A method and device for calculating artificial noise based on land cover data

Abstract

The specification provides a method and device for calculating artificial noise based on land cover data, wherein the method comprises: obtaining land cover data of a target area; dividing the target area into a plurality of sub-areas; determining an artificial noise coefficient of each sub-area according to a land cover type corresponding to each sub-area; calculating an artificial noise power of each sub-area according to the artificial noise coefficient of each sub-area, and obtaining artificial noise data of the target area. Through the method and device for calculating artificial noise based on land cover data provided by the specification, by dividing the target area into a plurality of sub-areas, determining the artificial noise coefficient according to the land cover type corresponding to each sub-area, and calculating the artificial noise power of each sub-area respectively, the spatial distribution of the artificial noise power changing with the geographical position can be obtained, reflecting the difference in artificial noise at different positions in the target area.

Description

Technical Field

[0001] This specification relates to the field of simulation and analysis technology for wireless communication systems, and for example to a method and apparatus for calculating artificial noise based on land cover data. Background Technology

[0002] In the simulation and analysis of wireless communication systems, it is necessary to model and quantify background environmental noise. Besides natural noise, background environmental noise also includes anthropogenic noise generated by human activities. Anthropogenic noise directly affects the quality of signal transmission, thereby impacting the overall performance of the communication system. Existing methods for calculating anthropogenic noise typically employ statistical parameterization models, empirically assigning anthropogenic noise coefficients to regions based on rough environmental categories such as cities, suburbs, and rural areas; or they use precise electromagnetic propagation models to calculate the distribution of anthropogenic noise point-by-point across the region.

[0003] However, statistical parameterization relies on empirical parameter settings and lacks reliable spatial references, failing to reflect the spatial variations in noise caused by differences in human activity density within the same environmental category, resulting in low spatial resolution. Precise modeling methods, on the other hand, are computationally intensive and time-consuming in large-scale scenarios, failing to meet the need for rapid computation. Therefore, existing methods for calculating artificial noise struggle to achieve rapid generation while maintaining quantitative accuracy over large spatial scales, thus failing to meet the demands of wireless communication system simulations for high-resolution noise spatial distribution calculations. Summary of the Invention

[0004] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0005] Firstly, embodiments of this specification propose a method for calculating anthropogenic noise based on land cover data, including: Obtain land cover data for the target area; The target region is divided into multiple sub-regions; The anthropogenic noise coefficient of each sub-region is determined based on the land cover type corresponding to each sub-region; Based on the anthropogenic noise coefficient of each sub-region, the anthropogenic noise power of each sub-region is calculated to obtain the anthropogenic noise data of the target region.

[0006] Secondly, embodiments of this specification also propose an anthropogenic noise calculation device based on land cover data, comprising: The acquisition module is used to acquire land cover data for the target area; A partitioning module is used to divide the target region into multiple sub-regions; The determination module is used to determine the anthropogenic noise coefficient of each sub-region based on the land cover type corresponding to each sub-region; The calculation module is used to calculate the anthropogenic noise power of each sub-region based on the anthropogenic noise coefficient of each sub-region, and obtain the anthropogenic noise data of the target region.

[0007] The method and apparatus for calculating anthropogenic noise in land cover data provided in the embodiments of this specification have the following technical effects: By dividing the target area into multiple sub-regions, determining the anthropogenic noise coefficient based on the land cover type of each sub-region, and calculating the anthropogenic noise power of each sub-region separately, the spatial distribution of anthropogenic noise power as a function of geographical location can be obtained, reflecting the differences in anthropogenic noise at different locations within the target area. This approach eliminates the need to investigate each anthropogenic noise source individually or to build electromagnetic models of buildings, electronic equipment, and power facilities. It reduces the difficulty of data acquisition, model building workload, and computational burden in large-scale scenarios, providing fundamental data for regional noise simulation of wireless communication systems.

[0008] Furthermore, by classifying and processing image map data or reading land cover data corresponding to the target area from a preset land cover dataset, it is possible to adapt to different land cover data sources and provide standardized data input for the calculation of human-caused noise in each sub-region.

[0009] Furthermore, by first determining the anthropogenic noise environment type of each sub-region based on the land cover type, and then determining the anthropogenic noise coefficient based on the anthropogenic noise environment type, land cover information can be converted into parameters required for anthropogenic noise power calculation, thereby improving the consistency of anthropogenic noise coefficient determination for each sub-region.

[0010] Furthermore, by pre-setting the correspondence between land cover type and anthropogenic noise environment type, the anthropogenic noise environment type of each sub-region can be determined according to a unified classification rule, thereby improving the classification efficiency and consistency of classification results among multiple sub-regions within the target area.

[0011] Furthermore, by statistically analyzing the proportion of each land cover type within a sub-region, we can comprehensively consider the composition of multiple land cover types within the same sub-region, reducing the bias caused by determining the type of anthropogenic noise environment based solely on a single land cover type.

[0012] Furthermore, by using multi-level thresholds for building proportion and the sum of building proportion and cultivated land proportion, it is possible to distinguish between high-density building areas, low-density building areas, agricultural activity areas, and low-human activity areas, thus providing clear and interconnected standards for determining the type of anthropogenic noise environment.

[0013] Furthermore, by combining the artificial noise figure with the reference temperature and the receiver's equivalent noise bandwidth, the artificial noise figure characterizing the environmental noise level can be converted into artificial noise power under the corresponding receiving conditions, thereby obtaining power data that can be used for subsequent communication simulations.

[0014] Furthermore, by storing the geographic coordinates, land cover type, anthropogenic noise environment type, and anthropogenic noise power of each sub-region, spatial distribution data of anthropogenic noise with spatial indexing can be formed, making it convenient to query and retrieve the corresponding anthropogenic noise power according to geographic location.

[0015] Furthermore, by associating and organizing natural noise data with man-made noise data according to the geographical location of each sub-region, it is possible to provide natural noise information and man-made noise information corresponding to each spatial location in the same dataset, providing a data foundation for subsequent background noise calculation or communication performance evaluation based on specific simulation models.

[0016] The above general description and the descriptions below are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0017] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein: Figure 1 This is a flowchart of an anthropogenic noise calculation method based on land cover data, provided in Embodiment 1 of this specification; Figure 2 This is a schematic diagram of a man-made noise calculation device based on land cover data, provided in Embodiment 2 of this specification. Detailed Implementation

[0018] To provide a more detailed understanding of the features and technical content of the embodiments of this specification, the implementation of the embodiments is described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this specification. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0019] The terms "first," "second," etc., in the description, claims, and accompanying drawings of the embodiments herein are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of the present specification described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0020] In the embodiments of this specification, the terms "upper," "lower," "inner," "middle," "outer," "front," and "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily used to better describe the embodiments of this specification and their implementations, and are not intended to limit the indicated devices, elements, or components to having a specific orientation, or to construct and operate in a specific orientation. Furthermore, some of the above terms may be used to indicate other meanings besides orientation or positional relationship; for example, the term "upper" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in the embodiments of this specification according to the specific circumstances.

[0021] Furthermore, the terms "set up," "connect," and "fix" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this specification according to the specific circumstances.

[0022] Unless otherwise stated, the term "multiple" means two or more.

[0023] In the embodiments described in this specification, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0024] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0025] It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this specification can be combined with each other.

[0026] In the simulation and analysis of wireless communication systems, background environmental noise can affect signal transmission quality and system performance. Background environmental noise includes not only natural noise but also anthropogenic noise generated by human activities such as electronic devices and power facilities. To ensure that wireless channel simulations accurately reflect the actual electromagnetic environment at different geographical locations, it is necessary to determine the spatial distribution of anthropogenic noise within the target area.

[0027] Traditional anthropomorphic noise models typically set noise parameters according to environmental categories such as urban, residential, and rural areas, making it difficult to reflect spatial differences within the same environmental category caused by variations in land cover and human activity density. If precise electromagnetic modeling is performed on each building and other noise source within the target area, the computational load in urban-level scenarios would be enormous, making it difficult to meet the needs of real-time or near-real-time communication simulations.

[0028] Based on the above problems, this application provides a method for calculating anthropogenic noise based on land cover data. The method uses land cover data as the correlation medium between the geospatial information of the target area and the anthropogenic noise model. The target area is divided into multiple sub-regions, and the conversion of "land cover type - anthropogenic noise coefficient - anthropogenic noise power" is completed for each sub-region to obtain the anthropogenic noise data of the target area.

[0029] Example 1 In some embodiments, such as Figure 1 As shown, the method includes: Step 100: Obtain land cover data for the target area; Step 102: Divide the target area into multiple sub-regions; Step 104: Determine the anthropogenic noise coefficient for each sub-region based on the land cover type corresponding to each sub-region; Step 106: Calculate the anthropogenic noise power of each sub-region based on the anthropogenic noise coefficient of each sub-region, and obtain the anthropogenic noise data of the target region.

[0030] Land cover data is used to characterize the land cover status at different locations within the target area. After dividing the target area into multiple sub-regions, the anthropogenic noise coefficient can be determined based on the land cover status of each sub-region, and the anthropogenic noise power of each sub-region can be further calculated. This allows us to obtain the spatial distribution of anthropogenic noise power as a function of geographical location, without needing to establish an electromagnetic model for each anthropogenic noise source individually.

[0031] In some embodiments, land cover data includes land cover types corresponding to each location within the target area. Land cover types include ten categories: water bodies, woodland, grassland, submerged vegetation, cultivated land, shrubs, buildings, bare land, snow / ice, and clouds.

[0032] The land cover types mentioned above can be encoded using code values. For example, the ten land cover types can be labeled with code values ​​1 to 10 respectively; if a location does not belong to any of the above land cover types, the code value for that location can be recorded as 0.

[0033] This application provides two methods for obtaining land cover data.

[0034] The first method involves classifying and processing the image map data of the target area to obtain land cover data.

[0035] Specifically, two-dimensional image map data of the target area can be acquired, and the original grid points in the two-dimensional image map data can be classified to determine the land cover type corresponding to each original grid point. The spatial resolution of the image map data can be 10m, that is, each original grid point corresponds to a geographic area of ​​10m×10m; other disclosed spatial resolutions, such as 30m, can also be used.

[0036] Classification can be performed using image recognition methods based on the training set. For each original grid point, based on the corresponding image data, it is determined whether it belongs to one of the following categories: water body, woodland, grassland, submerged vegetation, cultivated land, shrubs, buildings, bare land, snow / ice, or clouds. If the land cover type can be determined, the data value of the original grid point is set to the corresponding code value; if it cannot be determined to belong to any of the above types, the data value of the original grid point is set to 0. After classifying all original grid points within the target area, two-dimensional land cover data of the target area is obtained.

[0037] The second method is to obtain land cover data for the target area from a preset land cover dataset.

[0038] The preset land cover dataset can be a pre-generated dataset based on imagery or remote sensing data. Users can retrieve the data corresponding to the target area from the preset land cover dataset according to the geographical extent of the target area. The input format of the land cover data can be GeoTIFF or NetCDF format. The finished land cover dataset can be, for example, land cover data generated based on 10m spatial resolution imagery data, or land cover data with a spatial resolution of 30m.

[0039] Both methods described above can obtain the land cover type corresponding to each location within the target area. The choice of method depends on the availability of image map data, the final dataset, and the spatial resolution required for communication simulation.

[0040] After obtaining the land cover data of the target area, the target area is divided into multiple sub-regions according to the preset spatial resolution.

[0041] In some embodiments, the target area is divided into multiple uniformly distributed rectangular grids, each rectangular grid constituting a sub-region. The size of the sub-region can be 1km × 1km or larger, and the specific size is determined according to the spatial resolution of the communication system simulation.

[0042] Each subregion comprises one or more original grid points of land cover data. Each original grid point has a corresponding land cover type and geographic coordinates. Therefore, a subregion may correspond to only one land cover type or may contain multiple land cover types.

[0043] For example, if the original grid size of land cover data is 10m×10m and the sub-region size is 1km×1km, each sub-region contains 100×100, or 10,000, original grid points. The anthropogenic noise coefficient corresponding to the sub-region can be determined based on the land cover type of these 10,000 original grid points.

[0044] For a sub-region containing multiple land cover types, a representative land cover type can be identified for the sub-region, and the anthropogenic noise coefficient can be determined based on the representative land cover type; alternatively, the proportion of each land cover type within the sub-region can be statistically analyzed, and the anthropogenic noise coefficient can be determined based on the proportion of each land cover type. These two processing paths are described in the following embodiments.

[0045] In some embodiments, the anthropogenic noise coefficient of each sub-region is determined based on the land cover type corresponding to each sub-region, including: Based on the land cover type corresponding to each sub-region, determine the anthropogenic noise environment type of each sub-region; The anthropogenic noise coefficient of each sub-region is determined based on the anthropogenic noise environment type of each sub-region.

[0046] Anthropogenic noise environments can be categorized into urban, residential, rural, and quiet rural environments. These four types of anthropogenic noise environments correspond to different densities of human activity and levels of anthropogenic electromagnetic noise.

[0047] In some embodiments, a mapping relationship between land cover type and anthropogenic noise environment type is established in advance. When performing anthropogenic noise calculation, this mapping relationship is obtained, and the mapping relationship is queried according to the land cover type corresponding to each sub-region to determine the anthropogenic noise environment type of each sub-region.

[0048] The mapping relationship can be stored in the form of a mapping table. The mapping table records the correspondence between land cover type and one of the following environments: urban environment, residential environment, rural environment, and quiet rural environment. The specific correspondence can be pre-set according to the land material characteristics of the target area and fixed before the calculation of anthropogenic noise in the target area.

[0049] For example, a mapping relationship can be established between building types and urban or residential environments, between arable land and grassland and rural environments, and between woodland and bare land and tranquil rural environments. When establishing a mapping relationship for a target area, it is pre-determined whether the building type corresponds to an urban or residential environment.

[0050] When a sub-region includes multiple land cover types, the land cover type with the largest area in the sub-region can be identified as the representative land cover type. Then, the mapping relationship can be queried based on the representative land cover type to determine the anthropogenic noise environment type of the sub-region.

[0051] In other embodiments, the proportion of each land cover type in each sub-region is statistically analyzed, and the anthropogenic noise environment type of each sub-region is determined based on the proportion of each land cover type.

[0052] Specifically, the original grid points within a sub-region are statistically analyzed, and the ratio of the number of original grid points for each land cover type to the total number of original grid points in the sub-region is calculated to obtain the proportion of each land cover type in the sub-region.

[0053] In some embodiments, the type of anthropogenic noise environment is determined in the following order: If buildings account for more than 50% of the total area within a sub-area, the anthropogenic noise environment type of that sub-area is defined as an urban environment. If the proportion of buildings in a sub-area is less than 50% but more than 10%, the anthropogenic noise environment type of that sub-area is defined as a residential environment. If the proportion of buildings in a sub-region does not exceed 10%, and the sum of the proportion of buildings and the proportion of cultivated land exceeds 0.5%, the anthropogenic noise environment type of the sub-region is determined to be rural environment. If none of the above conditions are met, the anthropogenic noise environment type of this sub-region is determined to be a quiet rural environment.

[0054] The above conditions are applied in descending order of building proportion.

[0055] For example, when a subregion contains 10,000 original grid points, if more than 5,000 of these original grid points have building land cover, then the building proportion exceeds 50%, and the subregion is defined as an urban environment. If the number of building type original grid points is no more than 5,000 but more than 1,000, the subregion is defined as a residential environment. If the building proportion is less than 10%, but the sum of the number of building type and cultivated land type original grid points exceeds 50, the subregion is defined as a rural environment. In other cases, the subregion is defined as a quiet rural environment.

[0056] Determining based on mapping relationships and determining based on the proportion of land cover types are two alternative implementation methods for determining the type of anthropogenic noise environment, and they do not need to be executed simultaneously in the same calculation process.

[0057] After determining the anthropogenic noise environment type of each sub-region, the anthropogenic noise coefficient of each sub-region is determined according to the anthropogenic noise environment type and typical frequency points, based on the preset correspondence between environment type, frequency and anthropogenic noise coefficient.

[0058] As can be seen from the above introduction, this application uses a multi-level threshold rule based on the building ratio and the sum of the building ratio and the cultivated land ratio to convert high-resolution land cover data into sub-regional anthropogenic noise environment types. This allows for the generation of anthropogenic noise data that reflects the spatial differences within the target area without modeling specific anthropogenic noise sources one by one, thus balancing the computational efficiency of large-scale communication simulation with the accuracy of the spatial distribution of anthropogenic noise.

[0059] Typical frequency points are determined based on the operating frequency band of the receiving channel to be evaluated. For single-frequency communication systems, the receiver's operating frequency is determined as the typical frequency point; for communication systems with a certain operating bandwidth that are suitable for characterization using the center frequency, the center frequency of the receiving operating bandwidth can be determined as the typical frequency point.

[0060] In some embodiments, the human-caused noise figure is calculated according to the following formula: F am = c d ·lg f in, F am The figure represents the human-caused noise figure, expressed in dB. f Typical frequency points, in MHz; c and d These are preset constants corresponding to the types of man-made noise environments.

[0061] It should be noted that the human noise figure in this embodiment... F am , refers to the median external anthropogenic noise factor, expressed in dB, of additive white Gaussian noise (AWGN) under typical outdoor conditions. For ease of description, this paper simply refers to it as the anthropogenic noise figure. According to F am Calculated anthropogenic noise power P n , which represents the median available external man-made noise power at the input of the equivalent lossless receiving antenna under the corresponding reference conditions.

[0062] here, cand d The possible values ​​are shown in Table 1 below: Table 1

[0063] In this embodiment, the typical frequency point is located within the applicable frequency range of the artificial noise model used in each sub-region. For urban, residential, and rural environments, the typical frequency point is in the range of 0.3MHz to 250MHz; when the target area includes a quiet rural environment sub-region, the typical frequency point is also within the preset applicable frequency range of curve D.

[0064] While ensuring the applicable frequency range is met, for each sub-region, select the corresponding frequency range based on the type of anthropogenic noise environment in that sub-region. c and d and typical frequency points f Substituting into the above formula, we obtain the anthropogenic noise figure for this sub-region. F am .

[0065] Galaxy noise is a type of natural noise and is not considered as an anthropogenic noise figure or power. When it is necessary to generate comprehensive noise data, galactic noise can be included as part of the natural noise data, acquired separately according to the natural noise model, and then correlated and organized with anthropogenic noise data according to the geographical location of each sub-region.

[0066] For each sub-region, select the corresponding [specific type of noise environment] based on the type of anthropogenic noise environment in that sub-region. c and d and typical frequency points f Substituting into the above formula, we obtain the anthropogenic noise figure for this sub-region. F am .

[0067] When using a discrete frequency point correspondence table or noise figure curve as a preset correspondence, if a typical frequency point is located between two adjacent preset frequency points, linear interpolation or logarithmic interpolation can be used to determine the man-made noise figure corresponding to that typical frequency point.

[0068] After determining the anthropogenic noise figure for each sub-region, calculate the anthropogenic noise power for each sub-region using the following formula: P n = F am +10log 10 ( k · T 0· B ) in, P nThe median of the available external man-made noise power at the input of the equivalent lossless receiving antenna, expressed in dBW. F am This represents the anthropogenic noise figure for the sub-region, in dB. k Boltzmann's constant, in J / K; T 0 represents the reference temperature, in Kelvin (K). B This represents the receiver's equivalent noise bandwidth, measured in Hz.

[0069] In the above formula, k · T 0· B The dimension is power, and its unit is W; 10log 10 ( k · T 0· B ) indicates that it will be expressed in units of W. k · T 0· B Logarithmically represented relative to 1W, i.e., 10log 10 [( k · T 0· B ) / 1W]. Therefore, the formula P n = F am +10log 10 ( k · T 0· B () is a simplified expression when dBW is used as the unit of man-made noise power.

[0070] In some embodiments, the Boltzmann constant k can be 1.380649 × 10⁻⁶. - ²³J / K, reference temperature T 0 can be taken as 290K. Receiver equivalent noise bandwidth. B The preset value is determined based on the receiver parameters of the simulated communication system.

[0071] When the man-made noise spatial distribution dataset uses dBm to store the man-made noise power, the dBW value obtained according to the above formula can be converted into the corresponding dBm value by adding 30.

[0072] The above calculations are performed on each sub-region within the target area to obtain the anthropogenic noise power of each sub-region. Since the land cover type or the proportion of each land cover type may be different in each sub-region, the anthropogenic noise environment type and anthropogenic noise coefficient corresponding to each sub-region may also be different, thus forming a spatial distribution of anthropogenic noise power that varies with geographical location.

[0073] In some embodiments, the calculation results of each sub-region are organized into a spatial distribution dataset of man-made noise, and this spatial distribution dataset of man-made noise is used as the man-made noise data of the target region.

[0074] In the spatial distribution dataset of anthropogenic noise, the geographic coordinates, land cover type, anthropogenic noise environment type, anthropogenic noise power, and power unit for each sub-region are stored. The power unit is either dBW or dBm. For a sub-region containing multiple land cover types, the representative land cover type of the sub-region can be stored, or the land cover type and its proportion within the sub-region can be stored. When the power unit is dBW, the anthropogenic noise power calculated according to the above formula is stored; when the power unit is dBm, the dBW value calculated according to the above formula is increased by 30 before storage.

[0075] The spatial distribution dataset of anthropogenic noise can be in GeoTIFF or NetCDF format. This dataset can be used for subsequent wireless communication system simulations to obtain the anthropogenic noise power corresponding to different geographical locations within the target area.

[0076] In some embodiments, the method further includes acquiring natural noise data of the target area and associating the natural noise data with the aforementioned anthropogenic noise data according to the geographical location of each sub-region to obtain comprehensive noise data of the target area.

[0077] Specifically, both natural noise data and anthropogenic noise data are organized according to sub-regions of the target area. For the same sub-region, the geographic coordinates, natural noise data, and anthropogenic noise data of that sub-region are stored in the integrated noise data. Thus, the natural noise and anthropogenic noise conditions corresponding to each sub-region within the target area can be obtained from the same dataset.

[0078] The comprehensive noise data referred to in this embodiment refers to a collection of natural noise data and man-made noise data, and is not limited to simply adding the natural noise power and man-made noise power numerically. If subsequent communication system simulations require calculation of total noise power or signal-to-noise ratio, the comprehensive noise data can be further processed according to the specific simulation model; however, such further processing is not the focus of this application.

[0079] Example 2 like Figure 2 As shown in the embodiments of this specification, an anthropogenic noise calculation device based on land cover data is also proposed, comprising: Module 200 is used to acquire land cover data for the target area; The partitioning module 202 is used to divide the target region into multiple sub-regions; The determining module 204 is used to determine the anthropogenic noise coefficient of each sub-region based on the land cover type corresponding to each sub-region; The calculation module 206 is used to calculate the anthropogenic noise power of each sub-region based on the anthropogenic noise coefficient of each sub-region, and obtain the anthropogenic noise data of the target region.

[0080] The specific implementation process of the anthropogenic noise calculation device based on land cover data proposed in this embodiment is consistent with the process of the anthropogenic noise calculation method based on land cover data proposed in Embodiment 1, and will not be repeated here.

[0081] In summary, this application characterizes the spatial distribution of human activities within a target area using land cover data, determines the anthropogenic noise coefficient and calculates the anthropogenic noise power for each sub-region, and thus obtains the spatial distribution data of anthropogenic noise in the target area. This method eliminates the need to establish precise electromagnetic models for each building or anthropogenic noise source, thereby reducing the computational load of anthropogenic noise in large-scale scenarios while preserving spatial distribution differences.

[0082] The method and apparatus for calculating anthropogenic noise based on land cover data provided in this application have the following technical advantages: By dividing the target area into multiple sub-regions, determining the anthropogenic noise coefficient based on the land cover type of each sub-region, and calculating the anthropogenic noise power of each sub-region separately, the spatial distribution of anthropogenic noise power as a function of geographical location can be obtained, reflecting the differences in anthropogenic noise at different locations within the target area. This approach eliminates the need to investigate each anthropogenic noise source individually or to build electromagnetic models of buildings, electronic equipment, and power facilities. It reduces the difficulty of data acquisition, model building workload, and computational burden in large-scale scenarios, providing fundamental data for regional noise simulation of wireless communication systems.

[0083] Furthermore, by classifying and processing image map data or reading land cover data corresponding to the target area from a preset land cover dataset, it is possible to adapt to different land cover data sources and provide standardized data input for the calculation of human-caused noise in each sub-region.

[0084] Furthermore, by first determining the anthropogenic noise environment type of each sub-region based on the land cover type, and then determining the anthropogenic noise coefficient based on the anthropogenic noise environment type, land cover information can be converted into parameters required for anthropogenic noise power calculation, thereby improving the consistency of anthropogenic noise coefficient determination for each sub-region.

[0085] Furthermore, by pre-setting the correspondence between land cover type and anthropogenic noise environment type, the anthropogenic noise environment type of each sub-region can be determined according to a unified classification rule, thereby improving the classification efficiency and consistency of classification results among multiple sub-regions within the target area.

[0086] Furthermore, by statistically analyzing the proportion of each land cover type within a sub-region, we can comprehensively consider the composition of multiple land cover types within the same sub-region, reducing the bias caused by determining the type of anthropogenic noise environment based solely on a single land cover type.

[0087] Furthermore, by using multi-level thresholds for building proportion and the sum of building proportion and cultivated land proportion, it is possible to distinguish between high-density building areas, low-density building areas, agricultural activity areas, and low-human activity areas, thus providing clear and interconnected standards for determining the type of anthropogenic noise environment.

[0088] Furthermore, by combining the artificial noise figure with the reference temperature and the receiver's equivalent noise bandwidth, the artificial noise figure characterizing the environmental noise level can be converted into artificial noise power under the corresponding receiving conditions, thereby obtaining power data that can be used for subsequent communication simulations.

[0089] Furthermore, by storing the geographic coordinates, land cover type, anthropogenic noise environment type, and anthropogenic noise power of each sub-region, spatial distribution data of anthropogenic noise with spatial indexing can be formed, making it convenient to query and retrieve the corresponding anthropogenic noise power according to geographic location.

[0090] Furthermore, by associating and organizing natural noise data with man-made noise data according to the geographical location of each sub-region, it is possible to provide natural noise information and man-made noise information corresponding to each spatial location in the same dataset, providing a data foundation for subsequent background noise calculation or communication performance evaluation based on specific simulation models.

[0091] The foregoing description and accompanying drawings fully illustrate embodiments of this specification to enable those skilled in the art to practice them. Other embodiments may include structural and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included or substituted for parts and features of other embodiments. The embodiments of this specification are not limited to the structures described above and shown in the accompanying drawings, and various modifications and changes may be made without departing from their scope. The scope of this specification is limited only by the appended claims.

Claims

1. A method for calculating anthropogenic noise based on land cover data, characterized in that, include: Obtain land cover data for the target area; The target region is divided into multiple sub-regions; The anthropogenic noise coefficient of each sub-region is determined based on the land cover type corresponding to each sub-region; Based on the anthropogenic noise coefficient of each sub-region, the anthropogenic noise power of each sub-region is calculated to obtain the anthropogenic noise data of the target region.

2. The method according to claim 1, characterized in that, The acquisition of land cover data for the target area includes: The image map data of the target area is classified and processed to obtain the land cover data; Alternatively, land cover data for the target area can be obtained from a preset land cover dataset; The land cover data includes the land cover types corresponding to each location within the target area; the land cover types include water bodies, woodlands, grasslands, submerged vegetation, cultivated land, shrubs, buildings, bare land, snow / ice, and clouds.

3. The method according to claim 1, characterized in that, Based on the land cover type corresponding to each sub-region, the anthropogenic noise coefficient of each sub-region is determined, including: Based on the land cover type corresponding to each sub-region, determine the anthropogenic noise environment type of each sub-region; The anthropogenic noise coefficient of each sub-region is determined based on the anthropogenic noise environment type of each sub-region; wherein the anthropogenic noise environment type includes urban environment, residential environment, rural environment and quiet rural environment.

4. The method according to claim 3, characterized in that, Based on the land cover type corresponding to each sub-region, determine the anthropogenic noise environment type of each sub-region, including: Obtain the mapping relationship between land cover type and anthropogenic noise environment type; Based on the mapping relationship, the anthropogenic noise environment type of each sub-region is determined.

5. The method according to claim 3, characterized in that, Based on the land cover type corresponding to each sub-region, determine the anthropogenic noise environment type of each sub-region, including: The percentage of each land cover type within each sub-region is statistically analyzed. The anthropogenic noise environment type of each sub-region is determined based on the proportion of each land cover type within the sub-region.

6. The method according to claim 5, characterized in that, Based on the proportion of each land cover type within the sub-region, the anthropogenic noise environment type of each sub-region is determined, including: If buildings account for more than 50% of the total area within the sub-region, the anthropogenic noise environment type of the sub-region is defined as an urban environment. If the proportion of buildings in the sub-area is less than 50% but more than 10%, the anthropogenic noise environment type of the sub-area is defined as a residential environment. If the proportion of buildings in the sub-region does not exceed 10%, and the sum of the proportion of buildings and the proportion of cultivated land exceeds 0.5%, the anthropogenic noise environment type of the sub-region is determined to be a rural environment. In other cases, the anthropogenic noise environment type for this sub-region is defined as a quiet rural environment.

7. The method according to claim 1, characterized in that, Based on the anthropogenic noise figure of each sub-region, the anthropogenic noise power of each sub-region is calculated, including: According to the formula P n = F am +10log 10 ( k · T 0· B ), calculate the anthropogenic noise power of each of the sub-regions. P n ; in, F am This represents the anthropogenic noise figure for this sub-region. k Boltzmann's constant, T 0 is the reference temperature. B This is the receiver's equivalent noise bandwidth.

8. The method according to claim 3, characterized in that, The process of obtaining the anthropogenic noise data for the target region includes: The calculation results of each sub-region are organized into a spatial distribution dataset of artificial noise data for the target region. The man-made noise spatial distribution dataset centrally stores the geographic coordinates, land cover type, man-made noise environment type, and man-made noise power of each sub-region.

9. The method according to claim 1, characterized in that, Also includes: Acquire the natural noise data of the target area; Based on the geographical location of each sub-region, the natural noise data and the anthropogenic noise data are correlated and organized to obtain the comprehensive noise data of the target region.

10. A device for calculating anthropogenic noise based on land cover data, characterized in that, include: The acquisition module is used to acquire land cover data for the target area; A partitioning module is used to divide the target region into multiple sub-regions; The determination module is used to determine the anthropogenic noise coefficient of each sub-region based on the land cover type corresponding to each sub-region; The calculation module is used to calculate the anthropogenic noise power of each sub-region based on the anthropogenic noise coefficient of each sub-region, and obtain the anthropogenic noise data of the target region.

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