Dual-layer iterative lidar visibility inversion method and system based on near-field constraint and dynamic inversion of k value

Abstract

The application discloses a double-layer iterative laser radar visibility inversion method and system based on near-field constraint and K value dynamic inversion, and relates to the technical field of atmospheric remote sensing. Through designing an inner-outer double-layer iteration structure, the application decouples and links the optimization processes of two strongly coupled variables, i.e. the far-field boundary value and the K value, realizes the collaborative inversion of the two variables, finds a globally optimal parameter combination, and greatly improves the inversion accuracy of the extinction coefficient and the visibility. In addition, the application proposes a "near-field physical constraint" principle, utilizes the reliable characteristics of the near-field signal, converts the difficult-to-determine far-field boundary value optimization problem into a judgment problem of the physical form of the near-field profile, and enables the algorithm to have strong self-adaptive capability and to realize self-calibration without relying on external observation data.

Description

Technical Field

[0001] This invention relates to the field of atmospheric remote sensing technology, specifically to a two-layer iterative lidar visibility inversion method and system based on near-field constraints and dynamic K-value inversion. Background Technology

[0002] Visibility is the maximum horizontal distance at which a normal human eye can distinguish a black object against a background of sky under specific weather conditions at a given moment. Atmospheric visibility is an important indicator of atmospheric transparency and has significant implications for human health, transportation, aviation, and navigation.

[0003] Scattering lidar is a core device for detecting the vertical profile of the extinction coefficient of atmospheric aerosols and thus calculating visibility. The Klett inversion method is the mainstream algorithm for processing lidar signals, but its mathematical solution strongly depends on two key prior parameters: the extinction coefficient value at the far-field boundary and the extinction backscattering ratio (K-value), which characterizes the optical properties of aerosols. In traditional methods, these two parameters are usually set to fixed values ​​based on experience, leading to significant uncertainties and systematic biases in the inversion results, especially when atmospheric conditions are complex and variable, resulting in a severe decrease in inversion accuracy.

[0004] Existing technologies attempt to optimize boundary values ​​or K-values ​​separately, but often treat them as independent variables, ignoring their strong coupling relationship. Optimizing one parameter while fixing the other makes it difficult to obtain the globally optimal solution. Therefore, there is an urgent need for an inversion method that can collaboratively and adaptively determine the optimal boundary values ​​and K-values ​​to fundamentally improve the reliability and accuracy of quantitative remote sensing using lidar. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and provide a two-layer iterative lidar visibility inversion method and system based on near-field constraints and dynamic K-value inversion, which has clear physical meaning, strong anti-interference ability, and adaptability to atmospheric conditions. It can simultaneously optimize far-field boundary values ​​and K-values, thereby improving the aerosol extinction coefficient and atmospheric visibility inversion accuracy.

[0006] The first aspect discloses a two-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion, the method comprising:

[0007] Parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold;

[0008] The inner iterative loop is started with the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value;

[0009] When the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and satisfies physical rationality, the inner layer is judged to converge, and the optimal extinction coefficient profile of the inner layer and the average value of the optimal extinction coefficient profile in the near-field region under the current K value are obtained. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula, and the physical rationality means that the extinction coefficient profile changes smoothly.

[0010] The near-field average backscattering coefficient is calculated based on the inner layer optimal extinction coefficient profile shown.

[0011] A new K value is calculated based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient;

[0012] When the relative change of K is less than the K convergence threshold, the outer layer converges; otherwise, the inner layer iteration is restarted under the new K value until both the inner and outer layers converge.

[0013] Atmospheric visibility is calculated based on the extinction coefficient profile and K value obtained from the last iteration.

[0014] The second aspect discloses a two-layer iterative lidar visibility inversion system based on near-field constraints and dynamic K-value inversion, the system comprising:

[0015] An initialization module is used for parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold;

[0016] The inner optimization module is used to start the inner iterative loop under the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value;

[0017] The optimal value calculation module is used to determine inner layer convergence when the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and meets the physical rationality requirement. It obtains the inner layer optimal extinction coefficient profile and the average value of the optimal extinction coefficient profile in the near-field region under the current K value. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula. The physical rationality means that the extinction coefficient profile changes smoothly.

[0018] The near-field average backscattering coefficient calculation module is used to calculate the near-field average backscattering coefficient based on the inner layer optimal extinction coefficient profile shown.

[0019] The K-value calculation module is used to calculate a new K-value based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient.

[0020] The outer optimization module is used to achieve outer convergence when the relative change of K is less than the K convergence threshold; otherwise, the inner iteration is restarted under the new K value until both the inner and outer layers converge.

[0021] The visibility calculation module is used to calculate atmospheric visibility based on the extinction coefficient profile and K value obtained from the last iteration.

[0022] As can be seen from the above technical solutions, the present invention has the following beneficial effects:

[0023] Compared with the prior art, the present invention has the following significant advantages:

[0024] This invention, through the design of an inner and outer dual-layer iterative structure, decouples yet links the optimization processes of the two strongly coupled variables, far-field boundary values ​​and K-values, achieving synergistic inversion of both and finding the globally optimal parameter combination, significantly improving the inversion accuracy of extinction coefficient and visibility. Furthermore, this invention proposes the "near-field physical constraint" principle, leveraging the reliability of near-field signals to transform the difficult-to-determine far-field boundary value optimization problem into a problem of judging the physical morphology of the near-field profile. This gives the algorithm strong adaptive capabilities, enabling self-calibration without relying on external observation data. Moreover, this invention is insensitive to initial guesses; even if the initial boundary values ​​or K-values ​​deviate significantly, it can quickly converge to a stable solution through iteration, exhibiting strong anti-interference capabilities and applicability to various complex weather conditions. Attached Figure Description

[0025] Figure 1 The overall flowchart of a two-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion provided by the present invention is shown.

[0026] Figure 2 This is a schematic diagram of the actual echo power signal data provided by the present invention.

[0027] Figure 3 This invention provides a schematic diagram of a two-layer iterative lidar visibility inversion system architecture based on near-field constraints and dynamic K-value inversion. Detailed Implementation

[0028] To make the objectives, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of the present invention will be thorough and complete.

[0029] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there may be an intervening element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," "up," "down," and similar expressions used herein are for illustrative purposes only and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0031] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. The term "and / or" as used herein includes any and all combinations of one or more of the related listed items.

[0032] In one embodiment, the present invention provides a two-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion, such as... Figure 1 As shown, the specific steps include:

[0033] S101, parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold;

[0034] Specifically, the raw echo power signal at the lidar detection distance r is obtained. Among these, the power of the laser signal backscattered by atmospheric molecules should correspond one-to-one with the detection distance. Then, the original echo power signal... Background noise is subtracted, and then the distance correction signal X(r) is calculated, as shown in the formula:

[0035] X(r) = P(r) × r² (1)

[0036] Next, the key parameters are initialized, mainly including:

[0037] Effective signal range: The effective signal range is determined based on the distance correction signal X(r). ],in It is the starting distance at which the optical overlap factor tends to stabilize. The distance correction signal-to-noise ratio (SNR) drops to the SNR threshold. The maximum distance at. Wherein, =2, the specific value can be adjusted according to the signal quality.

[0038] Near-field region: Selected when the geometric overlap factor of the lidar is stable at 1 and the signal-to-noise ratio is higher than 1. The segment obtained [ ],in, Indicates the starting distance of the near-field region. This indicates the end distance of the near-field region.

[0039] Initial guess of K value The values ​​are set based on empirical values ​​for common aerosol types, and this invention does not impose specific limitations on them.

[0040] Extinction coefficient convergence threshold: =5%, K-value convergence threshold: =5%, where the extinction coefficient convergence threshold and the K-value convergence threshold can be adjusted according to the test results.

[0041] In one embodiment, the calculation process for the initial far-field boundary value includes:

[0042] Using the initial detection distance point as the adaptive starting point for Klett inversion, N distance points are taken backward, and linear fitting is performed on the N distance points. The initial detection distance point is the first distance point that satisfies the signal-to-noise ratio of the distance correction signal being greater than the signal-to-noise ratio threshold when searching from the far field to the near field. N is an integer greater than 1.

[0043] If the goodness of linear fit is greater than the first preset threshold and the standard deviation of slope is less than the second preset threshold, then the segment is determined to be smooth.

[0044] The initial far-field boundary value is calculated based on the fitted slope of this segment.

[0045] If the conditions that the goodness of linear fit is greater than the first preset threshold and the standard deviation of the slope of adjacent points is less than the second preset threshold are not met, then the window is slid back by one distance point, and linear fit is performed on the new N distance points until a smooth segment that meets the conditions is found.

[0046] Specifically, in At this point, an optimization algorithm is used to select a smooth, small region and the initial far-field boundary values ​​are initially estimated using the slope method. Searching from the far field to the near field, find the first condition that satisfies SNR> Distance point ,by This serves as the adaptive starting point for Klett's inversion. N points are then taken forward (e.g., N=10), and a linear fit is performed on these N points. If the goodness of fit of the linear fit is... If the slope is greater than a first preset threshold and the standard deviation of the slope is less than a second preset threshold, then the segment is considered smooth. The first preset threshold represents the goodness of fit of the linear fit. The value is 0.95, and the second preset threshold is the slope standard deviation threshold. The value is 0.1.

[0047] Then, based on the fitted slope of that segment, the following is calculated: The specific formula is as follows:

[0048] (2)

[0049] in, This indicates the slope of the fitted section.

[0050] If the above conditions are not met, slide the window back one point and repeat the above steps until a smooth segment that meets the conditions is found or the maximum distance is found. until.

[0051] S102. Start the inner iteration loop under the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value;

[0052] Specifically, set the outer iteration counter. The goal of the outer loop is to find the optimal value of K.

[0053] In the current outer iteration Under the given value, start the inner iteration and set the inner iteration counter. Initialize boundary values = Using the current and Calculate from Klett's backward integral formula Extinction coefficient profile at radar The effective signal range is defined by the radar location. Specifically, as shown in the formula:

[0054] (3)

[0055] in, Indicates the index of the inner iteration count. Indicates the detection distance. The distance at the current far-field boundary value. Indicates the innermost layer The far-field boundary value of the next iteration This means taking the natural logarithm to convert it into a linear relationship, which facilitates slope fitting and integral operations.

[0056] Then, calculate In the near field region [ The average value of ] .

[0057] S103. When the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and meets the physical rationality, the inner layer is judged to converge, and the optimal extinction coefficient profile of the inner layer and the average value of the optimal extinction coefficient profile in the near-field region under the current K value are obtained. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula, and the physical rationality means that the extinction coefficient profile changes smoothly.

[0058] It should be noted that if this is the first inner iteration... If the numerical convergence is not checked, the physical plausibility check is performed directly. If this is not the first iteration... Calculate the relative change of the near-field average extinction coefficient. The specific formula is as follows:

[0059] (4)

[0060] in, Indicates the innermost layer The average value of the extinction coefficient profile in the near-field region of the next iteration. Indicates the innermost layer The average value of the extinction coefficient profile in the near-field region of the next iteration.

[0061] like < If the physical plausibility is satisfied, then the inner layer is considered to have converged, and the next step is performed.

[0062] It should be noted that the criterion for judging physical rationality is: inspection The curve shape in the near-field region. If it from Towards If the direction (i.e. from far to near) shows a monotonous and rapid non-physical increase (forming a "peak"), it is judged as unreasonable; if the curve changes gently or only has reasonable fluctuations that conform to atmospheric physics, it is judged as reasonable.

[0063] In one embodiment, if the inner layer does not converge, the far-field boundary values ​​are updated based on near-field physical constraints until the inner layer converges.

[0064] Among them, "near-field physical constraints" refer to the fact that in the near-field region where the optical geometric overlap factor of the lidar is complete, the atmospheric extinction coefficient should not exhibit a non-physical phenomenon of rapidly and monotonically increasing with decreasing distance.

[0065] Specifically, the steps include the following:

[0066] If the physical judgment of the extinction coefficient profile is unreasonable, the current far-field boundary value is updated according to the gain factor.

[0067] If the physical judgment of the extinction coefficient profile is reasonable, but the average value of the extinction coefficient profile in the near field region has not converged, then the current far field boundary value is fine-tuned based on the relative change of the average value of the extinction coefficient profile in the near field region.

[0068] Specifically, if near field It exhibits a non-physical spike that increases sharply with decreasing distance, determining the current... If underestimated, it needs to be increased, as shown in the formula:

[0069] = (5)

[0070] Among them, the gain factor =0.1, This represents the far-field boundary value for the next inner iteration.

[0071] If near field The trend is reasonable, but the values ​​have not converged. The current far-field boundary values ​​could be adjusted. Make fine adjustments, as shown in the formula:

[0072] (6)

[0073] Among them, step size factor The far-field boundary value will be updated. .

[0074] After the update is complete, Then proceed with the next iteration of the inner layer.

[0075] When the inner iteration converges, we obtain the current... The optimal extinction coefficient profile under the following conditions and its near-field average .

[0076] In one embodiment, the invention further includes:

[0077] Determine whether the smoothness of the optimal extinction coefficient profile in the near-field region satisfies the condition that the linear fit goodness is greater than a first preset threshold and the slope standard deviation is less than a second preset threshold.

[0078] If the conditions are not met, the next round of inner layer iteration will be performed based on the updated far-field boundary values.

[0079] Specifically, after the inner layer converges, further judgment is needed before proceeding to the outer layer iteration. Smoothness in the near field. If the smoothness does not meet the condition that the goodness of linear fit is greater than a first preset threshold. And the standard deviation of the slope is less than the second preset threshold. The conditions will then As the new far-field boundary value, a new round of inner-layer iteration begins. This step utilizes the characteristic of "small near-field error" to calibrate the unreliable far-field initial value with a near-field result. If the smoothness requirement is met, proceed to the next step to update the K value.

[0080] In one embodiment, the present invention further includes the following steps:

[0081] When the outer layer is iterated for the first time, a preset perturbation is applied to the average value of the extinction coefficient profile in the near-field region, and the inner layer iteration is re-executed.

[0082] Determine whether the iteration result can still converge to the vicinity of the original solution. If it can, then perform the outer iteration.

[0083] If not, readjust the parameters and initialize.

[0084] Specifically, if this is the first iteration ( ),right Apply a small perturbation (e.g.) Then, re-execute the inner iteration and check if the iteration result still converges to the vicinity of the original solution. If it does, the algorithm has good robustness; if not, readjust the parameter initialization and start again. After successful verification, proceed to the next step.

[0085] If it is not the first outer iteration, proceed directly to the next step.

[0086] S104. Calculate the near-field average backscattering coefficient based on the inner layer optimal extinction coefficient profile;

[0087] (7)

[0088] in, Represents the near-field average backscattering coefficient. , Indicates bidirectional transmittance. This represents the average function.

[0089] S105. Calculate a new K value based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient;

[0090] Specifically, the calculations using S103 and S104 and A new K value was derived and calculated based on aerosol optical relationships. The specific formula is as follows:

[0091] (8)

[0092] S106. When the relative change of K value is less than the K value convergence threshold, the outer layer converges; otherwise, restart the inner and outer layer iterations under the new K value until both the inner and outer layers converge.

[0093] Specifically, calculate the relative change in the value of K. The specific formula is as follows:

[0094] (9)

[0095] like To determine if the outer iteration has converged, let... , The iteration terminates.

[0096] like The outer layer is determined to be non-convergent. Let... This marks the beginning of a new round of collaborative iteration between the inner and outer layers.

[0097] The iteration stops when both the inner and outer layers converge or the maximum number of iterations is reached. To prevent infinite loops, an upper limit on the number of iterations for both the inner and outer layers also needs to be set. The specific value can be set based on practical experience. When the maximum number of iterations is reached, the iteration terminates, and the extinction coefficient profile and K value obtained from the last iteration are output.

[0098] S107. Calculate atmospheric visibility based on the extinction coefficient profile and K value obtained from the last iteration.

[0099] Among them, the high-precision aerosol extinction coefficient profile obtained through double-layer iteration is The optimal K value obtained by inversion , This represents the K value that is most suitable for the current atmospheric level, and is used as the initial condition to recalculate visibility.

[0100] according to Using Koschmieder's law, the atmospheric horizontal visibility along the detection path is calculated, as shown in the formula:

[0101] (10)

[0102] in, This represents the extinction coefficient profile. This indicates atmospheric horizontal visibility.

[0103] Figure 2 This is a schematic diagram of real echo power signal data provided in an embodiment of the present invention. The vertical axis S represents the echo power signal power after distance correction, and the horizontal axis r represents the detection distance. The output result of the calculation of real echo power signal data by the present invention is: the extinction coefficient of the region (2.2km-5km) is 0.0789714, and the visibility is 51.7188km.

[0104] This invention, through the design of an inner and outer dual-layer iterative structure, decouples yet links the optimization processes of the two strongly coupled variables, far-field boundary values ​​and K-values, achieving synergistic inversion of both and finding the globally optimal parameter combination, significantly improving the inversion accuracy of extinction coefficient and visibility. Furthermore, this invention proposes the "near-field physical constraint" principle, leveraging the reliability of near-field signals to transform the difficult-to-determine far-field boundary value optimization problem into a problem of judging the physical morphology of the near-field profile. This gives the algorithm strong adaptive capabilities, enabling self-calibration without relying on external observation data. Moreover, this invention is insensitive to initial guesses; even if the initial boundary values ​​or K-values ​​deviate significantly, it can quickly converge to a stable solution through iteration, exhibiting strong anti-interference capabilities and applicability to various complex weather conditions.

[0105] This invention also provides an inversion system corresponding to the above method embodiments. Since the system embodiments are basically similar to the method embodiments, the description is relatively simple. For details of the relevant technical features and their effects, please refer to the corresponding descriptions of the above-provided method embodiments. In one embodiment, this invention provides a two-layer iterative lidar visibility inversion system based on near-field constraints and dynamic K-value inversion, such as... Figure 3 As shown, this system mainly includes:

[0106] An initialization module is used for parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold;

[0107] The inner optimization module is used to start the inner iterative loop under the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value;

[0108] The optimal value calculation module is used to determine inner layer convergence when the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and meets the physical rationality requirement. It obtains the inner layer optimal extinction coefficient profile and the average value of the optimal extinction coefficient profile in the near-field region under the current K value. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula. The physical rationality means that the extinction coefficient profile changes smoothly.

[0109] The near-field average backscattering coefficient calculation module is used to calculate the near-field average backscattering coefficient based on the inner layer optimal extinction coefficient profile shown.

[0110] The K-value calculation module is used to calculate a new K-value based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient.

[0111] The outer optimization module is used to achieve outer convergence when the relative change of K is less than the K convergence threshold; otherwise, the inner iteration is restarted under the new K value until both the inner and outer layers converge.

[0112] The visibility calculation module is used to calculate atmospheric visibility based on the extinction coefficient profile and K value obtained from the last iteration.

[0113] This invention also provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction or at least one program, which is loaded and executed by the processor. The method described above provides a two-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion.

[0114] Furthermore, the electronic device may participate in or include the apparatus or system provided in the embodiments of the present invention. The electronic device may include one or more processors (processors may include, but are not limited to, processing devices such as microprocessors (MCUs) or programmable logic devices (FPGAs), memory for storing data, and transmission devices for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a power supply, and / or a camera.

[0115] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the device (or mobile device). As involved in the embodiments of the present invention, the data processing circuit serves as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0116] The memory can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method described in the embodiments of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the above-mentioned data processing method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to electronic devices via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0117] The transmission device is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the device's communication provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0118] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows users to interact with the user interface of an electronic device (or mobile device).

[0119] This invention also provides a computer storage medium storing at least one instruction or at least one program, which is loaded and executed by a processor to implement the dual-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion provided in the above-described method embodiments.

[0120] Optionally, in this embodiment, the aforementioned computer storage medium may be located at at least one of the multiple network servers in a computer network. Optionally, in this embodiment, the aforementioned storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0121] This invention also provides a computer program product or computer program, which includes computer instructions stored in a computer storage medium. The processor of an electronic device reads the computer instructions from the computer storage medium and executes the computer instructions, causing the electronic device to perform the two-layer iterative lidar visibility inversion method based on near-field constraints and K-value dynamic inversion provided in the above-described method embodiment.

[0122] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0123] It should be understood that the above description of the preferred embodiments is quite detailed, but it should not be considered as a limitation on the scope of protection of this invention. Those skilled in the art, under the guidance of this invention, can make substitutions or modifications without departing from the scope of protection of the claims of this invention, and all such substitutions or modifications fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A two-layer iterative lidar visibility inversion method based on near-field constraints and dynamic K-value inversion, characterized in that, The method includes: Parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold; The inner iterative loop is started with the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value; When the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and satisfies physical rationality, the inner layer is judged to converge, and the optimal extinction coefficient profile of the inner layer and the average value of the optimal extinction coefficient profile in the near-field region under the current K value are obtained. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula, and the physical rationality means that the extinction coefficient profile changes smoothly. The near-field average backscattering coefficient is calculated based on the inner layer optimal extinction coefficient profile shown. A new K value is calculated based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient; When the relative change of K is less than the K convergence threshold, the outer layer converges; otherwise, the inner layer iteration is restarted under the new K value until both the inner and outer layers converge. Atmospheric visibility is calculated based on the extinction coefficient profile and K value obtained from the last iteration.

2. The method according to claim 1, characterized in that, The calculation process for the initial far-field boundary value includes: Using the initial detection distance point as the adaptive starting point for Klett inversion, N distance points are taken backward, and linear fitting is performed on the N distance points. The initial detection distance point is the first distance point that satisfies the signal-to-noise ratio of the distance correction signal being greater than the signal-to-noise ratio threshold when searching from the far field to the near field. N is an integer greater than 1. If the goodness of linear fit is greater than the first preset threshold and the standard deviation of slope is less than the second preset threshold, then the segment is determined to be smooth. The initial far-field boundary value is calculated based on the fitted slope of this segment.

3. The method according to claim 2, characterized in that, The method further includes: If the condition that the goodness of linear fit is greater than the first preset threshold and the standard deviation of the slope of adjacent points is less than the second preset threshold is not met, then the window is slid back by one distance point, and linear fit is performed on the new N distance points until a smooth segment that meets the conditions is found.

4. The method according to claim 1, characterized in that, The method further includes: If the inner layer does not converge, the far-field boundary values ​​are updated based on the near-field physical constraints until the inner layer converges.

5. The method according to claim 4, characterized in that, The update of far-field boundary values ​​based on near-field physical constraints includes: If the physical judgment of the extinction coefficient profile is unreasonable, the current far-field boundary value is updated according to the gain factor. If the physical judgment of the extinction coefficient profile is reasonable, but the average value of the extinction coefficient profile in the near field region has not converged, then the current far field boundary value is fine-tuned based on the relative change of the average value of the extinction coefficient profile in the near field region.

6. The method according to claim 5, characterized in that, The method further includes: Determine whether the smoothness of the optimal extinction coefficient profile in the near-field region satisfies the condition that the linear fit goodness is greater than a first preset threshold and the slope standard deviation is less than a second preset threshold. If the conditions are not met, the next round of inner layer iteration will be performed based on the updated far-field boundary values.

7. The method according to claim 1, characterized in that, The calculation of the near-field average backscattering coefficient based on the inner layer optimal extinction coefficient profile includes: （7）； in, Represents the near-field average backscattering coefficient. Indicates the detection distance. , Indicates the starting distance of the near-field region. Indicates the end distance of the near-field region. Indicates bidirectional transmittance. This represents the optimal extinction coefficient profile. This indicates the distance correction signal.

8. The method according to claim 1, characterized in that, The calculation of the new K value based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient includes: （8）； in, This represents the new K value. Represents the near-field average backscattering coefficient. This represents the average value of the extinction coefficient profile over the near-field region.

9. The method according to claim 1, characterized in that, The method further includes: When the outer layer is iterated for the first time, a preset perturbation is applied to the average value of the extinction coefficient profile in the near-field region, and the inner layer iteration is re-executed. Determine whether the iteration result can still converge to the vicinity of the original solution. If it can, then perform the outer iteration. If not, readjust the parameters and initialize.

10. A two-layer iterative lidar visibility inversion system based on near-field constraints and dynamic K-value inversion, characterized in that, The system includes: An initialization module is used for parameter initialization, wherein the parameters include at least the near-field region range, initial guess of K value, initial far-field boundary value, extinction coefficient convergence threshold, and K value convergence threshold; The inner optimization module is used to start the inner iterative loop under the initial guess of K value and the initial far-field boundary value to optimize the far-field boundary value; The optimal value calculation module is used to determine inner layer convergence when the relative change of the average value of the extinction coefficient profile in the near-field region is less than the extinction coefficient convergence threshold and meets the physical rationality requirement. It obtains the inner layer optimal extinction coefficient profile and the average value of the optimal extinction coefficient profile in the near-field region under the current K value. The extinction coefficient profile is calculated based on the current far-field boundary value using the Klett backward integral formula. The physical rationality means that the extinction coefficient profile changes smoothly. The near-field average backscattering coefficient calculation module is used to calculate the near-field average backscattering coefficient based on the inner layer optimal extinction coefficient profile shown. The K-value calculation module is used to calculate a new K-value based on the average value of the optimal extinction coefficient profile in the near-field region and the near-field average backscattering coefficient. The outer optimization module is used to achieve outer convergence when the relative change of K is less than the K convergence threshold; otherwise, the inner iteration is restarted under the new K value until both the inner and outer layers converge. The visibility calculation module is used to calculate atmospheric visibility based on the extinction coefficient profile and K value obtained from the last iteration.

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