Satellite communication attenuation prediction method and device for remote region electric power communication, electronic equipment and non-transient computer readable storage medium

Abstract

The invention provides a satellite communication attenuation prediction method and device for electric power communication in a remote area, electronic equipment and a non-transient computer readable storage medium, and the method comprises the steps: calculating a prediction attenuation value under the single influence of snowy weather, and obtaining a first prediction value; calculating a prediction attenuation value under the single influence of cloudy and foggy weather to obtain a second prediction value; based on the communication channel frequency of satellite communication, the snowing intensity of the current weather, the cloud liquid water content in the cloud and mist and the weather temperature, a prediction attenuation value additionally increased due to electromagnetic interaction between the snow crystal and the cloud droplet is determined, and a third prediction value is obtained; and obtaining a total attenuation prediction value of satellite communication based on the first prediction value, the second prediction value and the third prediction value. According to the satellite communication attenuation prediction method and device for remote region power communication, the electronic equipment and the non-transient computer readable storage medium provided by the invention, the signal attenuation condition of a satellite-ground link in satellite communication in a complex meteorological environment can be accurately predicted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite communication, and in particular to a satellite communication attenuation prediction method and device for power communication in remote areas, an electronic device, and a non-transitory computer-readable storage medium. BACKGROUND

[0002] Due to the diffusion attenuation characteristics of electromagnetic waves, atmospheric layer influence, weather changes, and other factors, there is a certain communication attenuation in satellite communication. Although the existing signal attenuation prediction method can consider changes in different weather, it still has the problem of inaccurate attenuation prediction in complex weather environments containing multiple weather, which affects the stability of satellite communication. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a satellite communication attenuation prediction method and device for power communication in remote areas, an electronic device, and a non-transitory computer-readable storage medium to solve the above technical problems.

[0004] To achieve the above purpose, the present application provides a satellite communication attenuation prediction method for power communication in remote areas to predict satellite communication attenuation when snow and cloud coexist, which comprises the following steps:

[0005] calculating the predicted attenuation value under the influence of snow weather alone to obtain a first predicted value;

[0006] calculating the predicted attenuation value under the influence of cloud weather alone to obtain a second predicted value;

[0007] determining the predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency of satellite communication, the snow intensity of the current weather, the cloud liquid water content in the cloud, and the weather temperature to obtain a third predicted value;

[0008] obtaining the total attenuation prediction value of satellite communication based on the first predicted value, the second predicted value, and the third predicted value.

[0009] Optionally, the step of determining the predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency of satellite communication, the snow intensity of the current weather, the cloud liquid water content in the cloud, and the weather temperature to obtain a third predicted value comprises:

[0010] determining the influence coefficient of electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency, the snow intensity, the cloud liquid water content, and the weather temperature to obtain an electromagnetic coupling coefficient;

[0011] multiplying the electromagnetic coupling coefficient by the equivalent path length of communication attenuation to obtain the third predicted value.

[0012] Optionally, the determining the influence coefficient of electromagnetic interaction between snow crystal and cloud drop based on the communication channel frequency, the snowfall intensity, the cloud liquid water content and the weather temperature comprises:

[0013] determining an electromagnetic interaction intensity coefficient between the snow crystal and the cloud drop based on the communication channel frequency;

[0014] determining a snow crystal number density based on the snowfall intensity;

[0015] determining a cloud drop number density based on the cloud liquid water content;

[0016] determining a first temperature correction coefficient based on the weather temperature;

[0017] determining an electromagnetic coupling coefficient based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud drop number density and the first temperature correction coefficient.

[0018] Optionally, the determining the snow crystal number density based on the snowfall intensity comprises:

[0019] the snow crystal number density is determined by the following formula:

[0020]

[0021] wherein, n s is the snow crystal number density, κ s is a first temperature influence coefficient, S is the snowfall intensity, and α s is a snow characteristic index.

[0022] Optionally, the determining the cloud drop number density based on the cloud liquid water content comprises:

[0023] the cloud drop number density is determined by the following formula:

[0024]

[0025] wherein, n c is the cloud drop number density, κ c is a second temperature influence coefficient, M is the cloud liquid water content, and α c is a cloud characteristic index.

[0026] Optionally, the determining the first temperature correction coefficient based on the weather temperature comprises:

[0027] the first temperature correction coefficient is determined by the following formula:

[0028]

[0029] wherein, η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitive coefficient, T ref is a reference temperature.

[0030] Optionally, the determining the influence coefficient of electromagnetic interaction between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density and the first temperature correction coefficient to obtain an electromagnetic coupling coefficient comprises:

[0031] The electromagnetic coupling coefficient γ sc is determined by the following formula:

[0032] γ sc = ξ · n s · n c · σ ref · η(T)

[0033] wherein, ξ is the electromagnetic interaction intensity coefficient; n s is the snow crystal number density, n c is the cloud droplet number density, η(T) is the first temperature correction coefficient, σ ref is a reference extinction cross section.

[0034] Optionally, the calculating the predicted attenuation value under the single influence of snow weather to obtain a first predicted value comprises:

[0035] determining an attenuation influence coefficient under the single influence of snow weather based on the weather temperature, the communication channel frequency of satellite communication and the snow intensity to obtain a snow attenuation coefficient;

[0036] multiplying the snow attenuation coefficient and the equivalent path length of communication attenuation to obtain the first predicted value.

[0037] Optionally, the determining the attenuation influence coefficient under the single influence of snow weather based on the weather temperature, the communication channel frequency of satellite communication and the snow intensity to obtain a snow attenuation coefficient comprises:

[0038] determining a second temperature correction coefficient based on the weather temperature;

[0039] determining a communication frequency coefficient based on the communication channel frequency;

[0040] multiplying the second temperature correction coefficient, the communication frequency coefficient and the snow intensity corrected by a frequency correlation coefficient to obtain the snow attenuation coefficient;

[0041] wherein, the snow intensity corrected by the frequency correlation coefficient is determined by the following method:

[0042] determine a frequency correlation coefficient based on the communication channel frequency;

[0043] multiply the frequency correlation coefficient by the snowfall intensity to obtain the frequency correlation coefficient corrected snowfall intensity.

[0044] Optionally, the calculation of the predicted attenuation value under the single influence of the cloud and fog weather to obtain the second predicted value comprises:

[0045] determine a cloud and fog attenuation coefficient under the single influence of the cloud and fog weather based on the communication channel frequency of the satellite communication, the cloud liquid water content and the liquid water temperature of the cloud and fog weather to obtain the cloud and fog attenuation coefficient;

[0046] multiply the cloud and fog attenuation coefficient by the equivalent path length of the communication attenuation to obtain the second predicted value.

[0047] Optionally, the determination of the cloud and fog attenuation coefficient under the single influence of the cloud and fog weather based on the communication channel frequency of the satellite communication, the cloud liquid water content and the liquid water temperature of the cloud and fog weather comprises:

[0048] determine a cloud droplet dielectric property parameter based on the liquid water temperature and the communication channel frequency;

[0049] multiply the cloud droplet dielectric property parameter by the cloud liquid water content to obtain the cloud and fog attenuation coefficient.

[0050] Optionally, the equivalent path length is determined according to the following method:

[0051] obtain a satellite elevation angle, and determine the equivalent path length based on the satellite elevation angle.

[0052] Optionally, the determination of the equivalent path length based on the satellite elevation angle comprises:

[0053] determine the equivalent path length by the following formula:

[0054]

[0055] wherein, L eff (θ) is the equivalent path length, θ is the satellite elevation angle, H atm is the effective height of the atmosphere.

[0056] Based on the same inventive concept, the application further provides a satellite communication attenuation prediction device for remote area power communication, which is used to predict the satellite communication attenuation when snow and cloud and fog coexist, comprising:

[0057] a snow attenuation prediction module, which is used to calculate a predicted attenuation value under the single influence of the snow weather to obtain a first predicted value;

[0058] A cloud and fog attenuation prediction module is used to calculate the predicted attenuation value under the influence of cloud and fog weather alone to obtain a second predicted value;

[0059] A coupled attenuation prediction module is used to determine an additional predicted attenuation value due to electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency of satellite communication, the current snow intensity, the cloud liquid water content in the cloud fog, and the weather temperature, thereby obtaining a third predicted value;

[0060] The total attenuation prediction module is configured to obtain a total attenuation prediction value of satellite communication based on the first prediction value, the second prediction value, and the third prediction value.

[0061] Optionally, the coupling attenuation prediction module includes:

[0062] a coupling coefficient calculation unit, configured to determine an influence coefficient of electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency, the snow intensity, the cloud liquid water content, and the weather temperature, to obtain an electromagnetic coupling coefficient;

[0063] The coupling attenuation calculation unit is used to multiply the electromagnetic coupling coefficient by the equivalent path length of the communication attenuation to obtain the third predicted value.

[0064] Optionally, the coupling coefficient calculation unit is further configured to:

[0065] determining an electromagnetic interaction strength coefficient between snow crystals and cloud droplets based on the communication channel frequency;

[0066] determining a snow crystal number density based on the snowing intensity;

[0067] determining a cloud droplet number density based on the cloud liquid water content;

[0068] determining a first temperature correction coefficient based on the weather temperature;

[0069] An influence coefficient of electromagnetic interaction between snow crystals and cloud droplets is determined based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud drop number density, and the first temperature correction coefficient to obtain an electromagnetic coupling coefficient.

[0070] Optionally, determining the snow crystal number density based on the snowing intensity includes:

[0071] The snow crystal number density is determined by the following formula:

[0072]

[0073] Among them, n s is the snow crystal number density, κ s is the first temperature influence coefficient, S is the snow intensity, αs is a snowfall characteristic index.

[0074] Optionally, the determining the cloud droplet number density based on the cloud liquid water content comprises:

[0075] The cloud droplet number density is determined by the following formula:

[0076]

[0077] wherein n c is a cloud droplet number density, κ c is a second temperature influence coefficient, M is a cloud liquid water content, α c is a cloud fog characteristic index.

[0078] Optionally, the determining the first temperature correction coefficient based on the weather temperature comprises:

[0079] The first temperature correction coefficient is determined by the following formula:

[0080]

[0081] wherein η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitivity coefficient, T ref is a reference temperature.

[0082] Optionally, the determining the electromagnetic interaction influence coefficient between the snow crystal and the cloud droplet based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density and the first temperature correction coefficient to obtain an electromagnetic coupling coefficient comprises:

[0083] The electromagnetic coupling coefficient γ sc is determined by the following formula:

[0084] γ sc = ξ · n s · n c · σ ref · η(T)

[0085] wherein ξ is an electromagnetic interaction intensity coefficient; n s is the snow crystal number density, n c is the cloud droplet number density, η(T) is the first temperature correction coefficient, σ ref is a reference extinction cross section.

[0086] Optionally, the snowfall attenuation prediction module comprises:

[0087] a snowfall attenuation coefficient calculation unit, configured to determine an attenuation influence coefficient under a single influence of snowfall weather based on a weather temperature, a communication channel frequency of satellite communication and a snowfall intensity to obtain a snowfall attenuation coefficient.

[0088] The snow attenuation calculation unit is configured to multiply the snow attenuation coefficient and an equivalent path length of communication attenuation to obtain a first prediction value.

[0089] Optionally, the snow attenuation coefficient calculation unit is further configured to:

[0090] determine a second temperature correction coefficient based on the weather temperature;

[0091] determine a communication frequency coefficient based on the communication channel frequency;

[0092] multiply the second temperature correction coefficient, the communication frequency coefficient, and a frequency-related coefficient corrected snow intensity to obtain the snow attenuation coefficient;

[0093] wherein the frequency-related coefficient corrected snow intensity is determined by the following method:

[0094] determine a frequency-related coefficient based on the communication channel frequency;

[0095] multiply the frequency-related coefficient and the snow intensity to obtain the frequency-related coefficient corrected snow intensity.

[0096] Optionally, the cloud and fog attenuation prediction module comprises:

[0097] A cloud and fog attenuation coefficient calculation unit is configured to determine an attenuation influence coefficient under the influence of a single cloud and fog weather based on a communication channel frequency of satellite communication, a cloud liquid water content of the cloud and fog weather, and a liquid water temperature, to obtain a cloud and fog attenuation coefficient;

[0098] A cloud and fog attenuation calculation unit is configured to multiply the cloud and fog attenuation coefficient and an equivalent path length of communication attenuation to obtain a second prediction value.

[0099] Optionally, the cloud and fog attenuation coefficient calculation unit is further configured to:

[0100] determine a cloud droplet dielectric property parameter based on the liquid water temperature and the communication channel frequency;

[0101] multiply the cloud droplet dielectric property parameter and the cloud liquid water content to obtain the cloud and fog attenuation coefficient.

[0102] Optionally, the equivalent path length is determined according to the following method:

[0103] obtain a satellite elevation angle, and determine the equivalent path length based on the satellite elevation angle.

[0104] Optionally, the determination of the equivalent path length based on the satellite elevation angle comprises:

[0105] The equivalent path length is determined by the following formula:

[0106]

[0107] wherein L eff is the equivalent path length, theta is the satellite elevation angle, H atm is the effective height of atmosphere.

[0108] Based on the same inventive concept, the application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that the processor implements the satellite communication attenuation prediction method for remote area power communication as described above when executing the program.

[0109] Based on the same inventive concept, the application further provides a non-transitory computer readable storage medium, which stores computer instructions, characterized in that the computer instructions are used to make a computer execute the satellite communication attenuation prediction method for remote area power communication as described above.

[0110] As can be seen from the above, the satellite communication attenuation prediction method, device, electronic device and non-transitory computer readable storage medium for remote area power communication provided by the application fully consider various factors affecting the electromagnetic interaction between snow crystals and cloud droplets, determine the prediction attenuation value, i.e. the third prediction value, caused by the electromagnetic interaction between snow crystals and cloud droplets by the communication channel frequency of satellite communication, the snowfall intensity of the current weather, the cloud liquid water content in the cloud and fog and the weather temperature, and then add the prediction attenuation value under the single influence of snowfall weather and the prediction attenuation value under the single influence of cloud and fog weather, i.e. the total attenuation prediction value under the complex meteorological environment when snowfall and cloud and fog coexist. The attenuation prediction method of the application fully considers the situation that the attenuation is aggravated due to the complex electromagnetic interaction between snow crystals and cloud droplets when cloud and fog and snowfall weather coexist, can accurately predict the signal attenuation of the satellite communication in the star-ground link under the complex meteorological environment, effectively improves the signal attenuation prediction accuracy, ensures the effective operation of the satellite communication, and thus ensures the normal communication and operation of the power system under the complex meteorological environment such as high altitude. BRIEF DESCRIPTION OF DRAWINGS

[0111] In order to more clearly illustrate the technical solutions in the application or related art, the following will briefly introduce the drawings needed to be used in the embodiments or related art description. Obviously, the drawings in the following description are only embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0112] Figure 1A satellite communication attenuation prediction method for remote area power communication according to an embodiment of the present application;

[0113] Figure 2 A curve showing changes over time of signal attenuation predicted according to a conventional linear superposition method and actual attenuation according to the present application;

[0114] Figure 3 A satellite communication attenuation prediction device for remote area power communication according to an embodiment of the present application;

[0115] Figure 4 An electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0116] To make the objectives, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to specific embodiments and accompanying drawings.

[0117] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the embodiments of the present application should be understood as their common meanings to those skilled in the art to which the present application belongs. The terms "first", "second", and similar terms used in the embodiments of the present application do not represent any order, number, or importance, but are only used to distinguish different components. The terms "include", "contain", and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, without excluding other elements or objects. The terms "connect" or "connected" and similar terms do not mean only physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right", and the like only represent relative positional relationships, which can change when the absolute positions of the described objects change.

[0118] With the continuous advancement of modernization of the power system, the power transmission line network in the western plateau region is expanding, covering a large number of remote areas with complex geographical environments such as high mountains, gorges, and Gobi deserts. The construction of power communication networks in these areas faces the severe challenge of insufficient coverage of traditional ground communication infrastructure. In this context, the satellite-ground communication system can realize information transmission between the ground and the low-orbit satellite, and has been widely used in remote area power communication due to its wide coverage and no geographical limitations. In particular, in the scenarios of power transmission line monitoring, power distribution automation, and power dispatching, satellite-ground communication has become a key technical means to solve the lack of ground communication capabilities, effectively building a power communication network covering remote areas, and providing a reliable data transmission channel and communication guarantee for the safe and stable operation of the power grid.

[0119] In a satellite communication system, especially in a satellite-to-ground communication link, there is a certain communication attenuation due to the diffused attenuation characteristics of electromagnetic waves, atmospheric influence, weather changes, etc. For example, when the signal passes through the atmosphere, especially the troposphere, it will interact with gas molecules, water vapor, clouds, etc., thereby causing signal attenuation; raindrops can scatter and absorb electromagnetic waves, so it will exacerbate the attenuation on rainy days. When the weather changes, the specific situation of the attenuation will also change, for example, the attenuation caused by sandstorms is generally weaker than that caused by rain, etc. Accurate prediction of signal attenuation under different weather conditions plays an important role in the normal operation of the satellite communication system and the efficient transmission of information.

[0120] Currently, many calculation and prediction techniques have emerged in the field of atmospheric propagation attenuation modeling, such as ITU-R model, statistical correction method, microphysical process modeling, etc. These techniques have achieved certain results in the field of single meteorological factor attenuation prediction, but there are still some challenges in the prediction of multi-factor coupled attenuation under complex weather conditions. Although the existing signal attenuation prediction methods can consider the changes of different weather, in the complex meteorological environment containing multiple weather, they generally only simply superimpose the predicted attenuation values under multiple weather conditions without considering the possible exacerbation of attenuation under the superposition of multiple weather, which leads to inaccurate attenuation prediction and affects the stability of satellite communication.

[0121] The electromagnetic interaction between snow crystal and cloud droplet refers to the complex synergistic effect of electromagnetic waves penetrating through the mixed-phase cloud layer in snowstorm weather when large snow crystals and supercooled cloud droplets coexist. This interaction not only significantly enhances signal attenuation, but also changes the polarization and scattering characteristics of electromagnetic waves, which is a major challenge for high-frequency satellite communication.

[0122] Under the condition of snowfall and cloud coexistence, especially in the low-temperature environment of snowstorm and cloud coexistence, the electromagnetic interaction between snow crystal and cloud droplet will further exacerbate signal attenuation. The traditional linear superposition method of simply superimposing the attenuation of snowstorm weather and the attenuation of cloud weather cannot effectively capture the situation of signal attenuation exacerbated by the electromagnetic interaction between snow crystal and cloud droplet, resulting in low communication attenuation prediction accuracy, thereby affecting the efficiency and stability of satellite-to-ground communication. The satellite-to-ground communication system of the power system is mainly deployed in remote high-altitude areas where the climate is changeable and complex weather occurs frequently, especially in winter when it often encounters complex weather conditions such as snowstorm, low temperature and cloud, etc. The existing prediction method cannot accurately predict the signal attenuation under such complex weather conditions, which poses a serious challenge to the stability of the satellite-to-ground communication link.

[0123] Therefore, the present application provides a satellite communication attenuation prediction method for remote area power communication, which comprises the following steps: Figure 1The method for predicting satellite communication attenuation when snow and cloud and fog coexist can effectively capture the intensification of signal attenuation when snow and cloud and fog coexist, effectively improve the signal attenuation prediction accuracy in the composite weather environment, and the method comprises the following steps:

[0124] S101, calculating the predicted attenuation value under the influence of snow weather alone to obtain a first prediction value;

[0125] S102, calculating the predicted attenuation value under the influence of cloud and fog weather alone to obtain a second prediction value;

[0126] S103, determining the predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency of satellite communication, the snow intensity of the current weather, the cloud liquid water content in the cloud and fog, and the weather temperature, to obtain a third prediction value;

[0127] S104, obtaining the total attenuation prediction value of satellite communication based on the first prediction value, the second prediction value and the third prediction value.

[0128] When the communication channel frequency of satellite communication, the snow intensity of the current weather, the cloud liquid water content in the cloud and fog, and the weather temperature are different, the predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets is also different. Under the high-frequency communication channel, snow crystal scattering reaches the peak, cloud droplet absorption loss increases dramatically, snow crystals and cloud droplets form ice-water mixed particles through electric field coupling, in the ice-water mixed particles, ice crystal skeleton as a carrier maintains millimeter size, which can efficiently capture electromagnetic waves, thereby intensifying signal attenuation. When the snow intensity increases, especially in heavy snow weather, the concentration of snow crystals increases significantly, large particles are formed by collision and adhesion between snow crystals, the collision probability of snow crystal group and cloud droplets increases, and mixed phase particles are formed by cloud droplets wrapped around the surface of snow crystals, the dielectric loss is doubled, and the signal attenuation intensity will also increase exponentially. When the cloud liquid water content is low, the number of cloud droplets is small, the snow crystals can maintain dry ice crystal state, the dielectric loss is low, and the additional attenuation caused is also low; when the cloud liquid water content increases, cloud droplets are densely attached to the surface of snow crystals to form liquid water film wrapped wet snow nuclei, snow crystals and cloud droplets produce electromagnetic field coupling resonance through sharing water film, and the absorption loss will increase dramatically. Under different weather temperatures, the ice-water phase ratio and the particle microstructure are different, thereby causing different intensification of signal attenuation.

[0129] In the present application, various factors affecting the electromagnetic interaction between snow crystals and cloud droplets are fully considered, and the prediction attenuation value additionally increased due to the electromagnetic interaction between snow crystals and cloud droplets is determined based on the communication channel frequency of satellite communication, the snowfall intensity of current weather, the cloud liquid water content in cloud and fog, and the weather temperature, that is, the third prediction value. Then, the prediction attenuation value under the single influence of snowfall weather and the prediction attenuation value under the single influence of cloud and fog weather are added, and the total attenuation prediction value under the complex meteorological environment of coexistence of snowfall and cloud and fog is obtained. The attenuation prediction method of the present application fully considers the case that the attenuation is aggravated due to the complex electromagnetic interaction between snow crystals and cloud droplets under the coexistence of cloud and fog and snowfall weather, can accurately predict the signal attenuation of the satellite communication star-ground link under the complex meteorological environment, effectively improves the signal attenuation prediction precision, ensures the effective operation of satellite communication, and thus ensures the normal communication and operation of the power system under the complex meteorological environment such as high altitude.

[0130] In some embodiments, the third prediction value is determined based on the communication channel frequency of satellite communication, the snowfall intensity of current weather, the cloud liquid water content in cloud and fog, and the weather temperature, and includes:

[0131] An influence coefficient of electromagnetic interaction between snow crystals and cloud droplets is determined based on the communication channel frequency, the snowfall intensity, the cloud liquid water content, and the weather temperature, and an electromagnetic coupling coefficient is obtained.

[0132] The electromagnetic coupling coefficient is multiplied by the equivalent path length of communication attenuation to obtain the third prediction value.

[0133] The equivalent path length is an equivalent distance value containing the path bending and propagation delay effects caused by atmospheric refraction. In communication attenuation prediction, the equivalent path length can be used to more accurately calculate the free space path loss, so as to more truly reflect the attenuation suffered by the signal due to the propagation distance and atmospheric refraction effect.

[0134] In the present application, firstly, the factors causing communication attenuation, such as the communication channel frequency, snowfall intensity, cloud liquid water content and weather temperature, are used to determine the signal attenuation caused by the electromagnetic interaction between snow crystal cloud droplets per unit distance, i.e. the electromagnetic coupling coefficient; and then the electromagnetic coupling coefficient is multiplied by the equivalent path length of communication attenuation to obtain the attenuation value caused by the electromagnetic interaction between snow crystal and cloud droplets in the communication process, i.e. the third prediction value. In the calculation process of the electromagnetic coupling coefficient, all factors affecting the electromagnetic interaction between cloud droplets and snow crystals, i.e. the communication channel frequency, snowfall intensity, cloud liquid water content and weather temperature, are fully considered, thereby effectively improving the prediction accuracy, and the equivalent path length is used to determine the attenuation path, which can more truly reflect the attenuation of the signal due to the propagation distance and atmospheric refraction effect, further improving the prediction accuracy of the attenuation value.

[0135] In some embodiments, the determination of the influence coefficient of the electromagnetic interaction between snow crystals and cloud droplets based on the communication channel frequency, the snowfall intensity, the cloud liquid water content and the weather temperature to obtain the electromagnetic coupling coefficient comprises:

[0136] determining the electromagnetic interaction intensity coefficient between snow crystals and cloud droplets based on the communication channel frequency;

[0137] determining the snow crystal number density based on the snowfall intensity;

[0138] determining the cloud droplet number density based on the cloud liquid water content;

[0139] determining the first temperature correction coefficient based on the weather temperature;

[0140] determining the influence coefficient of the electromagnetic interaction between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density and the first temperature correction coefficient to obtain the electromagnetic coupling coefficient.

[0141] The efficiency and intensity of the interaction between electromagnetic waves of different frequencies and snow crystals and cloud droplets are significantly different, so the electromagnetic interaction intensity between snow crystals and cloud droplets is obviously different at different communication channel frequencies, resulting in the change of the degree of signal attenuation with frequency. The intensity of the interaction between electromagnetic waves and particles mainly depends on the relative relationship between the wavelength and the particle size. The diameter of cloud droplets is generally about 10 μm, and the diameter of snow crystals is about 0.1-2 mm. In the low frequency band, the size of cloud droplets and snow crystals is much smaller than the wavelength, so the attenuation intensity is generally weak. In the medium frequency band, the diameter of snowflakes is close to the wavelength, especially in heavy snow, the size of snow crystals is large and close to the wavelength, which brings Mie scattering, and the scattering intensity increases significantly, thereby intensifying the signal attenuation. In the high frequency band, the size of cloud droplets and snow crystals is closer to the wavelength, and the signal attenuation is further intensified.

[0142] The snow crystal number density is directly affected by the snowfall intensity, and the cloud droplet number density is directly affected by the cloud liquid water content. The signal attenuation intensified when the snow weather and the cloud weather coexist is mainly caused by the electromagnetic interaction between the snow crystal and the cloud droplet. Therefore, when the snow crystal number density and the cloud droplet number density are different, the additional attenuation caused thereby is also different. In addition to the snowfall intensity and the cloud liquid water content, considering the significant influence of the low-temperature environment on the microphysical process, a first temperature correction coefficient is designed to further correct, so as to improve the prediction accuracy.

[0143] In the present application, the snow crystal number density is determined by collecting the snowfall intensity in the current weather, the cloud droplet number density is determined by collecting the cloud liquid water content in the current weather, and the influence of different weather temperatures and communication channel frequencies on electromagnetic interaction is considered. Finally, the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density and the first temperature correction coefficient are used to determine the final electromagnetic coupling coefficient. In the electromagnetic coupling coefficient, the influence of various environmental factors on the electromagnetic interaction between the snow crystal and the cloud droplet is considered. The final attenuation value obtained by calculation is closer to the actual attenuation value, and the communication attenuation prediction accuracy is higher.

[0144] In some embodiments, the snow crystal number density is determined based on the snowfall intensity, comprising:

[0145] The snow crystal number density is determined by the following formula:

[0146]

[0147] Wherein, n s is the snow crystal number density, κ s is the first temperature influence coefficient, S is the snowfall intensity, and a s is the snow characteristic index.

[0148] In some embodiments, the cloud droplet number density is determined based on the cloud liquid water content, comprising:

[0149] The cloud droplet number density is determined by the following formula:

[0150]

[0151] Wherein, n c is the cloud droplet number density, κ c is the second temperature influence coefficient, M is the cloud liquid water content, and a c is the cloud characteristic index.

[0152] In some embodiments, the first temperature correction coefficient is determined based on the weather temperature, comprising:

[0153] The first temperature correction coefficient is determined by the following formula:

[0154]

[0155] wherein η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitivity coefficient, T ref is a reference temperature.

[0156] The weather temperature has a significant influence on the growth and falling of snow crystals, and different temperature conditions will form snow crystals of different shapes and sizes, thereby affecting the snow crystal number density. At about -15℃, it is conducive to the formation of large-particle-size and low-density dendritic snow crystals, and at this time, if the snowfall intensity is large, these larger dendritic snow crystals will occupy a certain space, which may make the snow crystal number density relatively small. At a lower temperature, such as below -22℃, mainly columnar snow crystals are generated, and the density is relatively large, and if the snowfall intensity is the same, the snow crystal number density may be relatively high. Under the conditions of higher temperature and humidity, water vapor is more likely to condense into cloud droplets, thereby increasing the cloud droplet number density. Therefore, in the process of determining the cloud droplet number density by using the snow crystal number density and the cloud liquid water content, the influence of the weather temperature is also fully considered, so that the calculation of the snow crystal number density and the cloud droplet number density is more accurate.

[0157] Specifically, the first temperature influence coefficient k s has a value range of 10 3 ~ 10 5 , and specifically can be 10 3 , 2X10 3 , 5X10 3 , 8X10 3 , 9X10 3 , 10 4 , 2X10 4 , 5X10 4 , 6X10 4 , 8X10 4 , 10 5 , etc., and can also be other values in the range, and the specific limitation is not made. The snow characteristic index a s represents the nonlinear influence of the snowfall intensity on the coupling effect, and has a value range of 0.7~0.95, and specifically can be 0.7, 0.75, 0.8, 0.85, 0.9, 0.95, etc., and can also be other values in the range, and the specific limitation is not made. The second temperature influence coefficient κ c has a value range of 10 8 ~ 10 10 , and specifically can be 10 8 , 2X10 8 , 5X10 8 , 8X10 8 , 9X10 8 , 10 9, 2X10 9 , 5X10 9 , 6X10 9 , 8X10 9 , 10 10 , etc., or other values within the range, which are not limited specifically c . The cloud and fog characteristic index a ref is used to represent the nonlinear influence of cloud liquid water content on coupling effect, and the value range is 1.05-1.25, specifically, it can be 1.05, 1.08, 1.1, 1.12, 1.14, 1.15, 1.16, 1.18, 1.2, 1.22, 1.24, 1.25, etc., or other values within the range, which are not limited specifically

[0158] Since electromagnetic wave propagation analysis requires micro-physical parameters, and actual observation usually obtains macro-weather parameters, the present application establishes the parameter conversion relationship from macro to micro, that is, the relationship between snow intensity and snow crystal number density is established (i.e. ) by using the first temperature influence coefficient and the snow characteristic index, thereby effectively realizing the process of determining the snow crystal number density according to the snow intensity; the relationship between cloud liquid water content and cloud droplet number density is established (i.e. ) by using the second temperature influence coefficient and the cloud and fog characteristic index, thereby effectively realizing the process of determining the cloud droplet number density according to the cloud liquid water content, providing the implementation basis and prerequisite conditions for the calculation of the third prediction value.

[0159] Considering the significant influence of low-temperature environment on micro-physical process, the first temperature correction coefficient is constructed to correct the influence relationship, effectively capturing the influence of temperature change on scattering characteristics, to obtain more accurate electromagnetic coupling coefficient. The reference temperature T ref is used to standardize the temperature influence, and the value is 273K (i.e. 0℃, freezing point temperature). The value range of the first temperature sensitive coefficient γ is 0.01-0.02, specifically, it can be 0.01, 0.012, 0.014, 0.015, 0.016, 0.018, 0.02, etc., or other values within the range, which are not limited specifically.

[0160] In some embodiments, the influence coefficient of electromagnetic interaction between snow crystals and cloud droplets is determined based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, to obtain the electromagnetic coupling coefficient, including:

[0161] The electromagnetic coupling coefficient γ sc is determined by the following formula:

[0162] γ sc = ξ·n s ·n c ·σref • η(T)

[0163] wherein ξ is the electromagnetic interaction strength coefficient; n s is the number density of the snow crystals, n c is the number density of the cloud droplets, η(T) is the first temperature correction coefficient, σ ref is the reference extinction cross section.

[0164] The electromagnetic interaction strength coefficient ξ at different communication channel frequencies is shown in the following table:

[0165] Table 1 electromagnetic interaction strength coefficient value range table at different communication channel frequencies

[0166] Communication channel frequency Electromagnetic interaction strength coefficient ξ value range Ka band (26-40 GHz) 0.02～0.08 Ku band (12-18 GHz) 0.01～0.03 X band (8-12 GHz) 0.005～0.015

[0167] Specifically, at Ka band (26-40 GHz), the electromagnetic interaction strength coefficient ξ can be 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, and can also be other values within the range shown in Table 1, without limitation. At Ku band (12-18 GHz), the electromagnetic interaction strength coefficient ξ can be 0.01, 0.012, 0.015, 0.016, 0.018, 0.02, 0.024, 0.025, 0.026, 0.028, 0.03, and can also be other values within the range shown in Table 1, without limitation. At X band (8-12 GHz), the electromagnetic interaction strength coefficient ξ can be 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015, and can also be other values within the range shown in Table 1, without limitation.

[0168] The reference extinction cross section is determined based on Mie scattering (Mie scattering) theory, representing the average extinction cross section under a standard particle size distribution, and the value range is 10 -12 ~ 10 -10 , and can be 10 -12 , 2X10 -12 , 4X10 -12 , 5X10 -12 , 6X10 -12 , 8X10 -12 , 10 -11 , 2X10 -11 , 4X10 -11 , 6X10 -11 , 8X10 -11 , 10 -10 , and can also be other values within the range, without limitation.

[0169] By multiplying the electromagnetic interaction intensity coefficient, snow crystal number density, cloud droplet number density, and the first temperature correction coefficient with the reference extinction cross section, not only the influence of the current environmental information (snow crystal number density, cloud droplet number density, and the first temperature correction coefficient) is taken into account, but also the interaction mechanism of microscopic particles (electromagnetic interaction intensity coefficient and reference extinction cross section) is fully considered. The electromagnetic coupling coefficient calculation formula constructed in this way can accurately describe the electromagnetic interaction between snow crystals and cloud droplets, thereby achieving accurate prediction of signal attenuation.

[0170] In some embodiments, calculating the predicted attenuation value under the single influence of snowy weather to obtain the first predicted value includes:

[0171] The attenuation coefficient under the single influence of snowy weather is determined based on the weather temperature, the communication channel frequency of the satellite communication, and the snow intensity, and the snow attenuation coefficient is obtained;

[0172] The snow attenuation coefficient is multiplied by the equivalent path length of communication attenuation to obtain a first prediction value.

[0173] Calculating the attenuation caused by each independent meteorological factor in complex weather environments, namely the predicted attenuation due to snow and the predicted attenuation due to fog and cloud, lays the foundation for the subsequent calculation of the total attenuation prediction value. The predicted attenuation value under the sole influence of snow, namely the first prediction value, can be calculated using a modified ITU-R P.838 model, fully considering the impact of weather temperature on signal attenuation.

[0174] The impact of snow crystals on signal attenuation varies significantly with their physical form, which is significantly affected by weather temperature. At low temperatures, snow crystals are dry and loose, with a minimal imaginary part of the complex dielectric constant, low absorption losses, and attenuation primarily due to scattering. As temperatures rise, the snow crystals melt, forming a liquid film on their surface. The imaginary part of the dielectric constant (dissipation factor) increases exponentially, exacerbating signal attenuation. The higher the frequency of the communication channel, the stronger the Mie resonance between the snow crystals and electromagnetic waves, resulting in greater dielectric losses and, consequently, greater signal attenuation.

[0175] Considering the geometric characteristics of satellite links, the equivalent path length L eff (θ) Calculate the first predicted value. The specific calculation formula of the first predicted value is as follows: S =γ S ·L eff (θ), where A S is the first predicted value, γ S is the snow attenuation coefficient, L eff (θ) is the equivalent path length.

[0176] In the present application, first, the signal attenuation influence coefficient under the single influence factor of snowfall is determined based on the weather temperature and the communication channel frequency of satellite communication, to obtain the snowfall attenuation coefficient; then the snowfall attenuation coefficient is multiplied by the equivalent path length of communication attenuation, to obtain the predicted attenuation value of signal attenuation under the single influence factor of snowfall, i.e. the first predicted value; thus the predicted attenuation value is closer to the actual situation, and the signal attenuation prediction is more accurate.

[0177] In some embodiments, the attenuation influence coefficient under the single influence of snowfall weather is determined based on the weather temperature, the communication channel frequency of satellite communication, and the snowfall intensity, to obtain the snowfall attenuation coefficient, including:

[0178] A second temperature correction coefficient is determined based on the weather temperature;

[0179] A communication frequency coefficient is determined based on the communication channel frequency;

[0180] The second temperature correction coefficient, the communication frequency coefficient, and the snowfall intensity corrected by the frequency correlation coefficient are multiplied to obtain the snowfall attenuation coefficient;

[0181] Wherein, the snowfall intensity corrected by the frequency correlation coefficient is determined by the following method:

[0182] A frequency correlation coefficient is determined based on the communication channel frequency;

[0183] The frequency correlation coefficient is multiplied by the snowfall intensity to obtain the snowfall intensity corrected by the frequency correlation coefficient.

[0184] Taking the modified ITU-R P.838 model as an example, the calculation process of the first predicted value is explained in further detail, as follows:

[0185] First, the communication frequency coefficient k(f) is determined based on the communication channel frequency, which is the frequency-related coefficient provided by the ITU-R P.838 model, and is the standard model parameter recommended by the International Telecommunication Union. The value range of the communication frequency coefficient k(f) under different communication channel frequencies is as follows:

[0186] Table 2 Value range table of communication frequency coefficient under different communication channel frequencies

[0187] Communication channel frequency Communication frequency coefficient k(f) value range Ka band (26-40 GHz) 0.1-0.4 Ku band (12-18 GHz) 0.02-0.1 X band (8-12 GHz) 0.01-0.04

[0188] Specifically, under Ka band (26-40 GHz), the communication frequency coefficient k(f) can be 0.1, 0.12, 0.15, 0.18, 0.2, 0.22, 0.25, 0.26, 0.28, 0.3, 0.32, 0.35, 0.36, 0.38, 0.4, or other values within the range shown in Table 2, without limitation. Under Ku band (12-18 GHz), the communication frequency coefficient k(f) can be 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, 0.05, 0.055, 0.06, 0.075, 0.08, 0.085, 0.09, 0.095, 0.1, or other values within the range shown in Table 2, without limitation. Under X band (8-12 GHz), the communication frequency coefficient k(f) can be 0.01, 0.012, 0.015, 0.018, 0.02, 0.022, 0.025, 0.028, 0.03, 0.032, 0.035, 0.038, 0.04, or other values within the range shown in Table 2, without limitation.

[0189] Secondly, a second temperature correction coefficient Ψ(T) is determined based on the weather temperature, the second temperature correction coefficient Ψ(T) being a temperature correction coefficient for correcting the attenuation calculation under the single influencing factor of snow weather in the ITU-R P.838 model, and the calculation formula thereof is as follows:

[0190]

[0191] wherein Ψ(T) is the second temperature correction coefficient; T ref is the reference temperature, which is 273 K (0℃); a is the second temperature sensitivity coefficient, and the value range thereof is 0.02-0.05; b is the non-linear index, and the value range thereof is 0.8-1.2, and T is the weather temperature. The specific value of the second temperature sensitivity coefficient a can be 0.02, 0.025, 0.028, 0.03, 0.035, 0.04, 0.045, 0.05, or other values within the range, without limitation; and the specific value of the non-linear index b can be 0.8, 0.85, 0.9, 0.95, 1, 1.05, 1.1, 1.15, 1.2, or other values within the range, without limitation.

[0192] Thirdly, the second temperature correction coefficient is multiplied by the communication frequency coefficient to obtain the temperature-corrected communication frequency coefficient k S (f, T), k S (f, T) = k(f) · Ψ(T).

[0193] Finally, the temperature-corrected communication frequency coefficient is multiplied by the snow intensity corrected by the frequency-related coefficient to obtain the snow attenuation coefficient γS The specific calculation formula is as follows:

[0194] γ S = k S (f, T) · S α (f) = k(f) · Ψ(T) · S α (f)

[0195] S α (f) = S · α(f)

[0196] Wherein, S α (f) is the snowfall intensity corrected by the frequency correlation coefficient, S is the snowfall intensity, and α(f) is the frequency correlation coefficient.

[0197] The frequency correlation coefficient is further determined by the communication channel frequency. Specifically, the value range of the frequency correlation coefficient α(f) under different communication channel frequencies is shown in the following table:

[0198] Table 3 Value range table of frequency correlation coefficient under different communication channel frequencies

[0199] Communication channel frequency Frequency-dependent coefficient α(f) value range Ka band (26-40 GHz) 0.9-8.5 Ku band (12-18 GHz) 0.95-9.0 X band (8-12 GHz) 0.98-9.5

[0200] Specifically, under Ka band (26-40GHz), the frequency correlation coefficient α(f) can be 0.9, 1.0, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6.0, 6.5, 7, 7.5, 8.0, 8.5, and also can be other values within the range shown in Table 3, without specific limitation. Under Ku band (12-18GHz), the frequency correlation coefficient α(f) can be 0.95, 1.0, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6.0, 6.5, 7, 7.5, 8.0, 8.5, 9.0, and also can be other values within the range shown in Table 3, without specific limitation. Under X band (8-12GHz), the frequency correlation coefficient α(f) can be 0.98, 1.0, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6.0, 6.5, 7, 7.5, 8.0, 8.5, 9.0, 9.5, and also can be other values within the range shown in Table 3, without specific limitation.

[0201] In this application, the snowfall attenuation coefficient is calculated by the second temperature correction coefficient, the communication frequency coefficient and the snowfall intensity corrected by the frequency correlation coefficient, fully considering various factors affecting signal attenuation in snowy weather, which can effectively improve the signal attenuation prediction accuracy.

[0202] In some embodiments, the calculation of the predicted attenuation value under the single influence of the cloudy weather obtains a second predicted value, comprising:

[0203] The cloud fog attenuation coefficient is obtained based on the satellite communication channel frequency, cloud liquid water content and liquid water temperature of the cloud fog weather under the single influence of the cloud fog weather.

[0204] The second prediction value is obtained by multiplying the cloud fog attenuation coefficient and the equivalent path length of the communication attenuation.

[0205] In the cloud fog weather, the cloud liquid water content determines the cloud droplet number density and size. The higher the cloud liquid water content, the greater the cloud droplet number density or size, and the scattering and absorption cross section increases, and the signal attenuation is linearly enhanced. Different communication channel frequencies, the signal attenuation caused by the cloud fog is also different, and the higher the frequency, the more severe the signal attenuation caused.

[0206] Specifically, the specific calculation formula of the second prediction value is as follows:

[0207] A C =G·L eff (θ)

[0208] Wherein, A C is the second prediction value, F is the cloud fog attenuation coefficient, and L eff (θ) is the equivalent path length.

[0209] In the present application, first, the signal attenuation influence coefficient under the single influence factor of the cloud fog is determined based on the satellite communication channel frequency, cloud liquid water content and liquid water temperature of the cloud fog weather, and the cloud fog attenuation coefficient is obtained; then the cloud fog attenuation coefficient is multiplied by the equivalent path length of the communication attenuation, that is, the signal attenuation prediction attenuation value under the single influence factor of the cloud fog is obtained, that is, the second prediction value; the prediction attenuation value determined thereby is closer to the actual situation, and the signal attenuation prediction is more accurate.

[0210] In some embodiments, the cloud fog attenuation coefficient is obtained based on the satellite communication channel frequency, cloud liquid water content and liquid water temperature of the cloud fog weather under the single influence of the cloud fog weather, comprising:

[0211] The cloud droplet dielectric property parameter is determined based on the liquid water temperature and the communication channel frequency;

[0212] The cloud fog attenuation coefficient is obtained by multiplying the cloud droplet dielectric property parameter and the cloud liquid water content.

[0213] The prediction attenuation value under the single influence of the cloud fog weather, that is, the second prediction value, can be calculated by using the ITU-R P.840 model. Taking the ITU-R P.840 model as an example, the calculation process of the second prediction value is explained in further detail, as follows:

[0214] First, the cloud droplet dielectric property parameter K is determined by the specific absorption coefficient calculation formulac (f,T), and the specific calculation formula is as follows:

[0215]

[0216] wherein ε'(f,T) is the real part of the dielectric constant of water, ε"(f,T) is the imaginary part of the dielectric constant of water, and f is the frequency of the communication channel. The specific value range of the real part of the dielectric constant of water ε'(f,T) and the imaginary part of the dielectric constant of water ε"(f,T) is as follows:

[0217] Table 4 Value range of the real part and the imaginary part of the dielectric constant of water at different liquid water temperatures and communication channel frequencies

[0218]

[0219] After determining the cloud droplet dielectric characteristic parameter according to the liquid water temperature in the cloud and fog and the communication channel frequency, the cloud droplet dielectric characteristic parameter is multiplied by the cloud liquid water content, and the cloud and fog attenuation coefficient can be obtained.

[0220] The cloud and fog attenuation coefficient G is specifically calculated by the following formula: G = K c (f,T)·M, wherein K c (f,T) is the cloud droplet dielectric characteristic parameter, and M is the cloud liquid water content.

[0221] In the present application, the cloud droplet dielectric characteristic parameter is first determined by the liquid water temperature and the communication channel frequency, and then the cloud and fog attenuation coefficient is obtained based on the cloud droplet dielectric characteristic parameter and the cloud liquid water content. Each influencing factor affecting signal attenuation under cloud and fog weather is fully considered, the calculation accuracy of the cloud and fog attenuation coefficient is effectively ensured, the signal attenuation prediction accuracy under complex meteorological environment is improved, and the stability of satellite communication is ensured.

[0222] In some embodiments, the equivalent path length is determined according to the following method:

[0223] The satellite elevation angle is obtained, and the equivalent path length is determined based on the satellite elevation angle.

[0224] In some embodiments, the determination of the equivalent path length based on the satellite elevation angle comprises:

[0225] The equivalent path length is determined by the following formula:

[0226]

[0227] wherein L eff (θ) is the equivalent path length, θ is the satellite elevation angle, and H atm is the effective height of the atmosphere.

[0228] The atmospheric effective height refers to the thickness of the atmosphere layer that has a significant influence on the satellite signal attenuation, represents the thickness of the layer in which the components causing attenuation in the atmosphere are compressed into a uniform distribution, and has a value range of 2-3 kilometers. In this application, the equivalent path length is calculated through the satellite elevation angle, effectively improving the calculation accuracy of the equivalent path length, thereby improving the signal attenuation prediction accuracy under complex weather conditions and ensuring the stability of satellite communication.

[0229] When the communication attenuation prediction calculation is performed by the method of the application, various meteorological parameter data such as the current weather snowfall intensity, cloud liquid water content in the cloud and fog, and weather temperature need to be collected and processed to provide standardized input for subsequent communication attenuation prediction. The satellite communication channel is affected by multiple meteorological factors, and these factors come from different weather stations and sensors, and the data formats are different, which need to be uniformly processed. Therefore, the collected communication channel frequency, current weather snowfall intensity, cloud liquid water content in the cloud and fog, weather temperature, satellite elevation angle and other related parameters are uniformly converted into a standard format, which is convenient for subsequent calculation and analysis. In the collection process of the foregoing related parameters, the directly obtainable parameters can be extracted by reading various sources of original weather records; for the parameters that cannot be directly obtained, the corresponding physical model or empirical formula is used for calculation and conversion; all parameters are converted into standard units and formats. In this process, for the common missing values and abnormal values, time series interpolation, spatial interpolation, and abnormal value screening and correction methods based on the 3σ principle are used to ensure the continuity and reliability of the data. By converting the meteorological observation data of different sources and different formats into a standardized parameter set with clear physical meaning, the data is unified in format, complete in physical meaning, and continuous in space and time, providing high-quality input data for subsequent single-factor attenuation calculation and coupling coefficient construction, thereby laying a data foundation for accurately simulating the coupling effect of snow and cloud.

[0230] The satellite communication attenuation prediction method for power communication in remote areas provided by the application can efficiently and accurately predict the signal attenuation of satellite communication under the complex weather conditions of snow and cloud coupling, so as to improve the reliability and performance of the high-frequency satellite communication system; through in-depth analysis of the electromagnetic wave propagation physical mechanism, the calculated electromagnetic coupling coefficient can accurately describe the electromagnetic interaction between snow crystals and cloud droplets, and establish an attenuation model that is more in line with the actual situation; at the same time, effectively predicting the additional attenuation caused by the electromagnetic interaction between snow crystals and cloud droplets can effectively overcome the prediction deviation of the traditional linear simple superposition method, and provide a scientific basis for the link design of the high-frequency satellite communication system under severe weather conditions.

[0231] The application is directed to the linear superposition error problem of the traditional weather attenuation model under the condition of snow and cloud coexistence, and innovatively proposes a multiplicative coupling model based on electromagnetic scattering theory. The propagation characteristics of electromagnetic waves in mixed media are analyzed from the Maxwell equation set, and the electromagnetic interaction between snow crystals and cloud droplets is accurately captured. The calculation method of the total attenuation prediction value proposed in the application not only retains the compatibility of the traditional linear superposition, but also accurately reflects the nonlinear coupling effect under complex weather conditions, providing a more reliable theoretical basis for satellite communication link design.

[0232] The technical effects of the application are further illustrated by the following experiments.

[0233] For the same weather environment of snow and cloud coexistence, the traditional linear superposition method and the satellite communication attenuation prediction method for power communication in remote areas of the application are used to predict the communication attenuation, and the real attenuation is detected as a comparison benchmark. The curves of the traditional linear superposition method, the application and the real attenuation with time change are shown in Figure 2 The specific calculation process of the traditional linear superposition method is as follows: the signal attenuation caused by snow weather and cloud weather is calculated respectively, and then the two calculated signal attenuations are added to obtain the total attenuation.

[0234] As can be clearly seen from Figure 2 , the attenuation curve of the application is closer to the real attenuation of satellite communication, and the prediction accuracy is higher, which realizes accurate prediction of signal attenuation and effectively guarantees the stability of satellite communication.

[0235] It should be noted that the method of the embodiments of the application can be executed by a single device, such as a computer or a server, etc. The method of the embodiments can also be applied to a distributed scenario, and completed by multiple devices cooperating with each other. In this distributed scenario, one of the multiple devices can only execute one or more steps in the method of the embodiments of the application, and the multiple devices will interact with each other to complete the method.

[0236] It should be noted that some embodiments of the application have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than the order described above and still achieve the desired results. In addition, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0237] Based on the same inventive concept, the application also provides a satellite communication attenuation prediction device for remote area power communication, corresponding to the method of any of the above embodiments.

[0238] Reference Figure 3 The satellite communication attenuation prediction device for remote area power communication is used to predict satellite communication attenuation when snow and cloud and mist coexist, and includes:

[0239] The snow attenuation prediction module 201 is used to calculate a predicted attenuation value under the influence of snow weather alone, to obtain a first predicted value;

[0240] The cloud and mist attenuation prediction module 202 is used to calculate a predicted attenuation value under the influence of cloud and mist weather alone, to obtain a second predicted value;

[0241] The coupling attenuation prediction module 203 is used to determine a predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets, based on a communication channel frequency of satellite communication, a snow intensity of current weather, a cloud liquid water content in cloud and mist, and a weather temperature, to obtain a third predicted value;

[0242] The total attenuation prediction module 204 is used to obtain a total attenuation prediction value of satellite communication, based on the first predicted value, the second predicted value, and the third predicted value.

[0243] In some embodiments, the coupling attenuation prediction module 203 includes:

[0244] The coupling coefficient calculation unit is used to determine an electromagnetic interaction influence coefficient between snow crystals and cloud droplets, based on the communication channel frequency, the snow intensity, the cloud liquid water content, and the weather temperature, to obtain an electromagnetic coupling coefficient;

[0245] The coupling attenuation calculation unit is used to multiply the electromagnetic coupling coefficient by an equivalent path length of communication attenuation, to obtain the third predicted value.

[0246] In some embodiments, the coupling coefficient calculation unit is also used to:

[0247] determine an electromagnetic interaction intensity coefficient between snow crystals and cloud droplets, based on the communication channel frequency;

[0248] determine a snow crystal number density, based on the snow intensity;

[0249] determine a cloud droplet number density, based on the cloud liquid water content;

[0250] determine a first temperature correction coefficient, based on the weather temperature;

[0251] determining an electromagnetic interaction influence coefficient between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, to obtain an electromagnetic coupling coefficient.

[0252] In some embodiments, the determining the snow crystal number density based on the snowfall intensity comprises:

[0253] The snow crystal number density is determined by the following formula:

[0254]

[0255] wherein n s is the snow crystal number density, κ s is the first temperature influence coefficient, S is the snowfall intensity, and α s is a snowfall characteristic index.

[0256] In some embodiments, the determining the cloud droplet number density based on the cloud liquid water content comprises:

[0257] The cloud droplet number density is determined by the following formula:

[0258]

[0259] wherein n c is the cloud droplet number density, κ c is the second temperature influence coefficient, M is the cloud liquid water content, and α c is a cloud fog characteristic index.

[0260] In some embodiments, the determining the first temperature correction coefficient based on the weather temperature comprises:

[0261] The first temperature correction coefficient is determined by the following formula:

[0262]

[0263] wherein η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitivity coefficient, and T ref is a reference temperature.

[0264] In some embodiments, the determining the electromagnetic interaction influence coefficient between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, to obtain an electromagnetic coupling coefficient comprises:

[0265] The electromagnetic coupling coefficient γ sc is determined by the following formula:

[0266] γ sc = ξ · ns • n c • σ ref • η(T)

[0267] wherein ξ is the electromagnetic interaction strength coefficient; n s is the number density of the snow crystals, n c is the number density of the cloud droplets, η(T) is the first temperature correction coefficient, σ ref is the reference extinction cross section.

[0268] In some embodiments, the snow attenuation prediction module 201 comprises:

[0269] a snow attenuation coefficient calculation unit configured to determine an attenuation impact coefficient under the influence of snow weather alone based on a weather temperature, a communication channel frequency of satellite communication, and a snow intensity, to obtain a snow attenuation coefficient;

[0270] a snow attenuation calculation unit configured to multiply the snow attenuation coefficient by an equivalent path length of communication attenuation, to obtain a first prediction value.

[0271] In some embodiments, the snow attenuation coefficient calculation unit is further configured to:

[0272] determine a second temperature correction coefficient based on the weather temperature;

[0273] determine a communication frequency coefficient based on the communication channel frequency;

[0274] multiply the second temperature correction coefficient, the communication frequency coefficient, and a frequency-correlation-coefficient-corrected snow intensity, to obtain the snow attenuation coefficient;

[0275] wherein the frequency-correlation-coefficient-corrected snow intensity is determined by the following method:

[0276] determine a frequency correlation coefficient based on the communication channel frequency;

[0277] multiply the frequency correlation coefficient and the snow intensity, to obtain the frequency-correlation-coefficient-corrected snow intensity.

[0278] In some embodiments, the cloud and fog attenuation prediction module 202 comprises:

[0279] a cloud and fog attenuation coefficient calculation unit configured to determine an attenuation impact coefficient under the influence of cloud and fog weather alone based on a communication channel frequency of satellite communication, a cloud liquid water content of cloud and fog weather, and a liquid water temperature, to obtain a cloud and fog attenuation coefficient;

[0280] a cloud and fog attenuation calculation unit configured to multiply the cloud and fog attenuation coefficient by an equivalent path length of communication attenuation, to obtain a second prediction value.

[0281] In some embodiments, the cloud attenuation coefficient calculation unit is further configured to:

[0282] determine a cloud droplet dielectric property parameter based on the liquid water temperature and the communication channel frequency;

[0283] multiply the cloud droplet dielectric property parameter by the cloud liquid water content to obtain the cloud attenuation coefficient.

[0284] In some embodiments, the equivalent path length is determined according to the following method:

[0285] obtain a satellite elevation angle, and determine the equivalent path length based on the satellite elevation angle.

[0286] In some embodiments, the determination of the equivalent path length based on the satellite elevation angle comprises:

[0287] determine the equivalent path length by the following formula:

[0288]

[0289] wherein L eff (θ) is the equivalent path length, θ is the satellite elevation angle, H atm is the effective height of the atmosphere.

[0290] For the convenience of description, the above apparatus is described in various modules according to functions. Of course, the functions of the modules can be implemented in one or more software and / or hardware in the implementation of the present application.

[0291] The apparatus of the above embodiments is used to implement the satellite communication attenuation prediction method for remote area power communication in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described here again.

[0292] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of any of the above embodiments when executing the program.

[0293] Figure 4 A more specific hardware structure of an electronic device provided by the present embodiment is shown, which can include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 for communication within the device.

[0294] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., for executing relevant programs to implement the technical solutions provided by the embodiments of the present specification.

[0295] The memory 1020 can be implemented by a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called and executed by the processor 1010.

[0296] The input / output interface 1030 is configured to connect input / output modules to realize information input and output. The input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input devices can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices can include a display, a speaker, a vibrator, an indicator light, etc.

[0297] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to realize the communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as USB, network cable, etc.) or through a wireless manner (such as mobile network, WIFI, Bluetooth, etc.).

[0298] The bus 1050 includes a path for transmitting information between various components (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0299] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only include the components necessary to implement the solutions of the embodiments of the present specification, and does not have to include all the components shown in the figure.

[0300] The electronic device of the above embodiment is used to implement the satellite communication attenuation prediction method for remote area power communication in any of the preceding embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0301] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the satellite communication attenuation prediction method for remote area power communication in any of the above embodiments.

[0302] The computer-readable medium of the present embodiment includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0303] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to perform the satellite communication attenuation prediction method for remote area power communication in any of the above embodiments, and have the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0304] Based on the same concept, corresponding to the method of any of the above embodiments, the present application also provides a computer program product comprising computer program instructions for causing the computer to perform the method of any of the above embodiments when the computer program instructions are run on the computer, having the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0305] It can be understood that before using the technical solutions of the various embodiments of the present application, the user will be informed of the type, scope of use, use scenario, etc. of the personal information involved by appropriate means, and the authorization of the user will be obtained.

[0306] For example, in response to receiving the active request of the user, the user is sent prompt information to explicitly prompt the user that the operation requested to be performed will require obtaining and using personal information of the user. Thus, the user can autonomously choose whether to provide the personal information to the software or hardware, such as an electronic device, an application program, a server, or a storage medium, performing the operation of the technical solution of the application according to the prompt information.

[0307] As an optional but non-limiting implementation, in response to receiving the active request of the user, the user is sent prompt information in the form of a pop-up window, for example, in which the prompt information can be presented in the form of text. In addition, the pop-up window can also carry selection controls for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0308] It can be understood that the above notification and obtaining of user authorization process is only illustrative, and does not limit the implementation of the application, and other ways that meet the relevant laws and regulations can also be applied to the implementation of the application.

[0309] Those skilled in the art will understand that the discussion of any of the above embodiments is merely exemplary and is not intended to suggest that the scope of the application is limited to these examples; the above embodiments or technical features among different embodiments can also be combined, steps can be implemented in any order, and there are many other changes to the aspects of the embodiments of the application as described above. In order to be brief, they are not provided in detail.

[0310] In addition, in order to simplify the description and discussion, and so as not to make the embodiments of the application difficult to understand, the known power / ground connections of integrated circuit (IC) chips and other components can or can not be shown in the provided drawings. In addition, the devices can be shown in the form of block diagrams in order to avoid making the embodiments of the application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented (i.e., these details should be fully within the understanding of those skilled in the art). Where specific details (e.g., circuitry) are set forth in order to describe an illustrative embodiment of the application, it will be apparent to those skilled in the art that the embodiments of the application can be practiced without these specific details or with variations on these specific details. Therefore, these descriptions should be considered as illustrative rather than limiting.

[0311] Although the application has been described in conjunction with specific embodiments thereof, many alternatives, modifications and variations will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) can use the embodiments discussed.

[0312] Embodiments of the present application are intended to cover any and all such substitutions, modifications, and variations. Accordingly, any one of the above-described embodiments of the present application can be replaced by any other disclosed embodiments of the present application, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can be substituted for any other disclosed series, and the entirety of any disclosed series can

Claims

1. A method for satellite communication attenuation prediction for remote area power communication, characterized by, A method for predicting satellite communication attenuation in the presence of snow and cloud, comprising: calculating a predicted attenuation value under the single influence of snow weather to obtain a first predicted value; calculating a predicted attenuation value under the single influence of cloud weather to obtain a second predicted value; determining a predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets based on a satellite communication channel frequency, a current weather snow intensity, a cloud liquid water content in cloud, and a weather temperature to obtain a third predicted value; obtaining a total attenuation prediction value of satellite communication based on the first predicted value, the second predicted value, and the third predicted value.

2. The method for predicting satellite communication attenuation for power communication in remote areas as claimed in claim 1, wherein The method for determining a predicted attenuation value additionally increased due to electromagnetic interaction between snow crystals and cloud droplets based on a satellite communication channel frequency, a current weather snow intensity, a cloud liquid water content in cloud, and a weather temperature to obtain a third predicted value, comprises: determining an electromagnetic coupling coefficient based on the communication channel frequency, the snow intensity, the cloud liquid water content, and the weather temperature; multiplying the electromagnetic coupling coefficient by an equivalent path length of communication attenuation to obtain the third predicted value.

3. The method for predicting satellite communication attenuation for remote area power communication according to claim 2, wherein, The method for determining an electromagnetic coupling coefficient based on the communication channel frequency, the snow intensity, the cloud liquid water content, and the weather temperature, comprises: determining an electromagnetic interaction intensity coefficient between snow crystals and cloud droplets based on the communication channel frequency; determining a snow crystal number density based on the snow intensity; determining a cloud droplet number density based on the cloud liquid water content; determining a first temperature correction coefficient based on the weather temperature; determining an electromagnetic coupling coefficient based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient.

4. The method for satellite communication attenuation prediction for remote area electricity communication as claimed in claim 3 wherein, The method for determining a snow crystal number density based on the snow intensity, comprises: determining the snow crystal number density by the following formula: where n s is the snow crystal number density, κ s is the first temperature influence coefficient, S is the snowfall intensity, and α s is the snowfall characteristic exponent.

5. The method for satellite communication attenuation prediction for remote area electricity communication as claimed in claim 3 wherein, The method for determining a cloud droplet number density based on the cloud liquid water content, comprises: determining the cloud droplet number density by the following formula: where n c Cloud droplet number density, κ c is a second temperature influence coefficient, M is cloud liquid water content, a c is a cloud fog characteristic index.

6. The method for satellite communication attenuation prediction for remote area electricity communication as claimed in claim 3 wherein, The method for determining a first temperature correction coefficient based on the weather temperature, comprises: determining the first temperature correction coefficient by the following formula: wherein η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitivity coefficient, T ref is a reference temperature.

7. The method for satellite communication attenuation prediction for remote area electricity communication as claimed in claim 3 wherein, The method for determining an electromagnetic coupling coefficient based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, comprises: The electromagnetic coupling coefficient γ is determined by the following equation sc : γ sc = ξ · n s · n c · σ ref · η(T) where ξ is the electromagnetic interaction strength coefficient; n s is the snow crystal number density, n c is the cloud droplet number density, η(T) is the first temperature correction coefficient, σ ref is the reference extinction cross section.

8. The method for satellite communication attenuation prediction for remote area electricity communication as claimed in claim 1 wherein, The method for calculating a predicted attenuation value under the single influence of snow weather to obtain a first predicted value, comprises: determining a snow attenuation coefficient based on a weather temperature, a satellite communication channel frequency, and a snow intensity to obtain a snow attenuation coefficient; multiplying the snow attenuation coefficient by an equivalent path length of communication attenuation to obtain the first predicted value.

9. The method for satellite communication attenuation prediction for remote area electricity communication according to claim 8, characterized in that, The method for determining a snow attenuation coefficient based on a weather temperature, a satellite communication channel frequency, and a snow intensity, comprises: determining a second temperature correction coefficient based on the weather temperature; determining a communication frequency coefficient based on the communication channel frequency; multiplying the second temperature correction coefficient, the communication frequency coefficient and the snowfall intensity corrected by a frequency correlation coefficient to obtain the snowfall attenuation coefficient; wherein the snowfall intensity corrected by the frequency correlation coefficient is determined by the following method: determining a frequency correlation coefficient based on the communication channel frequency; multiplying the frequency correlation coefficient and the snowfall intensity to obtain the snowfall intensity corrected by the frequency correlation coefficient.

10. The satellite communication attenuation prediction method for remote area power communication according to claim 1, characterized in that: the calculation of the predicted attenuation value under the single influence of cloud and fog weather to obtain a second predicted value, comprising: determining an attenuation influence coefficient under the single influence of cloud and fog weather based on the communication channel frequency of satellite communication, the cloud liquid water content of cloud and fog weather and the liquid water temperature to obtain a cloud and fog attenuation coefficient; multiplying the cloud and fog attenuation coefficient and the equivalent path length of communication attenuation to obtain the second predicted value.

11. The method for satellite communication attenuation prediction for remote area electricity communication according to claim 10, wherein, the determination of the attenuation influence coefficient under the single influence of cloud and fog weather based on the communication channel frequency of satellite communication, the cloud liquid water content of cloud and fog weather and the liquid water temperature to obtain a cloud and fog attenuation coefficient, comprising: determining a cloud droplet dielectric property parameter based on the liquid water temperature and the communication channel frequency; multiplying the cloud droplet dielectric property parameter and the cloud liquid water content to obtain the cloud and fog attenuation coefficient.

12. The method for predicting satellite communication attenuation for remote area power communication according to any one of claims 2-11, characterized in that, the determination of the equivalent path length according to the following method: obtaining a satellite elevation angle and determining the equivalent path length based on the satellite elevation angle.

13. The method for satellite communication attenuation prediction for remote area electricity communication according to claim 12, wherein, the determination of the equivalent path length based on the satellite elevation angle, comprising: determining the equivalent path length by the following formula: where L eff (θ) is the equivalent path length, θ is the satellite elevation angle, H atm is the effective atmospheric height.

14. A satellite communication attenuation prediction device for remote area power communication, characterized by, a method for predicting satellite communication attenuation when snow and cloud and fog coexist, comprising: a snowfall attenuation prediction module for calculating a predicted attenuation value under the single influence of snowfall weather to obtain a first predicted value; a cloud and fog attenuation prediction module for calculating a predicted attenuation value under the single influence of cloud and fog weather to obtain a second predicted value; a coupling attenuation prediction module for determining a predicted attenuation value additionally increased due to electromagnetic interaction between snow crystal and cloud droplet based on the communication channel frequency of satellite communication, the snowfall intensity of current weather, the cloud liquid water content in cloud and fog and weather temperature to obtain a third predicted value; a total attenuation prediction module for obtaining a total attenuation prediction value of satellite communication based on the first predicted value, the second predicted value and the third predicted value.

15. The satellite communication attenuation prediction device for remote area electricity communication according to claim 14, wherein, the coupling attenuation prediction module, comprising: a coupling coefficient calculation unit for determining an influence coefficient of electromagnetic interaction between snow crystal and cloud droplet based on the communication channel frequency, the snowfall intensity, the cloud liquid water content and the weather temperature to obtain an electromagnetic coupling coefficient; a coupling attenuation calculation unit for multiplying the electromagnetic coupling coefficient and the equivalent path length of communication attenuation to obtain the third predicted value.

16. The satellite communication attenuation prediction device for remote area electricity communication according to claim 15, wherein, the coupling coefficient calculation unit is further used for: determining an electromagnetic interaction intensity coefficient between snow crystal and cloud droplet based on the communication channel frequency; determining a snow crystal number density based on the snowfall intensity; determining a cloud droplet number density based on the cloud liquid water content; determining a first temperature correction coefficient based on the weather temperature; determining an electromagnetic interaction influence coefficient between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, to obtain an electromagnetic coupling coefficient.

17. The satellite communication attenuation prediction device for remote area electricity communication according to claim 16, wherein, The determining the snow crystal number density based on the snowfall intensity comprises: The snow crystal number density is determined by the following formula: where n s is the snow crystal number density, κ s is the first temperature influence coefficient, S is the snowfall intensity, and α s is the snowfall characteristic exponent.

18. The satellite communication attenuation prediction device for remote area electricity communication according to claim 16, wherein, The determining the cloud droplet number density based on the cloud liquid water content comprises: The cloud droplet number density is determined by the following formula: where n c Cloud droplet number density, κ c is the second temperature influence coefficient, M is the cloud liquid water content, α c is the cloud fog characteristic index.

19. The satellite communication attenuation prediction device for remote area electricity communication according to claim 16, wherein, The determining the first temperature correction coefficient based on the weather temperature comprises: The first temperature correction coefficient is determined by the following formula: wherein η(T) is the first temperature correction coefficient, T is the weather temperature, γ is a first temperature sensitivity coefficient, T ref is a reference temperature.

20. The satellite communication attenuation prediction device for remote area power communication according to claim 16, characterized in that: The determining an electromagnetic interaction influence coefficient between snow crystals and cloud droplets based on the electromagnetic interaction intensity coefficient, the snow crystal number density, the cloud droplet number density, and the first temperature correction coefficient, to obtain an electromagnetic coupling coefficient comprises: The electromagnetic coupling coefficient γ is determined by the following equation sc : γ sc = ξ · n s · n c · σ ref · η(T) where ξ is the electromagnetic interaction strength coefficient; n s is the snow crystal number density, n c is the cloud droplet number density, η(T) is the first temperature correction coefficient, σ ref is the reference extinction cross section.

21. The satellite communication attenuation prediction device for remote area electricity communication according to claim 14, wherein, The snowfall attenuation prediction module comprises: A snowfall attenuation coefficient calculation unit is configured to determine an attenuation influence coefficient under the influence of snowfall weather only based on a weather temperature, a communication channel frequency of satellite communication, and a snowfall intensity, to obtain a snowfall attenuation coefficient. A snowfall attenuation calculation unit is configured to multiply the snowfall attenuation coefficient by an equivalent path length of communication attenuation, to obtain a first prediction value.

22. The satellite communication attenuation prediction device for remote area electricity communication according to claim 21, wherein, The snowfall attenuation coefficient calculation unit is further configured to: determine a second temperature correction coefficient based on the weather temperature; determine a communication frequency coefficient based on the communication channel frequency; multiply the second temperature correction coefficient, the communication frequency coefficient, and the snowfall intensity corrected by a frequency correlation coefficient, to obtain the snowfall attenuation coefficient; The snowfall intensity corrected by the frequency correlation coefficient is determined by the following method: determine a frequency correlation coefficient based on the communication channel frequency; multiply the frequency correlation coefficient by the snowfall intensity, to obtain the snowfall intensity corrected by the frequency correlation coefficient.

23. The satellite communication attenuation prediction device for remote area electricity communication according to claim 14, wherein, The cloud and fog attenuation prediction module comprises: A cloud and fog attenuation coefficient calculation unit is configured to determine an attenuation influence coefficient under the influence of cloud and fog weather only based on a communication channel frequency of satellite communication, a cloud liquid water content of cloud and fog weather, and a liquid water temperature, to obtain a cloud and fog attenuation coefficient. A cloud and fog attenuation calculation unit is configured to multiply the cloud and fog attenuation coefficient by an equivalent path length of communication attenuation, to obtain a second prediction value.

24. The satellite communication attenuation prediction device for remote area electricity communication according to claim 23, wherein, The cloud and fog attenuation coefficient calculation unit is further configured to: determine a cloud droplet dielectric property parameter based on the liquid water temperature and the communication channel frequency; multiply the cloud droplet dielectric property parameter by the cloud liquid water content, to obtain the cloud and fog attenuation coefficient.

25. The apparatus for predicting attenuation of satellite communications for remote electric power communications according to any one of claims 15 to 24, characterized in that, The equivalent path length is determined according to the following method: obtain a satellite elevation angle, and determine the equivalent path length based on the satellite elevation angle.

26. The satellite communication attenuation prediction device for remote area electricity communication according to claim 25, wherein, The determining the equivalent path length based on the satellite elevation angle comprises: The equivalent path length is determined by the following formula: where L eff (θ) is the equivalent path length, θ is the satellite elevation angle, H atm is the effective atmospheric height.

27. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor implements the satellite communication attenuation prediction method for remote area power communication according to any one of claims 1 to 13 when executing the program.

28. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to make the computer execute the satellite communication attenuation prediction method for remote area power communication according to any one of claims 1 to 13.

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