Safe firing area projection method for mobile operation site in artificial influence weather

Abstract

The invention discloses a safe firing area projection method for an artificial influence weather mobile operation station. The method comprises the following steps: calculating an environment transmission attenuation index according to environment basic attenuation data; calculating a medium scattering interference index according to the environment medium scattering interference data; the effective projection data, the environment transmission attenuation index and the medium scattering interference index are comprehensively analyzed, and the effective projection contrast is calculated; calculating a dynamic mode weight according to the parameters; comparing the dynamic mode weight with a threshold value in a weather conversion threshold value set, judging an environment state of the target location, and selecting a corresponding projection mode according to the environment state; determining a safe firing area image cutting, terrain distortion correction and splicing fusion scheme according to the positioning and north setting information; the problem that a fixed projection mode is difficult to cope with a complex and changeable meteorological environment and consequently the projection definition of the firing area is difficult to guarantee is solved, a safe firing area graph is accurately projected to the surface of the rugged topography, and visual deformation caused by the topography is eliminated.

Description

Technical Field

[0001] This invention relates to the field of safe field projection, specifically a method for safe field projection at mobile weather modification sites. Background Technology

[0002] With global climate change and the increasing frequency of extreme weather events, the demand for water resource allocation, agricultural production enhancement and disaster prevention, and ecological environment improvement is becoming increasingly urgent. Weather modification (hereinafter referred to as "modification") operations, as an important means of regulating regional climate and preventing meteorological disasters, play a crucial role in agricultural production, ecological protection, and disaster prevention. Currently, ground-based modification equipment, with its wide coverage and flexible operational characteristics, has become the mainstay of modification operations, undertaking important tasks such as artificial rain enhancement and hail suppression.

[0003] Operational safety is paramount in weather modification work, with the accurate delineation of safe firing boundaries on the ground being particularly crucial. At fixed weather modification sites, safe firing boundaries are typically marked with ground paint. By establishing standardized safe firing boundary marking areas, the ballistic safety zone of the operational equipment is precisely defined, ensuring that the launch trajectory of weather modification operations remains within a controlled and safe range throughout the entire process. This effectively prevents accidental injuries caused by ammunition deviating from its trajectory, creating a safety barrier for operators, surrounding residents, and facilities. However, for mobile operation sites, whose locations may be on highways, in rural areas, at weather stations, or even in scenic areas, traditional ground paint marking methods are not feasible. The current solution involves carrying paper or electronic safe firing boundary maps in the vehicle, with operators relying on visual judgment and confirmation of the safe firing boundary. This method is not only inefficient but also prone to human error, posing significant safety hazards and failing to meet the stringent safety and accuracy requirements of modern weather modification operations.

[0004] Furthermore, common single-device projection technologies also have significant limitations when dealing with safe projection of the traverse at mobile work sites. Since mobile weather modification sites require safe projection of the traverse around the vehicle, the projection system must possess precise north-south and positioning capabilities. However, existing single-device projection technologies struggle to simultaneously meet the requirements of high-definition projection, accurate image stitching, and terrain adaptive correction under complex and variable environmental conditions, especially in adverse weather conditions such as cloudy, overcast, and rainy days, as well as in non-horizontal terrain. This makes it impossible to provide workers with clear, accurate, and reliable safe traverse guidance, severely restricting the safety and effectiveness of mobile weather modification operations. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a method for projecting a safe ray boundary at mobile weather modification sites, solving the problem of clear and accurate projection of the safe ray boundary map under different weather conditions and terrain variations.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for projecting a safe radiant field for mobile weather modification operation sites, comprising:

[0009] A method for projecting a safe radiant field for mobile weather modification sites includes the following steps:

[0010] Step 1: Obtain the environmental baseline attenuation data of the target location through environmental data acquisition equipment, and analyze the environmental baseline attenuation data to obtain the Environmental Transmission Attenuation Index (ETI).

[0011] Step 2: Acquire medium scattering interference data at the target location using acquisition equipment, and analyze the environmental medium scattering interference data to obtain the Medium Scattering Interference Index (MSI).

[0012] Step 3: Acquire effective projection data of the target location through acquisition equipment, and comprehensively analyze the effective projection data, environmental transmission attenuation index (ETI), and medium scattering interference index (MSI) to obtain the effective projection contrast (EPC).

[0013] Step 4: Calculate the dynamic mode weight W by using the ambient transmission attenuation index ETI, the medium scattering interference index MSI, and the effective projection contrast ratio EPC. mode ;

[0014] Step 5: Set the weather transition threshold set and assign dynamic mode weights W. mode The system compares the target location with the thresholds in the weather conversion threshold set to determine the environmental state of the target location and selects the corresponding projection mode based on the environmental state.

[0015] Step Six: Define the global geographic coordinate system and model vehicle parameters;

[0016] Step 7: Construct a dynamic allocation model for vehicle projection viewpoints;

[0017] Step 8: Achieve high-precision correction through terrain data preprocessing, ray tracing modeling, and perspective transformation calculation;

[0018] Step 9: Achieve natural stitching of images from adjacent projection devices through overlapping region detection, feature matching optimization, and weighted fusion calculation.

[0019] Furthermore, the environmental baseline attenuation data includes atmospheric transmittance τ and aerosol concentration C. aand background illuminance L b ;

[0020] The Environmental Transmission Attenuation Index (ETI) is calculated using environmental baseline attenuation data, based on the following formula:

[0021]

[0022] Where e is the base of the natural logarithm; k1 represents the aerosol attenuation coefficient; and L0 is the reference illuminance value.

[0023] Furthermore, the medium scattering interference data includes the scattering coefficient σ. s Cloud optical thickness δ c and visibility change rate δ v ;

[0024] The formula used to calculate the Medium Scattering Interference Index (MSI) from medium scattering interference data is as follows:

[0025]

[0026] Where v0 is the visibility attenuation threshold and ρ is the surface reflectance.

[0027] Furthermore, effective projection data includes the intensity I of the projection light source. P and background brightness I b The effective projection contrast ratio (EPC) is calculated through comprehensive analysis, and the calculation formula is as follows:

[0028]

[0029] Where k2 is the scattering correction factor.

[0030] Furthermore, the effective projection data includes the cloud movement vector V. 云 and ground wind speed vector V 地面 Specifically:

[0031] By continuously monitoring cloud movement using weather radar, the cloud movement vector V is obtained in real time. 云 The surface wind speed vector V is obtained by measuring and recording wind speeds using the wind measuring equipment at the meteorological station. 地面 .

[0032] Furthermore, the dynamic mode weights W are calculated. mode The formula used is as follows:

[0033]

[0034] Where α is an empirical parameter.

[0035] Furthermore, the method for selecting the corresponding projection mode based on the environmental conditions is as follows:

[0036] The weather transition threshold set includes cloudy transition thresholds and rain / fog transition thresholds;

[0037] The dynamic mode weight W mode The dynamic mode weight W is compared with the cloudy transition threshold and the rain / fog transition threshold, respectively. mode > When the cloudy transition threshold is reached, select the sunny projection mode; when the rain / fog transition threshold is less than or equal to the dynamic mode weight W. mode When the cloud cover projection mode is ≤, select the cloud cover projection mode; when the dynamic mode weight W mode When the rain / fog transition threshold is reached, select the rain / fog projection mode.

[0038] Furthermore, the image cropping strategy based on vehicle structure includes cropping according to the vehicle's aspect ratio. The location of the launching device is determined using a non-uniform viewing angle: the front area covers a wide angle, while the single device viewing angle is [not specified].

[0039] The rear area of ​​the vehicle needs to be covered as the launching device is located there; single device viewpoint.

[0040] Single device perspective θ in the middle of the vehicle body side =60°-θ head -θ tail

[0041] Convert the vehicle coordinate system view to the geographic coordinate system, where the clipping formula is:

[0042]

[0043] Furthermore, the terrain data extraction uses the center coordinates (x0, y0, z0) of the rocket launch device as the origin, obtains a digital elevation model (DEM) from the GIS system, and extracts a local area with a radius of R (e.g., R = 50m):

[0044] DEN sub =Clip(DEM,[x0-R,y0-R,x0+R,y0+R])

[0045] Simultaneously, the DEM data is converted into a 3D point cloud format.

[0046]

[0047] Where N is the number of point clouds;

[0048] Terrain area priority is determined based on the Euclidean distance from the terrain point to the launching device.

[0049] The region is divided into three levels:

[0050] Near region (d ≤ 10 m): Sub-pixel light field sampling is adopted (sampling interval Δθ ≤ 0.05°, )

[0051] Middle region (10 m < d ≤ 30 m): Conventional sampling (Δθ = 0.1°, )

[0052] Far region (d ≥ 30 m): Low-precision sampling (Δθ = 0.2°, )

[0053] Sampling density formula:

[0054] <​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0063] To avoid color inconsistencies, brightness equalization can be further introduced:

[0064] Mean matching: Calculate the average brightness μ of the overlapping region. i and μ i+1 , to I″ i+1 Adjust the brightness:

[0065]

[0066] Final fusion: using the adjusted I″′ i+1 Perform pixel blending.

[0067] (III) Beneficial Effects

[0068] This invention provides a method for safe radiant projection at mobile weather modification sites, which has the following advantages:

[0069] (1) Environmental attenuation data of the target location was acquired and analyzed using environmental data acquisition equipment to obtain the environmental transmission attenuation index, and medium scattering interference data was acquired and analyzed to obtain the medium scattering interference index. This achieved precise quantification of environmental factors. The environmental transmission attenuation index accurately reflects the degree of attenuation of the signal during transmission, while the medium scattering interference index clearly defines the scattering interference effect of different media in the environment on the projection of the ray field. In weather modification operations, the accuracy of signal propagation is directly related to the positioning accuracy of the equipment on the target cloud area. By accurately acquiring these two indices, the ray field deviation caused by environmental factors can be effectively reduced, making the ray field projection more consistent with the actual environmental conditions. This solves the problem that fixed projection modes are difficult to cope with complex and changeable meteorological environments, cannot achieve the best ray field projection effect under different weather conditions, and thus cannot guarantee the clarity of the ray field projection.

[0070] (3) The dynamic mode weight is used to determine the environmental state and select the corresponding projection mode, realizing the dynamic adaptive selection of the projection mode. In actual operation, the weather conditions are constantly changing, and the suitable projection mode is different under different weather conditions. By calculating the dynamic mode weight, multiple key parameters such as environmental transmission attenuation index, medium scattering interference index, effective projection contrast and operation safety factor are comprehensively considered, which can reflect the projection requirements and operation conditions under the current environment in real time. Setting a weather conversion threshold set provides a clear judgment standard for mode selection. When the dynamic mode weight is compared with the threshold, the environmental state of the target location can be accurately determined, and then the matching projection mode can be selected quickly and intelligently. This dynamic mode selection mechanism greatly improves the flexibility and adaptability of the safe radiant projection of the mobile weather modification operation site, enabling it to better cope with complex and changeable meteorological environments, ensuring that the optimal radiant projection method can be used under different weather conditions, and improving the projection effect.

[0071] (4) By using positioning and north-fixing information, an image cropping strategy based on vehicle structure is established. Through terrain distortion correction and stitching fusion enhancement, multiple projection devices work together to accurately project the safety field map onto the ground with the working device as the center. This technology solves the image distortion problem of safety field projection under undulating terrain. Attached Figure Description

[0072] Figure 1 This is a schematic diagram illustrating the steps of a method for safe ray projection at mobile weather modification sites according to the present invention. Detailed Implementation

[0073] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0074] Example 1

[0075] Please see Figure 1 This invention provides a method for safe radiant projection at mobile weather modification sites, comprising:

[0076] Step 1: Obtain the environmental baseline attenuation data of the target location through environmental data acquisition equipment, and analyze the environmental baseline attenuation data to obtain the Environmental Transmission Attenuation Index (ETI).

[0077] It should be noted that in the process of calculating the Environmental Transmission Attenuation Index (ETI), all parameters involved in each calculation step need to be normalized and preprocessed to eliminate the dimensions of different parameters, so as to facilitate subsequent formula calculations.

[0078] Environmental baseline attenuation data include atmospheric transmittance τ and aerosol concentration C. a and background illuminance L b .

[0079] Step 101: Obtain surface temperature, surface atmospheric pressure, and temperature and pressure data of the vertical atmospheric profile at the target time and location from meteorological stations near the work site; if the meteorological station does not have vertical data, a standard atmospheric model can be used for simulation, such as the standard atmosphere in mid-latitude summer. Then, obtain the surface water vapor pressure from the meteorological station, or calculate the water vapor content of the entire atmospheric layer through radiosonde data. Input the data obtained from the meteorological station into the MODTRAN model, select the corresponding aerosol type and concentration, and obtain the atmospheric transmittance τ at the target location;

[0080] It should be noted that the MODTRAN model is a well-known professional model widely used in the field of atmospheric radiative transfer.

[0081] Step 102: Use a lidar system to acquire backscattered echo signal intensity data at different altitudes, and calculate the aerosol concentration C based on the Mie scattering theory algorithm. a Alternatively, the aerosol concentration C can be indirectly obtained by measuring the turbidity of the atmosphere. a .

[0082] Step 103: Use a lux meter to measure the illuminance at different locations and heights around the work site, and select representative measurements as the background illuminance; for example, if the work requires high uniformity of illumination, the average of multiple measurements can be selected as the background illuminance L. b If the task focuses more on the illumination at a specific height or in a particular area, then the background illuminance L is taken from the measurements at that location and height. b .

[0083] Step 104: Calculate the Environmental Transmission Attenuation Index (ETI) using the basic environmental attenuation data. The formula used is as follows:

[0084]

[0085] Where e is the base of the natural logarithm; k1 represents the aerosol attenuation coefficient, which reflects the change in light attenuation caused by a unit change in aerosol concentration; and L0 is the reference illuminance value.

[0086] It should be noted that the sol attenuation coefficient k1 can be obtained through actual measurement or model calculation based on the measurement methods and typical value frameworks provided by standards such as QX / T and ISO 28439. For those in the field, the lidar equation, Mie scattering theory, and MODTRAN parameters are common knowledge, and a value of 500 can be taken here.

[0087] The reference illuminance value L0 can be given directly according to standards such as GB 50034 and IESNA RP-27, which are well-known standards. Here, the value can be taken as 10000 lux.

[0088] It should be noted that τ in the formula describes the atmosphere's ability to transmit light, reflecting the proportion of light that is not attenuated by atmospheric absorption, scattering, etc., as it propagates through the atmosphere. Its value ranges from 0 to 1. The closer τ is to 1, the less obstruction the atmosphere provides to light, and the easier it is for light to propagate through the atmosphere. As a fundamental factor, τ directly affects the ETI (Electronic Tolerance) value and is a key parameter for measuring the impact of basic atmospheric light transmission characteristics on the transmission of projected light. In clear, clean weather, a high τ value results in a relatively large ETI, indicating that the projection is less affected by atmospheric attenuation, and the projection across the ray is more clearly presented. This helps operators judge the effectiveness of the projection and ensures safe operation. In hazy weather, a low τ value results in a small ETI, indicating a strong environmental shading effect on the projection. This demonstrates the exponential relationship between aerosol concentration and light attenuation; as C... a Increase Increase The higher the aerosol concentration, the more severe the light attenuation, and the more pronounced the weakening effect of this exponential term on ETI. (Fractional term) In the middle, when L b Increase (i.e., brighten the ambient background light), Increasing the value of the fraction decreases the overall value. This fraction measures the impact of background light brightness on the projection occlusion effect; the brighter the background light, the greater the interference with the projection, and the smaller the ETI. This method effectively quantifies the impact of background illuminance on projection occlusion. In strong daylight conditions, L... b Larger values ​​indicate smaller fractional terms; in low-light conditions such as at night or on cloudy days, L... b A smaller value for the fractional term and a larger value for ETI indicate less interference from background light on the projection, making the spectral projection clearer. τ reflects the atmospheric basic light transmittance. This reflects the light attenuation caused by aerosol concentration. The ETI, which is the product of the background light brightness and the three factors, reflects the degree of influence of environmental factors on the transmission of projected light and the visibility of the projection field. The ETI value ranges from 0 to 1, and the lower the value, the stronger the environmental interference.

[0089] Step 2: Acquire medium scattering interference data at the target location using acquisition equipment, and analyze the environmental medium scattering interference data to obtain the Medium Scattering Interference Index (MSI).

[0090] It should be noted that in the process of calculating the medium scattering interference index (MSI), all parameters involved in each calculation step need to be normalized and preprocessed to eliminate the dimensions of different parameters, so as to facilitate subsequent formula calculations.

[0091] Medium scattering interference data includes scattering coefficient σ s Cloud optical thickness δ cand visibility change rate δ v .

[0092] Step 201: Use an integrating nephelometer. This instrument measures the intensity of scattered light of a specific wavelength within a given volume of atmosphere and calculates the scattering coefficient using its built-in algorithm. For example, at an artificial weather modification site, the integrating nephelometer is placed at the target location, and the intensity of scattered atmospheric light at different times is continuously measured. The scattering coefficient σ is then directly obtained after processing by the instrument. s The value.

[0093] Step 202: Using a cloud lidar, a laser beam is emitted into the cloud layer. Based on the scattered echo signal of the laser beam traveling back and forth within the cloud, and by analyzing the echo intensity, time delay, and other information, combined with the lidar equations, the optical thickness of the cloud layer can be obtained. By deploying cloud lidar around the work site, changes in the cloud layer in the upper atmosphere are monitored in real time, and the optical thickness δ of the cloud layer is obtained. c The data.

[0094] Step 203: Continuously measure visibility data using a forward-scattering visibility meter or a transmission visibility meter. Process the visibility values ​​measured at different times and calculate the visibility change rate δ per unit time. v The formula can be expressed as: Where V t0 V t1 These are the visibility at the initial time and subsequent time, respectively, such as t1-t0=1, used to calculate the attenuation rate per minute.

[0095] Step 204: Calculate the Medium Scattering Interference Index (MSI) using the medium scattering interference data. The formula used is as follows:

[0096]

[0097] Where v0 is the visibility attenuation threshold and ρ is the surface reflectance.

[0098] It should be noted that a portable ground object spectrometer is used, which is vertically aligned with the ground surface at the work site to measure the reflectance spectrum. The surface reflectance ρ is obtained through data processing within the instrument.

[0099] It should be noted that the scattering coefficient σ s Incorporating MSI into the calculation allows for a precise characterization of the interference effect of the atmospheric medium's fundamental scattering capabilities on the ray projection, σ s A high value indicates a relatively large MSI, suggesting strong interference from medium scattering on the projection of the radiation field.

[0100] σ s A low value indicates a small MSI, suggesting that the ray projection is less affected by scattering interference; in the MSI formula, δc The larger the cloud, the more pronounced its blocking and attenuation effect on light; the greater the energy loss of light after passing through the cloud, the more difficult it is to clearly project the ray onto the horizon under the influence of the cloud. δ c With σ s The combined effect of these factors on the projected light rays is reflected in the combined interference of atmospheric media (clouds as a special large-scale medium) and other scattering media. In the middle, when δ v Increase (i.e., visibility decreases rapidly), An increase in visibility increases the overall value of the term. This part measures the dynamic impact of the rate of change in visibility on the interference of the traverse projection. The faster the visibility decays, the more severe the interference with the traverse projection, leading to an increase in the MSI. The formula incorporates ρ... 0.5 Afterwards, it is possible to accurately characterize the impact of surface reflection characteristics on the interference of the projection field. When operating in a high-reflectivity surface environment, ρ is large, ρ 0.5 A high MSI (Mean Scattering Indicator) indicates strong interference from ground reflections in the ray projection. Comprehensive calculation of the MSI allows for a complete and accurate quantification of the interference caused by medium scattering and related environmental factors on the ray projection. Based on the MSI value, operators can clearly understand the overall interference situation of the ray projection under the current environment: a lower MSI indicates less interference from medium scattering; a higher MSI indicates strong interference, requiring appropriate measures to ensure the ray's identifiability.

[0101] Step 3: Acquire effective projection data of the target location using acquisition equipment, and comprehensively analyze the effective projection data, environmental transmission attenuation index (ETI), and medium scattering interference index (MSI) to obtain the effective projection contrast (EPC).

[0102] It should be noted that in the process of calculating the effective projection contrast (EPC), all parameters involved in each calculation step need to be normalized and preprocessed to eliminate the dimensions of different parameters, so as to facilitate subsequent formula calculations.

[0103] Effective projection data includes the intensity of the projection light source I. P and background brightness I b .

[0104] Step 301: Using a luminance meter, such as a spectroradiometer, with the projection equipment working normally and projecting a safe field of view pattern, point the luminance meter probe at the projected light and measure the brightness of the projected light in a specific area (such as the light projected onto a work site sign) to obtain the intensity I of the projected light source. P Alternatively, the technical specifications or parameter tables of the projection equipment will list the relevant parameters for its light source intensity. The projection light source intensity (I) can be obtained directly from the information provided by the equipment manufacturer. P The value.

[0105] Step 302: Using a luminance meter, select multiple locations at the work site, such as the center of the work area or open areas in different directions around it, and measure the brightness of the ambient background when the projector is off or the influence of the projected light on the measurement area is negligible. For example, if the work requires high uniformity of background brightness, the average of multiple measurements can be selected as the background brightness I. b If the task focuses more on the background brightness at a specific point in time, then the measured value at that specific time point should be used as the background brightness I. b .

[0106] Step 303: Based on the effective projection data, the environmental transmission attenuation index (ETI), and the medium scattering interference index (MSI), a comprehensive analysis is performed to obtain the effective projection contrast ratio (EPC). The calculation formula is as follows:

[0107]

[0108] Where k2 is the scattering correction factor;

[0109] The scattering correction factor k2 can be determined through numerous simulation experiments and actual tests at various weather modification sites. By varying the scattering conditions of different media (such as different aerosol concentrations and cloud thicknesses, corresponding to different MSI values), and measuring the actual changes in effective projection contrast under these conditions, the coefficient value that can reasonably correct for the impact of scattering interference can be determined using methods such as data fitting and regression analysis. Here, k2 can be set to 0.8.

[0110] It should be noted that I in the formula P -I b ETI represents the "inherent contrast" of the projected light relative to the background light, that is, the difference in brightness between the projected light and the background without considering environmental factors such as the atmosphere; ETI is related to I... P -I b Multiplication reflects the correction of environmental transmission attenuation to the inherent contrast of the projection; that is, the difference in brightness between the actual projected light reaching the observation point and the background light after considering environmental factors. Dividing by I b This is to normalize this brightness difference to the scale of background brightness, obtain the contrast ratio relative to the background brightness, and make the projection contrast comparable under different background brightness environments. This study comprehensively considers the effects of projection light source, background light and environmental transmission attenuation on the inherent contrast of the projection, and calculates the initial contrast of the projection relative to the background under the influence of the environment. This term is used to further correct the impact of medium scattering interference on the projection contrast. Medium scattering causes the projected light to scatter, resulting in dispersed light energy and blurred edges of the projection horizon, thus reducing the projection contrast. The larger the value of k2, the stronger the weakening effect of medium scattering on the projection contrast. The smaller the value, the greater the correction to the projection contrast. This reflects a reasonable downward adjustment of the initially calculated projection contrast after considering media scattering interference, in order to more accurately reflect the actual identifiable contrast. This effectively corrects the impact of medium scattering interference on the contrast of the projection, making the calculated EPC closer to the actual identifiable contrast. In environments with strong medium scattering, k2 is large. A smaller value for k2 results in a corresponding decrease in EPC, indicating to operators that the ray projection is significantly affected by scattering, leading to low contrast. Measures (such as optimizing the projection anti-scattering algorithm and increasing the directionality of the projection light source) are needed to improve the ray visibility. In environments with weak medium scattering, a smaller k2 value indicates that... A higher EPC value indicates that the radiant projection is less affected by scattering, has high contrast, and is suitable for normal operation. The introduction of this correction term improves the accuracy of EPC calculation, providing a more reliable basis for operational decisions. By comprehensively calculating EPC, the effective contrast of the radiant projection in the actual working environment can be quantified comprehensively and accurately. Based on the EPC value, operators can clearly understand the identifiability of the radiant projection in the current environment.

[0111] According to the rules of vector operations, first obtain V. 云 and V 地面 The specific vector value is then calculated using vector subtraction and the modulus formula. Let V be... 云 =(v 云x v 云y V 地面 =(v 地面x v 地面y 0, then

[0112] Step 5: Calculate the dynamic mode weight W by using the ambient transmission attenuation index (ETI), medium scattering interference index (MSI), and effective projection contrast (EPC). mode The formula used is as follows:

[0113]

[0114] Where α is an empirical parameter.

[0115] It should be noted that the empirical parameter α can be determined through experimental testing, data fitting, and the actual needs of weather modification operations. The specific approach is as follows: At mobile weather modification sites, design multiple sets of experiments to simulate different environmental conditions (such as different aerosol concentrations, cloud thicknesses, and projection contrasts). Collect environmental transmission attenuation index (ETI), medium scattering interference index (MSI), and effective projection contrast (EPC), and label the mode decision results, such as "whether the projection mode needs to be enhanced." Optimize α using multiple linear regression or machine learning algorithms (such as random forests and gradient boosting) to make the formula... Output W mode The best match is to the actual model decision-making needs. For example, set an initial value for α (e.g., 0.1, 0.2, ..., 1.0), and for each set of experimental data, substitute it into the formula to calculate W. mode Compared to W mode The model decision results are compared with those of the labeled model (e.g., using a confusion matrix to evaluate prediction accuracy); the α that maximizes the accuracy is selected, and finally the optimal empirical weight of α is determined by statistically analyzing multiple sets of experiments, where a value of 0.5 can be taken.

[0116] It should be noted that, This method quantifies the deep coupling of environmental transmission, scattering, and operational safety, providing a direct understanding of the basic adaptability of the projection field under the combined influence of environment and operational safety. In clear weather (high ETI) and low scattering (low MSI) environments, a high value indicates good basic projection field conditions, allowing for mode adjustments towards conventional and efficient modes. In hazy weather (low ETI, high MSI), a low value warns of the need to strengthen projection mode compensation to ensure a clear projection field and improve the scientific basis of mode decisions and operational safety. With the addition of α·EPC, the dynamic mode weights simultaneously consider three dimensions: environment, safety, and the projection itself. Operators can adjust mode strategies in real time based on EPC: when EPC is low, even... It's acceptable; however, including α·EPC will also lower W. mode The system prompts that the projection mode needs to be enhanced; when EPC is high, the advantages of the regular mode can be strengthened. Through α-adaptation to different work scenarios, it accurately balances the impact of the projection's own characteristics and environmental safety, improving the accuracy of mode adjustments and work effectiveness.

[0117] Step Six: Set the weather transition threshold set and assign dynamic mode weights W. mode The system compares the target location with the thresholds in the weather conversion threshold set to determine the environmental state of the target location, and selects the corresponding projection mode based on the environmental state.

[0118] Step 601: Set the weather transition threshold set, which includes the cloudy weather transition threshold and the rain / fog transition threshold.

[0119] Step 602: Adjust the dynamic mode weights W modeThe dynamic mode weight W is compared with the cloudy transition threshold and the rain / fog transition threshold, respectively. mode > When the cloudy transition threshold is reached, select the sunny projection mode; when the rain / fog transition threshold is less than or equal to the dynamic mode weight W. mode When the cloud cover projection mode is ≤, select the cloud cover projection mode; when the dynamic mode weight W mode When the rain / fog transition threshold is reached, select the rain / fog projection mode.

[0120] It should be noted that the method for determining the weather transition threshold set is as follows: Obtain operational data from the past three years or more, which may include raw values ​​from meteorological sensors (τ, C...). a L b δ v (etc.), projection recognition success rate, and operational effectiveness, etc. Calculate W for each group of sample data in the historical data. mode Label the actual weather type (based on satellite cloud imagery and visibility meter readings), and analyze W. mode The curve showing the relationship between the projection recognition success rate and the accuracy of the projection recognition is taken from the point of sudden change in recognition rate, such as the inflection point from sunny day to cloudy day: W mode When the value is 1.2, the recognition rate drops sharply from 95% to 85%, so this is taken as the threshold for the transition from cloudy to rainy / foggy weather: W mode When the value is 0.8, the recognition rate drops sharply from 80% to 60%, so this value is used as the threshold for rain-fog transition.

[0121] Step 603: Real-time monitoring of background illuminance L b When the ambient light intensity is greater than 100,000 lux, the sunny mode will be automatically activated.

[0122] Specifically, when selecting the sunny day projection mode, a laser projector with ≥20,000 lumens is used, along with a polarizing filter, to suppress glare interference caused by direct sunlight; red-blue dual-color markings are used to distinguish between no-light and permitted areas, and color difference is used to enhance recognizability (e.g., red marks high-voltage line no-light zones, and blue marks safe light zones); the projection contrast is adjusted according to the surface reflectivity ρ to avoid image fading on light-colored surfaces (such as sand).

[0123] When selecting the cloudy projection mode, infrared thermal imaging (identifying personnel / vehicle activity) and radar echo (real-time cloud position) are superimposed to solve the problem of low contrast on cloudy days; the screen material uses microprism reflective material to improve brightness gain and compensate for edge blurring caused by insufficient light.

[0124] When selecting the rain and fog projection mode, millimeter-wave radar-assisted positioning is enabled to generate a virtual ray grid that penetrates the water mist to project images; sonar feedback calibration is enabled to correct image distortion caused by raindrop scattering.

[0125] Step Six: Define the global geographic coordinate system and model vehicle parameters;

[0126] Global geographic coordinate system

[0127] Origin: Center of rocket launch device (x0, y0, z0)

[0128] Azimuth reference: North is 0°, and the direction of increasing angle is clockwise.

[0129] Vehicle local coordinate system

[0130] origin

[0131] Rocket Launching Device Center

[0132] Coordinate axis direction:

[0133] X-axis: Points in the direction of the train's heading (determined by the fixed north angle α).

[0134] Y-axis: Perpendicular to the X-axis and pointing to the right.

[0135] Z-axis: Vertical upward

[0136] Vehicle structural parameters

[0137] Dimensions: Length L, Width W

[0138] Launcher location: Located slightly rear-middle of the vehicle, with the offset δ from the rear of the vehicle as a percentage of the vehicle length, e.g., δ = 0.3.

[0139] Projection device layout:

[0140] Front sides: Left front (LF), Right front (RF)

[0141] Rear sides: Left rear (LB), Right rear (RB)

[0142] The two sides of the middle section of the vehicle body: left center (LM), right center (RM)

[0143] Step 7: Construct a dynamic allocation model for vehicle projection viewpoints; employ an image cropping strategy based on vehicle structure and aspect ratio. The location of the launching device is divided using a non-uniform viewing angle:

[0144] Front area (LF, RF): Covers a wide angle in front, single-device view.

[0145] Rear area (LB, RB): Due to the location of the launching device, this area requires focused coverage; single-device view.

[0146] Mid-section of vehicle body (LM, RM): Single-device perspective θ side =60°-θ head -θ tail

[0147] Viewpoint range calculation (vehicle coordinate system)

[0148]

[0149] Geographic coordinate system transformation

[0150] Convert the vehicle coordinate system perspective to the geographic coordinate system:

[0151] θ geo =(θ veh +α)mod 360°

[0152] Cutting formula

[0153]

[0154] Terrain distortion correction and enhancement scheme

[0155] The system accurately projects a safety horizon map onto the undulating terrain surface, eliminating visual distortions caused by the terrain. High-precision correction is achieved through three core steps: terrain data preprocessing, ray tracing modeling, and perspective transformation calculation, combined with light field rendering technology.

[0156] Step 8: Achieve high-precision correction through terrain data preprocessing, ray tracing modeling, and perspective transformation calculation;

[0157] Terrain data extraction

[0158] Using the center coordinates (x0, y0, z0) of the rocket launch device as the origin, obtain the digital elevation model (DEM) from the GIS system, and extract a local area with a radius of R (e.g., R = 50m):

[0159] DEM sub =Clip(DEM,[x0-R,y0-R,x0+R,y0+R])

[0160] Simultaneously, the DEM data is converted into a 3D point cloud format.

[0161]

[0162] Where N is the number of point clouds.

[0163] Terrain region priority classification

[0164] Based on the Euclidean distance from the terrain point to the launching device The region is divided into three levels:

[0165] Near-field (d≤10m): Sub-pixel level light field sampling is used (sampling interval Δθ≤0.05°). )

[0166] Central region (10m < d ≤ 30m): Conventional sampling (Δθ = 0.1°, )

[0167] Far region (d ≥ 30m): Low-precision sampling (Δθ = 0.2°, )

[0168] Sampling density formula:

[0169]

[0170] Light field-based ray tracing modeling

[0171] Projection ray equation construction

[0172] For the pixel (u, v) in the image of the i-th projection device, its projection point P0 on the ideal plane (without terrain distortion) can be calculated through the internal parameter matrix K i Calculate:

[0173]

[0174] Taking the optical center of the projection device as the starting point, construct the ray vector

[0175]

[0176] Then the ray equation is:

[0177]

[0178] Solving the intersection of the ray and the terrain

[0179] Use the bisection method to iteratively calculate the intersection of the ray R(t) and the terrain surface DEM sub Intersection point:

[0180] (1) Determine the initial interval: Let the intersection interval of the ray and the terrain bounding box be [t min , t max .

[0181] (2) Iterative solution:

[0182] Calculate the midpoint Get the ray point R(t m ) = (x m , y m , z m )

[0183] Obtain the terrain height z corresponding to this point through bilinear interpolation dem = BilinearInterp(DEM sub , x m , ym ).

[0184] According to z m With z dem Size relationship update interval:

[0185] If z m >z dem , then t max =t m

[0186] If z m <z dem , then t min =t m

[0187] (3) Termination condition: When |z m -z dem When |<∈ (e.g., ∈=0.01m), the intersection point is obtained as P=R(t). m ).

[0188] Enhanced light in the rear area

[0189] For the rear-end devices (LB, RB), increase the density of light sampling in the vertical direction:

[0190] Vertical sampling interval of conventional devices:

[0191] Vertical sampling interval of the rear device:

[0192] Sampling quantity formula:

[0193] Perspective Transformation and Image Correction

[0194] Homography matrix calculation

[0195] Calculate the homography matrix H from the ideal plane to the actual terrain surface. i :

[0196]

[0197] in:

[0198] K i Let i be the intrinsic parameter matrix of device i

[0199] K0 is the ideal plane intrinsic parameter matrix.

[0200] [R i |t i Let ] be the extrinsic parameter matrix of device i relative to the terrain surface, which is solved through the following steps:

[0201] Select at least 4 sets of ideal plane points Xj Intersection with the terrain X′ j The matching pairs.

[0202] Solve H using the DLT (Direct Linear Transformation) algorithm. i The initial value.

[0203] Optimize H using RANSAC algorithm i Remove false matches.

[0204] Image correction and resampling

[0205] For the cropped image I i Applying the homography matrix H i Perform perspective transformation:

[0206] I i =Warp(I i ,Η i )

[0207] Bicubic interpolation is used to resample the transformed image to avoid pixel loss or jagged edges.

[0208]

[0209] B(x) is the basis function for cubic B-spline interpolation.

[0210] Error Compensation and Real-time Optimization

[0211] To further improve calibration accuracy, a closed-loop feedback mechanism is introduced.

[0212] Error detection

[0213] Control point C is set up on the ground. k =(x k ,y k ,z k ), compare the projection point C′ k Deviation from actual position ΔC k =C k -C′ k .

[0214] Parameter adjustment

[0215] Based on the error ΔC k The homography matrix H is optimized using the least squares method. i The parameters enable real-time correction.

[0216] The projection error caused by terrain distortion can be controlled to ≤2cm (plane) and ≤5cm (elevation), ensuring the geometric accuracy of the safety projection map on complex terrain.

[0217] Step 9: Achieve natural stitching of images from adjacent projection devices through overlapping region detection, feature matching optimization, and weighted fusion calculation.

[0218] To achieve natural stitching of images from adjacent projection devices, it is necessary to solve the problem of stitching gaps caused by differences in viewing angles and terrain distortions through overlapping area detection, feature matching optimization, and weighted fusion calculation.

[0219] According to the viewing angle range θ of each projection device i-start and θ i-end Calculate the overlap angle interval Δθ between adjacent devices i and i+1. i,i+1 :

[0220]

[0221] Wherein, ∈ is the preset overlap width (usually 5°-10°), used to ensure that adjacent images have sufficient overlapping area.

[0222] Dynamic weight function

[0223] To eliminate visual discontinuities at the splicing boundaries, a two-factor weighted model is introduced, comprehensively considering both angular and spatial distances:

[0224] ω i,i+1 (θ,d)=σ(θ)×β(d)

[0225] Angle weight σ(θ): A smooth transition weight based on the Sigmoid function, controlling the fusion strength in the angular direction.

[0226]

[0227] in, The center angle of the overlapping region is given by , and k is a parameter that controls the steepness of the transition (empirical value: k = 0.2-0.5).

[0228] Distance weight β(d): Based on the distance attenuation factor at the center of the transmitter, it reduces the fusion sensitivity of distant pixels.

[0229]

[0230] Where d is the ground projection distance from the pixel to the center of the rocket launch device (unit: meters), and λ is the attenuation coefficient (empirical value: λ = 0.001-0.005).

[0231] Multi-scale feature matching and geometric correction

[0232] Multi-scale SIFT feature extraction

[0233] To improve matching robustness, the pyramid multi-scale SIFT algorithm is adopted:

[0234] Image pyramid construction: for the corrected image I' i and I' i+1 Generate n-layer Gaussian pyramids (e.g., n=4).

[0235] Feature detection and description: SIFT feature points are extracted from each pyramid image layer, and a 128-dimensional descriptor F is generated. i,j and F i+1,j (j represents the pyramid level).

[0236] Cross-layer matching and filtering: Prioritize matching high-level (low-resolution) feature points, use RANSAC to remove mismatches, and then project the matching results to low-level (high-resolution) layers for fine-tuning.

[0237] Transformation matrix optimization calculation

[0238] Solve the problem from image I' using the RANSAC algorithm. i To I' i+1 The homography matrix H i,i+1 :

[0239] Random sampling: Randomly select 4 sets of points from the matched point pairs and calculate the initial homography matrix H. hyp .

[0240] Error assessment: Calculate the reprojection error e = ||x| for all matching points. i+1 -H hyp ·x i ||, where x i and x i+1 For the coordinates of the matching point.

[0241] Iterative optimization: Repeated sampling and evaluation, retaining the H with the smallest error. hyp As the final transformation matrix H i,i+1 .

[0242] Subpixel-level precision correction

[0243] Bicubic interpolation and affine fine-tuning are used to improve matching accuracy.

[0244] Bicubic interpolation: for the transformed image I″ i+1 =Warp(I' i+1 H i,i+1 Subpixel-level resampling is performed to reduce the jagged edge effect.

[0245] Affine fine-tuning: Fine-tuning H by minimizing the pixel mean square error (MSE) in the overlapping region. i,i+1 Translation parameters:

[0246]

[0247] Here, Δt is the translation vector, which is solved iteratively using the gradient descent method.

[0248] Pixel-level fusion computing

[0249] For pixels (θ, Φ) within the overlapping region, according to the dynamic weight ω i,i+1 (θ,d) Calculate the merged pixel value I fused (θ,Φ):

[0250] I fused (θ,Φ)=ω i,i+1 (θ,d)·I′ i (θ,Φ)+(1-ω i,i+1 (θ,d))I″ i+1 (θ,Φ)

[0251] To avoid color inconsistencies, brightness equalization can be further introduced:

[0252] Mean matching: Calculate the average brightness μ of the overlapping region. i and μ i+1 , to I″ i+1 Adjust the brightness:

[0253]

[0254] Final fusion: using the adjusted I″′ i+1 Perform pixel blending.

[0255] When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0256] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0257] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for projecting a safe radiant field for mobile weather modification operation sites, characterized in that, include: Step 1: Obtain the environmental baseline attenuation data of the target location through environmental data acquisition equipment, and analyze the environmental baseline attenuation data to obtain the Environmental Transmission Attenuation Index (ETI). Step 2: Acquire medium scattering interference data at the target location using acquisition equipment, and analyze the environmental medium scattering interference data to obtain the Medium Scattering Interference Index (MSI). Step 3: Acquire effective projection data of the target location through acquisition equipment, and comprehensively analyze the effective projection data, environmental transmission attenuation index (ETI), and medium scattering interference index (MSI) to obtain the effective projection contrast (EPC). Step 4: Calculate the dynamic mode weight W by using the ambient transmission attenuation index ETI, the medium scattering interference index MSI, and the effective projection contrast ratio EPC. mode ; Step 5: Set the weather transition threshold set and assign dynamic mode weights W. mode The system compares the target location with the thresholds in the weather conversion threshold set to determine the environmental state of the target location and selects the corresponding projection mode based on the environmental state. Step Six: Define the global geographic coordinate system and model vehicle parameters; Step 7: Construct a dynamic allocation model for vehicle projection viewpoints; Step 8: Achieve high-precision correction through terrain data preprocessing, ray tracing modeling, and perspective transformation calculation; Step 9: Achieve natural stitching of images from adjacent projection devices through overlapping region detection, feature matching optimization, and weighted fusion calculation.

2. The method for safe radiant projection at mobile weather modification sites according to claim 1, characterized in that, Environmental baseline attenuation data include atmospheric transmittance τ and aerosol concentration C. a and background illuminance L b ; The Environmental Transmission Attenuation Index (ETI) is calculated using environmental baseline attenuation data, based on the following formula: Where e is the base of the natural logarithm; k1 represents the aerosol attenuation coefficient; and L0 is the reference illuminance value.

3. The method for safe radiant projection at mobile weather modification sites according to claim 2, characterized in that, Medium scattering interference data includes scattering coefficient σ s Cloud optical thickness δ c and visibility change rate δ v ; The formula used to calculate the Medium Scattering Interference Index (MSI) from medium scattering interference data is as follows: Where v0 is the visibility attenuation threshold and ρ is the surface reflectance.

4. A method for safe radiant projection at mobile weather modification sites according to claim 3, characterized in that, Effective projection data includes the intensity of the projection light source I. P and background brightness I b The effective projection contrast ratio (EPC) is calculated through comprehensive analysis, and the calculation formula is as follows: Where k2 is the scattering correction factor.

5. A method for projecting a safe radiant field for mobile weather modification sites according to claim 4, characterized in that, Effective projection data includes cloud movement vector V 云 and ground wind speed vector V 地面 Specifically: By continuously monitoring cloud movement using weather radar, the cloud movement vector V is obtained in real time. 云 The surface wind speed vector V is obtained by measuring and recording wind speeds using the wind measuring equipment at the meteorological station. 地面 .

6. A method for safe radiant projection at mobile weather modification sites according to claim 1, characterized in that, Calculate the dynamic mode weights W mode The formula used is as follows: Where α is an empirical parameter.

7. A method for projecting a safe radiant field for mobile weather modification sites according to claim 1, characterized in that, The method for selecting the appropriate projection mode based on environmental conditions is as follows: The weather transition threshold set includes cloudy transition thresholds and rain / fog transition thresholds; The dynamic mode weight W mode The dynamic mode weight W is compared with the cloudy transition threshold and the rain / fog transition threshold, respectively. mode > When the cloudy transition threshold is reached, select the sunny projection mode; when the rain / fog transition threshold is less than or equal to the dynamic mode weight W. mode When the cloud cover projection mode is ≤, select the cloud cover projection mode; when the dynamic mode weight W mode When the rain / fog transition threshold is reached, select the rain / fog projection mode.

8. A method for projecting a safe radiant field for mobile weather modification sites according to claim 1, characterized in that, Image cropping strategies based on vehicle structure include those based on the vehicle's aspect ratio. The location of the launching device is determined using a non-uniform viewing angle: the front area covers a wide angle, while the single device viewing angle is [not specified]. The rear area of ​​the vehicle needs to be covered as the launching device is located there; single device viewpoint. Single device perspective θ in the middle of the vehicle body side =60°-θ head -θ tail Convert the vehicle coordinate system view to the geographic coordinate system, where the clipping formula is: I i =I(θ geo )∈[θ i-start ,i i-end ], 9. A method for projecting a safe radiant field for mobile weather modification sites according to claim 1, characterized in that, The terrain data extraction uses the rocket launch device's center coordinates (x0, y0, z0) as the origin, obtains a digital elevation model (DEM) from the GIS system, and extracts a local area with a radius of R (e.g., R = 50m). THEY sub NClip(DEM,[x0-R,y0-R,x0+R,y0+R]) Simultaneously, the DEM data is converted into a 3D point cloud format. Where N is the number of point clouds; Terrain area priority is determined based on the Euclidean distance from the terrain point to the launching device. The region is divided into three levels: Near-field (d≤10m): Sub-pixel level light field sampling is used (sampling interval Δθ≤0.05°). Central area (10m < d ≤ 30m): Conventional sampling (Δθ = 0.1°, ) Far-field (d≥30m): Low-precision sampling (Δθ=0.2°, ) Sampling density formula:

10. A method for safe radiant projection at mobile weather modification sites according to claim 1, characterized in that, The stitching and blending enhancement is based on the viewing angle range θ of each projection device. i-start and θ i-end Calculate the overlap angle interval Δθ between adjacent devices i and i+1. i,i+1 : Wherein, ∈ is the preset overlap width (usually 5°-10°), used to ensure that adjacent images have sufficient overlapping area; The pyramid multi-scale SIFT algorithm is used to correct the image I' i and I' i+1 Generate n layers of Gaussian pyramids and extract SIFT feature points from each pyramid image; Solve the problem from image I' using the RANSAC algorithm. i To I' i+1 The homography matrix H i,i+1 ; Bicubic interpolation and affine fine-tuning are used to improve matching accuracy; For pixels (θ, Φ) within the overlapping region, according to the dynamic weight ω i,i+1 (θ,d) Calculate the merged pixel value I fused (θ,Φ): I fused (θ,Φ)=ω i,i+1 (θ,d)·I′ i (θ,Φ)+(1-ω i,i+1 (θ,d))I″ i+1 (θ,Φ) To avoid color inconsistencies, brightness equalization can be further introduced: Mean matching: Calculate the average brightness μ of the overlapping region. i and μ i+1 , to I" i+1 Adjust the brightness: Final fusion: using the adjusted I”' i+1 Perform pixel blending.

Images