A method and system for compiling low-altitude safety three-dimensional stereoscopic maps of petrochemical plant areas

Abstract

This invention relates to low-altitude security in petrochemical plant areas, specifically to a method and system for creating a three-dimensional safety map of petrochemical plant areas. The method involves multi-level grid subdivision of the petrochemical plant area based on GeoSOT, matching grid accuracy according to target size, and generating a unique BeiDou grid code for each grid cell. Multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed. The grid status is dynamically updated, partially updated, and version-managed to achieve real-time updates and historical backtracking of the airspace situation. Target threat assessment is conducted, and countermeasure resources are scheduled for rapid countermeasures against threatening targets. A three-dimensional map visualization rendering is performed, intuitively presenting the airspace situation, target trajectories, and countermeasure equipment status. This invention effectively overcomes the shortcomings of two-dimensional control, such as airspace blind spots, insufficient positioning accuracy in complex environments, inability to achieve three-dimensional fusion of multi-source data, and low efficiency in dynamic control response.

Description

Technical Field

[0001] This invention relates to low-altitude security in petrochemical plant areas, specifically to a method and system for creating three-dimensional safety maps of low-altitude areas in petrochemical plant areas. Background Technology

[0002] The existing low-altitude security technology in petrochemical plant areas mainly has the following problems: 1) Two-dimensional control has airspace blind spots. Existing technologies primarily rely on two-dimensional planar monitoring, which cannot achieve layered identification and control of "low, slow, and small" targets at different altitudes. The height requirements of various areas within a petrochemical plant, such as refining units, large storage tank areas, wharves, and pipeline corridors, vary. Some areas require centimeter-level high control precision. For example, the elevation difference between the top and bottom of a large storage tank can be more than 30 meters. Airspace points with the same planar coordinates but different elevations have completely different safety attributes. Existing two-dimensional systems cannot express this difference in the height dimension, resulting in "vertical blind spots" in airspace control. The root cause is the lack of support for three-dimensional airspace modeling that integrates the height dimension. Traditional geographic information systems mainly use two-dimensional planar representation, making it difficult to achieve fine segmentation of three-dimensional airspace. 2) Insufficient positioning accuracy in complex environments Petrochemical plant areas are generally characterized by high salt spray and strong electromagnetic interference environments. In addition, the "canyon effect" formed by large storage tanks and pipe corridors leads to severe signal refraction and multipath interference of traditional radar and radio detection equipment. The high positioning error cannot meet the needs of accurate identification and countermeasures of drones in flammable and explosive scenarios. The root cause is the lack of a signal attenuation compensation mechanism for the complex environment of petrochemical plant areas, and the failure to effectively suppress the spatial calculation error caused by multipath interference. 3) Multi-source data cannot be fully integrated. Data from radar, optoelectronic, and spectrum sensing devices are mostly collected in a planar dimension and lack a unified three-dimensional spatial coding standard. The data fusion of existing systems usually adopts a simple mapping method of "correlation based on geodetic coordinates". Data from different coordinate systems are difficult to achieve seamless integration and visualization in three-dimensional space, which makes it impossible to achieve a "one-map overview" of the airspace situation during command and decision-making. The root cause is that there is no unified spatial reference framework and the data from each sensing device lacks a globally unique grid location identifier, making it impossible to achieve feature-level deep fusion. 4) Low efficiency in dynamic control and response. Existing countermeasure systems require manual configuration of control rules layer by layer to deal with multiple drones that attempt to penetrate defenses at various altitudes. This results in a delayed response. In flammable and explosive environments such as petrochemical plants, the timeliness of response directly affects the safety baseline. The total response time from detection to countermeasure triggering can be as long as tens of seconds, which is difficult to meet actual needs. The root cause is the lack of an automated response mechanism based on a unified grid coding system and the absence of a linkage between grid status updates and countermeasure equipment. Summary of the Invention

[0003] (a) Technical problems to be solved To address the aforementioned shortcomings of existing technologies, this invention provides a method and system for creating low-altitude safety three-dimensional stereoscopic maps of petrochemical plant areas. This method effectively overcomes the deficiencies of existing technologies, such as airspace blind spots in two-dimensional control, insufficient positioning accuracy in complex environments, inability to fuse multi-source data in three dimensions, and low efficiency in dynamic control response.

[0004] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: A method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area includes the following steps: S1. Perform multi-level grid subdivision of the petrochemical plant area based on GeoSOT, match the grid accuracy according to the target size, and generate a unique BeiDou grid code for each grid cell. S2. Unify multi-source data to the BeiDou grid code spatiotemporal reference, establish an error compensation model based on environmental perception to suppress multipath interference, and perform multi-source data fusion, including: Based on the BeiDou grid code spatiotemporal reference, multi-source data spatiotemporal alignment is performed. Combined with the environmental perception error compensation model, multipath interference in the petrochemical plant area is eliminated. Finally, a weighted fusion algorithm based on the measurement error variance is used to achieve high-precision and high-reliability three-dimensional positioning of the target. S3. Dynamically update, partially update, and manage the version of the grid status to achieve real-time updates and historical backtracking of the airspace situation; S4. Conduct target threat assessment and allocate countermeasure resources to quickly counter the threatened targets; S5. Perform 3D visualization rendering to intuitively present the airspace situation, target trajectory, and countermeasure equipment status.

[0005] Preferably, in S1, the petrochemical plant area is subjected to multi-level mesh generation based on GeoSOT, and the mesh accuracy is matched according to the target size, including: For key areas of petrochemical plants, including refining units, large storage tank areas, wharves, and pipeline corridors, a three-dimensional mesh system based on GeoSOT earth partitioning theory was established. 1) Based on the target's minimum feature size Dobject Determine the grid level L: ; Among them, 40075.02×10 3 m is the circumference of the Earth's equator. For critical equipment, D object For areas ≤0.2m, the corresponding grid level is L=9; for large areas, the corresponding grid level is L=8. Indicates rounding up; 2) Accuracy of the Lth level grid for: ; Where R is the Earth's radius; 3) The geometric accuracy of the 3D model must meet the following requirements: ; in, Geometric errors in 3D modeling.

[0006] Preferably, in S1, a unique BeiDou grid code is generated for each grid cell, including: The BeiDou grid code, representing the grid cell using a binary string: ; Where L is the grid level of the grid cell. When in binary mode, it corresponds to the subgrid direction encoding of a planar quadtree / 3D octree; This is a quaternary extended mode, corresponding to the four subquadrant codes of a planar quadtree, b i For the i-th code element, the three-dimensional grid adds the height dimension encoding to the two-dimensional latitude and longitude to form a three-dimensional grid code.

[0007] Preferably, in S2, multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed, including: S21. Unify multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data, into the BeiDou grid code spatiotemporal reference: If the i-th sensor observes the position of the target in the sensor coordinate system at time t, the observed value is x. i (t), then through the coordinate transformation matrix T i Position observations X converted to geocentric coordinates i (t): ; Time alignment uses linear interpolation to align all location observations X. i (t) Aligned to a uniform system timestamp T sys : ; Among them, X i (T sys ) represents the system timestamp T of the i-th sensor. sys The observed position of the target in the geocentric coordinate system, X i (t k ), X i (t k+1 Let ) represent the time of the i-th sensor at time t. k t k+1 The observed position of the target in the geocentric coordinate system was obtained; S22. To address the multipath interference caused by the "canyon effect" in petrochemical plant areas, establish an error compensation model based on environmental perception: In the error compensation model, the location observation X i (T sys The effect of multipath propagation can be expressed as: ; Among them, X i (T sys ) ture For the i-th sensor at system timestamp T sys The true position of the target in the geocentric coordinate system was observed, e mp (p i v) represents the position p of the i-th sensor. i The multipath error term related to the target velocity v For random noise; By pre-collecting a multipath feature database of the factory area environment, an error lookup table is established to analyze the location observation value X. i (T sys Perform error compensation: ; Among them, X i '(T sys ) represents the system timestamp T of the i-th sensor. sys The position of the target in the geocentric coordinate system was observed and compensated for. For the position p of the i-th sensor i The multipath error estimate related to the target velocity v is obtained by using a pre-established error lookup table, based on the position p of the i-th sensor. i The error prediction value obtained by querying the target velocity v; S23. If the same target is detected by multiple sensors, a weighted fusion algorithm based on the variance of measurement error is used for position fusion, and the location is determined at the system timestamp T. sys Lower fusion position estimate for: ; in, Let be the weighting coefficient of the i-th sensor. , Let be the measurement error variance of the i-th sensor, and n be the number of sensors participating in the fusion. Total error after fusion for: .

[0008] Preferably, S3 performs dynamic updates, partial updates, and version management of the grid status to achieve real-time updates and historical backtracking of the airspace situation, including: 1) Dynamically update trigger conditions, specifically including: New targets entering the airspace, changes in target location, targets leaving the airspace, establishment / removal of temporary control areas, and changes in environmental parameters; 2) Partial update mechanism: A local update strategy based on grid coding is adopted, updating only the grid cell that triggers the dynamic update and its neighboring grids to form a spatial situation map: The set of neighboring grids within the airspace is: ; Where N(g) is the set of grid cells G that triggers the dynamic update. changed The set of neighboring grids of a grid cell g, dist(g',g) represents the calculation of the spatial distance between two grid cells g' and g, and r is the neighborhood radius; 3) Version Management: Set a version number for each updated airspace situation map, supporting historical version rollback. Version differences can be represented as follows: ; in, Let k be the set of version differences in the k-th update. , These are the sets of grid cells that trigger dynamic updates for the k-th and (k-1)-th updates, respectively. \ represents the set difference operator, used to calculate the set difference in... It exists in, but The set of all grid cells that do not exist in the array.

[0009] Preferably, in S4, target threat assessment is performed and countermeasure resources are allocated to quickly counter the threat target, including: S41. For detected non-cooperative targets, a weighted model is used to calculate their threat probability P. threat : ; Among them, A trajLet v' be the trajectory anomaly degree, and v' be the flight speed of the non-cooperative target. max Where h is the maximum permissible flight speed in this airspace, and h is the flight altitude of the non-cooperative target. safe R is the lower limit of the safe altitude for this airspace. signal For signal compliance, , , , All are weighting coefficients, and ; S42, Preset warning trigger threshold and countermeasure trigger threshold Implement a tiered response mechanism for non-cooperative targets based on threat probability: when When non-cooperative targets are determined to be low-threat targets, an electronic fence alarm is sent and a voice warning is issued to drive them away. when When a non-cooperative target is identified as a medium threat target, targeted electromagnetic interference is initiated, communication is cut off, and location is determined. when If a non-cooperative target is identified as a high-threat target, a combined signal deception and physical capture response will be initiated. S43. Based on grid coding, spatial matching between medium-threat targets / high-threat targets and countermeasures devices is achieved, and the countermeasures device that is closest to the target's grid cell and is in an idle state is selected for processing.

[0010] Preferably, in S5, a three-dimensional visualization rendering is performed to intuitively present the airspace situation, target trajectory, and countermeasure equipment status, including: A hierarchical coloring strategy is used to achieve the visualization rendering of 3D stereoscopic images, specifically including: 1) Grid boundary lines: Semi-transparent thin lines are used to show the grid hierarchy of the grid cells; 2) Airspace status: Colored according to the dynamic status code of the grid cell, no-fly zone is red, altitude-restricted zone is yellow, buffer zone is orange, and suitable flight zone is green; 3) Target trajectory: Historical trajectory points are displayed using a trailing effect, with the size and color of the points indicating their time sequence; 4) Countermeasures equipment: Use icons to indicate the location, type, and working status of the equipment.

[0011] A system for creating a low-altitude safety 3D model of a petrochemical plant area includes a data acquisition layer, a mesh partitioning layer, a spatiotemporal modeling layer, a data fusion layer, a dynamic update layer, a visualization and linkage layer, and a result output layer. The data acquisition layer collects multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data. The petrochemical plant area is divided into multiple levels of grids based on GeoSOT. The grid accuracy is matched according to the target size, and a unique BeiDou grid code is generated for each grid cell. The spatiotemporal modeling layer performs 3D modeling in a 3D mesh system for key areas of the petrochemical plant, including the refining unit area, large storage tank area, wharf, and pipeline corridor. The data fusion layer unifies multi-source data to the BeiDou grid code spatiotemporal reference, establishes an error compensation model based on environmental perception to suppress multipath interference, and performs multi-source data fusion. The dynamic update layer dynamically updates, partially updates, and manages the version of the grid status, generates an airspace situation map, and enables real-time updates and historical backtracking of the airspace situation. The visualization and linkage layer performs target threat assessment and dispatches countermeasure resources to quickly counter threat targets, and performs 3D stereoscopic visualization rendering to intuitively present the airspace situation, target trajectory and countermeasure equipment status; The output layer outputs airspace situation maps, 3D stereoscopic maps, threat warning information, and countermeasures results, and supports historical retrospective analysis and annotation of airspace situation maps.

[0012] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area.

[0013] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps of the above-described method for compiling a low-altitude safety three-dimensional stereoscopic image of a petrochemical plant area.

[0014] (III) Beneficial Effects Compared with the prior art, the method and system for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area provided by the present invention has the following beneficial effects: 1) Unify spatiotemporal benchmarks to achieve globally unique identification. Based on GeoSOT Earth Partition Theory and GB / T 39409-2020 national standard, this invention establishes a unified spatiotemporal reference framework for the low-altitude airspace of petrochemical plant areas. The Beidou grid code of this invention is globally unique and can realize data sharing and linkage across plant areas, cities, and departments, laying the foundation for multi-source data fusion. 2) Multi-scale grid representation, balancing efficiency and accuracy. This invention proposes a grid level selection criterion based on target feature size. Large areas use a low-resolution grid level (level 8), while key equipment uses a high-resolution grid level (level 9). This criterion can be dynamically adjusted according to control requirements, balancing computational efficiency and positioning accuracy. 3) Weighted fusion and multipath suppression significantly improve positioning accuracy. This invention uses the BeiDou grid code spatiotemporal reference to perform spatiotemporal alignment of multi-source data, combines an environmental perception error compensation model to eliminate multipath interference in the petrochemical plant area, and finally adopts a weighted fusion algorithm based on the measurement error variance to achieve high-precision and high-reliability three-dimensional positioning of the target, controlling the fused positioning error to less than 5m, effectively improving positioning accuracy. 4) The grid status is dynamically updated, achieving a response time within seconds. This invention proposes an event-triggered dynamic update mechanism for grid status, with an update response time of less than 2 seconds. At the same time, it establishes a fully automated closed loop for the countermeasure linkage process, with an overall response time of less than 5 seconds from detection to countermeasure triggering, which greatly improves the response speed. 5) Partial updates and version management, supporting post-event review. This invention adopts a neighborhood-based local update strategy to avoid the computational overhead of global redrawing, while establishing a version management mechanism to support historical backtracking and change analysis. 6) Multi-target concurrent processing, adapting to complex threat scenarios This invention is based on a countermeasure resource scheduling model, which can handle more than 100 threat targets at the same time, and is suitable for complex threat scenarios involving multi-squadron, multi-altitude coordinated penetration. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Figure 1 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] The following section, with specific examples, describes the detailed process and technical effects of the method for compiling low-altitude safety three-dimensional stereoscopic maps of petrochemical plant areas provided by this invention.

[0019] S1. Perform multi-level grid subdivision of the petrochemical plant area based on GeoSOT, match the grid accuracy according to the target size, and generate a unique BeiDou grid code for each grid cell.

[0020] Specifically, the petrochemical plant area is subjected to multi-level mesh generation based on GeoSOT, and the mesh accuracy is matched according to the target size, including: For key areas of petrochemical plants, including refining units, large storage tank areas, wharves, and pipeline corridors, a three-dimensional mesh system based on GeoSOT earth partitioning theory was established. 1) Based on the target's minimum feature size D object (Unit: m) Determine the grid level L: ; Among them, 40075.02×10 3 m is the circumference of the Earth's equator. For critical equipment (such as tank valves, pipe rack connection points, etc.), D object For areas ≤0.2m, the corresponding grid level is L=9; for large areas (such as an entire tank farm), the corresponding grid level is L=8. Indicates rounding up; 2) Accuracy of the Lth level grid for: ; Where R is the Earth's radius; 3) The geometric accuracy of the 3D modeling (including 3D modeling of key areas such as the refining unit area, large storage tank area, wharf, and pipeline corridor in the petrochemical plant area) must meet the following requirements: ; in, Geometric errors in 3D modeling.

[0021] Specifically, a unique BeiDou grid code is generated for each grid cell, including: The BeiDou grid code, representing the grid cell using a binary string: ; Where L is the grid level of the grid cell. When in binary mode, it corresponds to the subgrid direction encoding of a planar quadtree / 3D octree; This is a quaternary extended mode, corresponding to the four subquadrant codes of a planar quadtree, b i For the i-th code element, the three-dimensional grid adds the height dimension encoding to the two-dimensional latitude and longitude to form a three-dimensional grid code.

[0022] S2. Unify multi-source data to the BeiDou grid code spatiotemporal reference, establish an error compensation model based on environmental perception to suppress multipath interference, and perform multi-source data fusion, including: Multi-source data is spatiotemporally aligned based on the BeiDou grid code spatiotemporal reference. Multipath interference within the petrochemical plant area is eliminated by combining an environmental perception error compensation model. Finally, a weighted fusion algorithm based on measurement error variance is used for high-precision and high-reliability three-dimensional positioning of the target.

[0023] Specifically, multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed, including: S21. Unify multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data, into the BeiDou grid code spatiotemporal reference: If the i-th sensor observes the position of the target in the sensor coordinate system at time t, the observed value is x. i (t), then through the coordinate transformation matrix T i Position observations X converted to geocentric coordinates i (t): ; Time alignment uses linear interpolation to align all location observations X. i (t) Aligned to a uniform system timestamp T sys : ; Among them, X i (T sys ) represents the system timestamp T of the i-th sensor. sys The observed position of the target in the geocentric coordinate system, X i (t k ), X i (t k+1 Let ) represent the time of the i-th sensor at time t. k t k+1 The observed position of the target in the geocentric coordinate system was obtained; S22. To address the multipath interference caused by the "canyon effect" in petrochemical plant areas, establish an error compensation model based on environmental perception: In the error compensation model, the location observation X i (T sys The effect of multipath propagation can be expressed as: ; Among them, X i (T sys ) ture For the i-th sensor at system timestamp T sysThe true position of the target in the geocentric coordinate system was observed, e mp (p i v) represents the position p of the i-th sensor. i The multipath error term related to the target velocity v For random noise; By pre-collecting a multipath feature database of the factory area environment, an error lookup table is established to analyze the location observation value X. i (T sys Perform error compensation: ; Among them, X i '(T sys ) represents the system timestamp T of the i-th sensor. sys The position of the target in the geocentric coordinate system was observed and compensated for. For the position p of the i-th sensor i The multipath error estimate related to the target velocity v is obtained by using a pre-established error lookup table, based on the position p of the i-th sensor. i The error prediction value obtained by querying the target velocity v; S23. If the same target is detected by multiple sensors, a weighted fusion algorithm based on the variance of measurement errors (this algorithm can effectively suppress single sensor errors and improve positioning accuracy) is used for position fusion, and the location is fused at the system timestamp T. sys Lower fusion position estimate for: ; in, Let be the weighting coefficient of the i-th sensor. , Let be the measurement error variance of the i-th sensor, and n be the number of sensors participating in the fusion. Total error after fusion for: .

[0024] S3. Dynamically update, partially update, and manage the version of the grid status to achieve real-time updates and historical backtracking of the airspace situation, including: 1) Dynamically update trigger conditions, specifically including: New target enters airspace (detection), target position changes (tracking), target leaves airspace (disappears), temporary control area is established / removed, and environmental parameters change (such as wind speed, visibility, etc.). 2) Partial update mechanism: A local update strategy based on grid coding is adopted, updating only the grid cell that triggers the dynamic update and its neighboring grids to form a spatial situation map: The set of neighboring grids within the airspace is: ; Where N(g) is the set of grid cells G that triggers the dynamic update. changed The set of neighboring grids of a grid cell g, dist(g',g) represents the calculation of the spatial distance between two grid cells g' and g, and r is the neighborhood radius; 3) Version Management: Set a version number for each updated airspace situation map, supporting historical version rollback. Version differences can be represented as follows: ; in, Let k be the set of version differences in the k-th update. , These are the sets of grid cells that trigger dynamic updates for the k-th and (k-1)-th updates, respectively. \ represents the set difference operator, used to calculate the set difference in... It exists in, but The set of all grid cells that do not exist in the array.

[0025] S4. Conduct target threat assessment and allocate countermeasure resources to rapidly counter the threatened targets, including: S41. For detected non-cooperative targets, a weighted model is used to calculate their threat probability P. threat : ; Among them, A traj Let v' be the trajectory anomaly degree, and v' be the flight speed of the non-cooperative target. max Where h is the maximum permissible flight speed in this airspace, and h is the flight altitude of the non-cooperative target. safe R is the lower limit of the safe altitude for this airspace. signal For signal compliance, , , , All are weighting coefficients, and ; S42, Preset warning trigger threshold and countermeasure trigger threshold Implement a tiered response mechanism for non-cooperative targets based on threat probability: when When non-cooperative targets are determined to be low-threat targets, an electronic fence alarm is sent and a voice warning is issued to drive them away. when When a non-cooperative target is identified as a medium threat target, targeted electromagnetic interference is initiated, communication is cut off, and location is determined. when If a non-cooperative target is identified as a high-threat target, a combined signal deception and physical capture response will be initiated. S43. Based on grid coding, spatial matching between medium-threat targets / high-threat targets and countermeasures devices is achieved, and the countermeasures device that is closest to the target's grid cell and is in an idle state is selected for processing.

[0026] S5. Perform 3D visualization rendering to intuitively present the airspace situation, target trajectory, and countermeasure equipment status, including: A hierarchical coloring strategy is used to achieve the visualization rendering of 3D stereoscopic images, specifically including: 1) Grid boundary lines: Semi-transparent thin lines are used to show the grid hierarchy of the grid cells; 2) Airspace status: Colored according to the dynamic status code of the grid cell, no-fly zone is red, altitude-restricted zone is yellow, buffer zone is orange, and suitable flight zone is green; 3) Target trajectory: Historical trajectory points are displayed using a trailing effect, with the size and color of the points indicating their time sequence; 4) Countermeasures equipment: Use icons to indicate the location, type, and working status of the equipment.

[0027] Based on the aforementioned method for compiling three-dimensional safety maps of petrochemical plant areas, this invention also discloses a system for compiling three-dimensional safety maps of petrochemical plant areas, such as... Figure 1 As shown, it includes a data acquisition layer, a mesh partitioning layer, a spatiotemporal modeling layer, a data fusion layer, a dynamic update layer, a visualization and linkage layer, and a result output layer; The data acquisition layer collects multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data. The petrochemical plant area is divided into multiple levels of grids based on GeoSOT. The grid accuracy is matched according to the target size, and a unique BeiDou grid code is generated for each grid cell. The spatiotemporal modeling layer performs 3D modeling in a 3D mesh system for key areas of the petrochemical plant, including the refining unit area, large storage tank area, wharf, and pipeline corridor. The data fusion layer unifies multi-source data to the BeiDou grid code spatiotemporal reference, establishes an error compensation model based on environmental perception to suppress multipath interference, and performs multi-source data fusion. The dynamic update layer dynamically updates, partially updates, and manages the version of the grid status, generates an airspace situation map, and enables real-time updates and historical backtracking of the airspace situation. The visualization and linkage layer performs target threat assessment and dispatches countermeasure resources to quickly counter threat targets, and performs 3D stereoscopic visualization rendering to intuitively present the airspace situation, target trajectory and countermeasure equipment status; The output layer outputs airspace situation maps, 3D stereoscopic maps, threat warning information, and countermeasures results, and supports historical retrospective analysis and annotation of airspace situation maps.

[0028] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for compiling a low-altitude safety three-dimensional image of a petrochemical plant area.

[0029] A computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the various steps of the above-described method for compiling a low-altitude safety three-dimensional stereoscopic image of a petrochemical plant area.

[0030] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for compiling a three-dimensional safety map of a petrochemical plant area, characterized in that: Includes the following steps: S1. Perform multi-level grid subdivision of the petrochemical plant area based on GeoSOT, match the grid accuracy according to the target size, and generate a unique BeiDou grid code for each grid cell. S2. Unify multi-source data to the BeiDou grid code spatiotemporal reference, establish an error compensation model based on environmental perception to suppress multipath interference, and perform multi-source data fusion, including: Based on the BeiDou grid code spatiotemporal reference, multi-source data spatiotemporal alignment is performed. Combined with the environmental perception error compensation model, multipath interference in the petrochemical plant area is eliminated. Finally, a weighted fusion algorithm based on the measurement error variance is used to achieve high-precision and high-reliability three-dimensional positioning of the target. S3. Dynamically update, partially update, and manage the version of the grid status to achieve real-time updates and historical backtracking of the airspace situation; S4. Conduct target threat assessment and allocate countermeasure resources to quickly counter the threatened targets; S5. Perform 3D visualization rendering to intuitively present the airspace situation, target trajectory, and countermeasure equipment status.

2. The method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area according to claim 1, characterized in that: In S1, a multi-level mesh based on GeoSOT is used to generate the petrochemical plant area, and the mesh accuracy is matched according to the target size, including: For key areas of petrochemical plants, including refining units, large storage tank areas, wharves, and pipeline corridors, a three-dimensional mesh system based on GeoSOT earth partitioning theory was established. 1) Based on the target's minimum feature size D object Determine the grid level L: ； Among them, 40075.02×10 3 m is the circumference of the Earth's equator. For critical equipment, D object For areas ≤0.2m, the corresponding grid level is L=9; for large areas, the corresponding grid level is L=8. Indicates rounding up; 2) Accuracy of the Lth level grid for: ； Where R is the Earth's radius; 3) The geometric accuracy of the 3D model must meet the following requirements: ； in, Geometric errors in 3D modeling.

3. The method for compiling a three-dimensional safety map of a petrochemical plant area according to claim 2, characterized in that: In S1, a unique BeiDou grid code is generated for each grid cell, including: The BeiDou grid code, representing the grid cell using a binary string: ； Where L is the grid level of the grid cell. When in binary mode, it corresponds to the subgrid direction encoding of a planar quadtree / 3D octree; This is a quaternary extended mode, corresponding to the four subquadrant codes of a planar quadtree, b i For the i-th code element, the three-dimensional grid adds the height dimension encoding to the two-dimensional latitude and longitude to form a three-dimensional grid code.

4. The method for compiling a three-dimensional safety map of a petrochemical plant area according to claim 1, characterized in that: In S2, multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed, including: S21. Unify multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data, into the BeiDou grid code spatiotemporal reference: If the i-th sensor observes the position of the target in the sensor coordinate system at time t, the observed value is x. i (t), then through the coordinate transformation matrix T i Position observations X converted to geocentric coordinates i (t): ； Time alignment uses linear interpolation to align all location observations X. i (t) Aligned to a uniform system timestamp T sys : ； Among them, X i (T sys ) represents the system timestamp T of the i-th sensor. sys The observed position of the target in the geocentric coordinate system, X i (t k ), X i (t k+1 Let ) represent the time of the i-th sensor at time t. k t k+1 The observed position of the target in the geocentric coordinate system was obtained; S22. To address the multipath interference caused by the "canyon effect" in petrochemical plant areas, establish an error compensation model based on environmental perception: In the error compensation model, the location observation X i (T sys The effect of multipath propagation can be expressed as: ； Among them, X i (T sys ) ture For the i-th sensor at system timestamp T sys The true position of the target in the geocentric coordinate system was observed, e mp (p i v) represents the position p of the i-th sensor. i The multipath error term related to the target velocity v For random noise; By pre-collecting a multipath feature database of the factory area environment, an error lookup table is established for the location observation value X. i (T sys Perform error compensation: ； Among them, X i '(T sys ) represents the system timestamp T of the i-th sensor. sys The position of the target in the geocentric coordinate system was observed and compensated for. For the position p of the i-th sensor i The multipath error estimate related to the target velocity v is obtained by using a pre-established error lookup table, based on the position p of the i-th sensor. i The error prediction value obtained by querying the target velocity v; S23. If the same target is detected by multiple sensors, a weighted fusion algorithm based on the variance of measurement error is used for position fusion, and the location is determined at the system timestamp T. sys Lower fusion position estimate for: ； in, Let be the weighting coefficient of the i-th sensor. , Let be the measurement error variance of the i-th sensor, and n be the number of sensors participating in the fusion. Total error after fusion for: 。 5. The method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area according to claim 1, characterized in that: S3 performs dynamic updates, partial updates, and version management of the grid status, enabling real-time updates and historical backtracking of the airspace situation, including: 1) Dynamically update trigger conditions, specifically including: New targets entering the airspace, changes in target location, targets leaving the airspace, establishment / removal of temporary control areas, and changes in environmental parameters; 2) Partial update mechanism: A local update strategy based on grid coding is adopted, updating only the grid cell that triggers the dynamic update and its neighboring grids to form a spatial situation map: The set of neighboring grids within the airspace is: ； Where N(g) is the set of grid cells G that triggers the dynamic update. changed The set of neighboring grids of a grid cell g, dist(g',g) represents the calculation of the spatial distance between two grid cells g' and g, and r is the neighborhood radius; 3) Version Management: Set a version number for each updated airspace situation map, supporting historical version rollback. Version differences can be represented as follows: ； in, Let k be the set of version differences in the k-th update. , These are the sets of grid cells that trigger dynamic updates for the k-th and (k-1)-th updates, respectively. \ represents the set difference operator, used to calculate the set difference in... It exists in, but The set of all grid cells that do not exist in the array.

6. The method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area according to claim 1, characterized in that: In S4, target threat assessment is performed and countermeasure resources are allocated to quickly counter the threat target, including: S41. For detected non-cooperative targets, a weighted model is used to calculate their threat probability P. threat : ； Among them, A traj Let v' be the trajectory anomaly degree, and v' be the flight speed of the non-cooperative target. max Where h is the maximum permissible flight speed in this airspace, and h is the flight altitude of the non-cooperative target. safe R is the lower limit of the safe altitude for this airspace. signal For signal compliance, , , , All are weighting coefficients, and ; S42, Preset warning trigger threshold and countermeasure trigger threshold Implement a tiered response mechanism for non-cooperative targets based on threat probability: when When non-cooperative targets are determined to be low-threat targets, an electronic fence alarm is sent and a voice warning is issued to drive them away. when When a non-cooperative target is identified as a medium threat target, targeted electromagnetic interference is initiated, communication is cut off, and location is determined. when If a non-cooperative target is identified as a high-threat target, a combined signal deception and physical capture response will be initiated. S43. Based on grid coding, spatial matching between medium-threat targets / high-threat targets and countermeasures devices is achieved, and the countermeasures device that is closest to the target's grid cell and is in an idle state is selected for processing.

7. The method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area according to claim 1, characterized in that: The S5 performs 3D visualization rendering, intuitively presenting the airspace situation, target trajectory, and countermeasure equipment status, including: A hierarchical coloring strategy is used to achieve the visualization rendering of 3D stereoscopic images, specifically including: 1) Grid boundary lines: Semi-transparent thin lines are used to show the grid hierarchy of the grid cells; 2) Airspace status: Colored according to the dynamic status code of the grid cell, no-fly zone is red, altitude-restricted zone is yellow, buffer zone is orange, and suitable flight zone is green; 3) Target trajectory: Historical trajectory points are displayed using a trailing effect, with the size and color of the points indicating their time sequence; 4) Countermeasures equipment: Use icons to indicate the location, type, and working status of the equipment.

8. A system for compiling a three-dimensional safety map of a petrochemical plant area, applicable to the method for compiling a three-dimensional safety map of a petrochemical plant area as described in claim 1, characterized in that: It includes a data acquisition layer, a mesh partitioning layer, a spatiotemporal modeling layer, a data fusion layer, a dynamic update layer, a visualization and linkage layer, and a result output layer; The data acquisition layer collects multi-source data, including BeiDou positioning, radar, photoelectric, and spectrum data. The petrochemical plant area is divided into multiple levels of grids based on GeoSOT. The grid accuracy is matched according to the target size, and a unique BeiDou grid code is generated for each grid cell. The spatiotemporal modeling layer performs 3D modeling in a 3D mesh system for key areas of the petrochemical plant, including the refining unit area, large storage tank area, wharf, and pipeline corridor. The data fusion layer unifies multi-source data to the BeiDou grid code spatiotemporal reference, establishes an error compensation model based on environmental perception to suppress multipath interference, and performs multi-source data fusion. The dynamic update layer dynamically updates, partially updates, and manages the version of the grid status, generates an airspace situation map, and enables real-time updates and historical backtracking of the airspace situation. The visualization and linkage layer performs target threat assessment and dispatches countermeasure resources to quickly counter threat targets, and performs 3D stereoscopic visualization rendering to intuitively present the airspace situation, target trajectory and countermeasure equipment status; The output layer outputs airspace situation maps, 3D stereoscopic maps, threat warning information, and countermeasures results, and supports historical retrospective analysis and annotation of airspace situation maps.

9. A computer device, characterized in that: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements the various steps of the method for compiling a low-altitude safety three-dimensional stereoscopic map of a petrochemical plant area as described in any one of claims 1-7.

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