeated here.

[0170] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present invention can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present invention.

[0171] The above-described method according to an embodiment of the present invention may be implemented in hardware, firmware, or as software or computer code that may be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code that is originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded over a network and will be stored in a local recording medium, so that the method described herein may be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that a computer, processor, microprocessor controller, or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, processor, or hardware, the method described herein is implemented. In addition, when a general-purpose computer accesses the code for implementing the method shown herein, the execution of the code converts the general-purpose computer into a dedicated computer for executing the method shown herein.

[0172] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present invention.

[0173] The above implementation methods are only used to illustrate the embodiments of the present invention, and are not limitations of the embodiments of the present invention. Ordinary technicians in the relevant technical field may make various changes and modifications without departing from the spirit and scope of the embodiments of the present invention. Therefore, all equivalent technical solutions also belong to the scope of the embodiments of the present invention. The patent protection scope of the embodiments of the present invention should be defined by the claims.

Claims

1. A method for calculating atmospheric visibility, characterized in that: include: The received lidar echo signal is input into the temporal convolutional network to obtain the apparent extinction coefficient; The laser radar echo signal includes multiple scattered photons and single scattered photons; Obtaining a first initial scattering free path of photons in a first iteration according to the apparent extinction coefficient, and performing multiple scattering simulation based on the first initial scattering free path, the obtained first initial transmission direction and the first initial transmission position to obtain an initial multiple scattering factor and an initial simulated photon number; the photons are generated by a laser radar; Acquire a theoretical number of photons based on the laser radar echo signal, and when an error between the theoretical number of photons and the initial simulated number of photons is greater than a preset threshold, acquire a second initial scattering free path, a second initial transmission position, and a second initial transmission direction of the photons in a second iteration; performing multiple scattering simulation again based on the second initial scattering free path, the second initial transmission position, and the second initial transmission direction until a target multiple scattering factor and a target simulated photon number are obtained; and an error between the target simulated photon number and the theoretical photon number is not greater than the preset threshold; An actual extinction coefficient is determined based on the apparent extinction coefficient and the target multiple scattering factor, and atmospheric visibility is acquired based on the actual extinction coefficient.

2. The method according to claim 1, characterized in that The temporal convolutional network includes an input layer, a first stack, a second stack and a fully connected layer, the first stack includes a first temporal convolutional layer, a second temporal convolutional layer, and a third temporal convolutional layer, the second stack includes a temporal convolutional layer one, a temporal convolutional layer two and a temporal convolutional layer three, the input layer, the first temporal convolutional layer, the second temporal convolutional layer, the third temporal convolutional layer, the temporal convolutional layer one, the temporal convolutional layer two, the temporal convolutional layer three and the fully connected layer are connected in sequence, and the temporal convolutional layers of the first stack and the second stack are each set with an expansion rate parameter.

3. The method according to claim 1, characterized in that The performing multiple scattering simulation based on the first initial scattering free path, the acquired first initial transmission direction and the first initial transmission position to obtain an initial multiple scattering factor and an initial simulated photon number includes: Acquire a second transmission direction at the first moment based on the first initial transmission direction and the first moment; Acquire a second transmission position of the photon at the first moment based on the first initial transmission position, the second transmission direction, the first initial scattering free path, and a position calculation formula; When it is determined through the second transmission position and the second transmission direction that the photons have entered the laser receiver, the initial simulated photon number and the initial multiple scattering factor are acquired through the laser receiver.

4. The method according to claim 3, characterized in that After obtaining the second transmission position of the photon at the first moment based on the first initial transmission position, the second transmission direction, the first initial scattering free path and a position calculation formula, the method further includes: In a case where it is determined through the second transmission position and the second transmission direction that the photon has not entered the laser receiver, obtaining a second scattering free path at the first moment through the second transmission position and a scattering path formula; Calculating a third transmission direction at the second moment based on the first initial transmission direction and the second moment; Acquire a third transmission position of the photon at the second moment based on the second transmission position, the third transmission direction, the second scattering free path and the position calculation formula; It is determined again based on the third transmission direction and the third transmission position whether the photon is received by the laser receiver until the initial simulated photon number and the initial multiple scattering factor are acquired by the laser receiver.

5. The method according to claim 1, characterized in that: The determining of the actual extinction coefficient based on the apparent extinction coefficient and the target multiple scattering factor comprises: The actual extinction coefficient is calculated by the apparent extinction coefficient, the target multiple scattering factor and a preset coefficient calculation formula; wherein the preset coefficient calculation formula is: In the above formula, R is the detection distance of the laser radar, m is the target multiple scattering factor, m' is the derivative of the target multiple scattering factor, σ is the actual extinction coefficient, σ t is the apparent extinction coefficient.

6. The method according to claim 1, characterized in that The temporal convolutional network is trained through the following process: Obtaining a target apparent extinction coefficient based on a sampling result in a preset apparent extinction coefficient range; and obtaining respective corresponding laser radar echo simulation signals using the target apparent extinction coefficient and a laser radar equation; Obtaining a laser radar echo measured signal and a corresponding measured apparent extinction coefficient, and obtaining a corresponding first distance correction signal based on the laser radar echo measured signal; Based on the first distance correction signal, a corresponding target distance correction signal is obtained, and when a mean square error between the target distance correction signal and the first distance correction signal is less than a preset value, the laser radar echo measured signal corresponding to the first distance correction signal is used as the target laser radar echo measured signal; The target lidar echo measured signal, the measured apparent extinction coefficient, the lidar echo simulation signal and the target apparent extinction coefficient are used as initial training samples, and the temporal convolutional network is determined based on the initial training samples.

7. The method according to claim 6, characterized in that The acquiring a corresponding target distance correction signal based on the first distance correction signal comprises: Processing the first distance correction signal by a piecewise linear approximation method and a sliding average method to obtain a processed distance correction signal, and determining a first apparent extinction coefficient corresponding to the processed distance correction signal; The corresponding target distance correction signal is obtained through the first apparent extinction coefficient.

8. The method according to claim 6, characterized in that The determining the temporal convolutional network based on the initial training sample comprises: Based on the logarithmic distance correction signal derivative formula, respectively obtain the derivatives of the logarithmic distance correction signal corresponding to the target laser radar echo measured signal and the laser radar echo simulation signal; constructing a target training sample through the derivative of the logarithmic distance correction signal, the target apparent extinction coefficient and the measured apparent extinction coefficient; The temporal convolutional network to be trained is trained using the target training samples until the training conditions are met, thereby obtaining the temporal convolutional network.

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