Emergency rescue method and system based on satellite positioning

Abstract

The invention relates to the technical field of satellite positioning, and discloses an emergency rescue method and system based on satellite positioning, and the method comprises the steps: obtaining the real-time information of a region and the function information of an emergency unit, dispatching a satellite to carry out image collection and signal linkage, analyzing a satellite image and signal data, and constructing an emergency rescue real-time model; a multi-search scheme is formulated according to the model and issued to each emergency rescue unit, search work is executed, the rescue scheme is dynamically adjusted according to feedback information, and a cyclic execution mechanism is formed. According to the method, real-time and accurate data support is provided through the satellite technology, the efficiency, accuracy and strain capacity of emergency rescue are improved, and the rescue efficiency is improved. Rapid and effective disaster area rescue is ensured, and the problem of poor linkage between a satellite and a ground unit in emergency rescue in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite positioning, and particularly to an emergency rescue method and system based on satellite positioning. Background Art

[0002] In emergency rescue missions, especially in disaster rescue operations, how to accurately and quickly locate the specific situation of the disaster area and effectively coordinate various emergency rescue units is the key to ensuring the smooth progress of the rescue work. With the rapid development of satellite technology, especially the wide application of technologies such as satellite positioning, remote sensing imaging, and signal communication, the emergency rescue method based on satellite positioning has gradually become an efficient emergency response plan. In the existing satellite rescue assistance plans, there is a lack of in-depth linkage between satellite functions and ground rescue units, resulting in the lack of flexibility and adaptability of satellite assistance functions. Summary of the Invention

[0003] The purpose of the present invention is to provide an emergency rescue method and system based on satellite positioning, aiming to solve the problem of poor linkage between satellites and ground units in emergency rescue in the prior art.

[0004] The present invention is implemented as follows. In the first aspect, the present invention provides an emergency rescue method based on satellite positioning, including: Obtaining the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue units, and performing emergency scheduling on the positioning satellites prepared for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units; Performing satellite image acquisition and satellite signal connection on the emergency rescue area through the image positioning function and signal link function of the emergency satellite units to obtain the satellite image data and signal link data of the emergency rescue area; Performing multiple content analyses on the satellite image data and the signal link data for the landform where the emergency rescue units are located, the unit self-positioning relationship, and the rescue target positioning relationship, and expressing the results of the multiple content analyses in the form of digital feedback to obtain an emergency rescue actual situation model; Analyzing the specific implementation plans of multiple search methods for each of the emergency rescue units relative to the emergency rescue area according to the emergency rescue actual situation model to obtain multiple rescue plans for each of the emergency rescue units; Issuing the multiple rescue plans to the corresponding emergency rescue units, instructing the emergency rescue units to perform the search work corresponding to the multiple rescue plans, obtaining rescue search information and substituting it into the emergency rescue actual situation model to circularly perform the rescue plan analysis and execution of the emergency rescue units.

[0005] In a second aspect, the present invention provides an emergency rescue system based on satellite positioning, which is used to implement an emergency rescue method based on satellite positioning as described in any one of the first aspects, including: A satellite dispatching module is used to obtain the regional real-time information of the emergency rescue area and the unit function information of the emergency rescue unit, and perform emergency dispatch on the positioning satellites prepared for rescue according to the regional real-time information and the unit function information to obtain a number of emergency satellite units; A data acquisition module, used to acquire satellite images and link satellite signals of the emergency rescue area through the image positioning function and signal link function of the emergency satellite unit, so as to obtain satellite image data and signal link data of the emergency rescue area; A real-time simulation module is used to perform multiple content analysis on the satellite image data and the signal link data, including the terrain where the emergency rescue unit is located, the unit's self-positioning relationship, and the rescue target's positioning relationship, and to express the results of the multiple content analysis in the form of digital feedback to obtain a real-time emergency rescue model; A rescue search module, used for analyzing the specific implementation scheme of the multiple search methods for each of the emergency rescue units relative to the emergency rescue area according to the emergency rescue real-time model, so as to obtain multiple rescue schemes for each of the emergency rescue units; The continue execution module is used to send the multiple rescue plans to the corresponding emergency rescue units, order the emergency rescue units to perform the search work corresponding to the multiple rescue plans, obtain the rescue search information and substitute it into the emergency rescue real-time model, so as to cyclically analyze and execute the rescue plans of the emergency rescue units.

[0006] The present invention provides an emergency rescue method based on satellite positioning, which has the following beneficial effects: The present invention obtains regional real-time information and emergency unit function information, dispatches satellites to perform image acquisition and signal linking, analyzes satellite images and signal data, builds a real-time model of emergency rescue, formulates multiple search plans based on the model and sends them to each emergency rescue unit, executes the search work and dynamically adjusts the rescue plan based on feedback information, and forms a circular execution mechanism. This method provides real-time and accurate data support through satellite technology, improves the efficiency, accuracy and adaptability of emergency rescue, ensures rapid and effective disaster area rescue, and solves the problem of poor linkage between satellites and ground units in emergency rescue in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 It is a schematic diagram of the steps of an emergency rescue method based on satellite positioning provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of an emergency rescue system based on satellite positioning provided by an embodiment of the present invention. Detailed implementation manners

[0008] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0009] The implementation of the present invention will be described in detail below with reference to specific embodiments.

[0010] Referring to Figure 1 、 Figure 2 as shown, a preferred embodiment of the present invention is provided.

[0011] In a first aspect, the present invention provides an emergency rescue method based on satellite positioning, including: S1: Obtain the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue unit, and perform emergency scheduling on the positioning satellites reserved for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units; S2: Perform satellite image acquisition and satellite signal connection on the emergency rescue area through the image positioning function and signal connection function of the emergency satellite unit to obtain satellite image data and signal connection data of the emergency rescue area; S3: Perform multi-content analysis on the satellite image data and the signal connection data for the landform where the emergency rescue unit is located, the self-positioning relationship of the unit, and the rescue target positioning relationship, and express the results of the multi-content analysis in the form of digital feedback to obtain an emergency rescue actual situation model; S4: Analyze the specific implementation plans of various emergency rescue units in a multi-search manner relative to the emergency rescue area according to the emergency rescue actual situation model to obtain multi-rescue plans for various emergency rescue units; S5: Send the multi-rescue plans to the corresponding emergency rescue units, and order the emergency rescue units to perform the search work corresponding to the multi-rescue plans, obtain rescue search information and substitute it into the emergency rescue actual situation model to circularly analyze and execute the rescue plans of the emergency rescue units.

[0012] Specifically, in step S1 of the embodiment provided by the present invention, detailed actual situation information of the emergency rescue area is obtained by using satellite image data, signal link data, other sensor data, etc., including but not limited to the terrain of the disaster area, weather conditions, positions of trapped people, traffic network conditions, etc. This information is usually comprehensively collected through real-time satellite images, sensor networks, meteorological data, and ground sensors. The functional information of each emergency rescue unit is collected, including the equipment types of the rescue unit (such as medical, fire, engineering, etc.), rescue capabilities (such as the number of team members, equipment types, transportation tools, etc.), location, and current status. This information can be obtained through the real-time communication system of the rescue unit and reflects the current preparedness status and available resources of the unit.

[0013] More specifically, by combining the area actual situation information and the unit functional information, different possible emergency rescue tasks are analyzed. By analyzing the geographical information of the area, the priorities of the rescue tasks are determined. At the same time, considering the functional characteristics of each emergency rescue unit, it is evaluated whether it can effectively execute the tasks in this specific environment. The positioning satellites are dynamically scheduled according to the actual situation information and the unit functional information. By analyzing the actual situation and requirements, appropriate satellites are selected for positioning support, which may include scheduling satellites to provide target positioning, communication link, navigation information, etc. support. The scheduling of emergency satellites needs to consider their working ranges, resource configurations, and the urgency of the rescue tasks, determine the required satellite types (such as communication satellites, positioning satellites, surveillance satellites, etc.) and the number and orbits of the scheduled satellites to ensure that they can effectively support the tasks.

[0014] More specifically, according to the scheduling information, the required satellites are formed into several emergency satellite units. Each emergency satellite unit is responsible for different emergency rescue areas or tasks to ensure that positioning, communication, and monitoring during the rescue process can cover all key areas. Each satellite unit collaborates through the real-time communication system to provide continuous satellite support, update the actual situation information in real time, and provide precise support for the task execution of the rescue unit. During the emergency rescue process, the satellite unit monitors the rescue progress in real time and makes feedback adjustments to the already scheduled satellite resources to ensure that the orbits and positioning tasks of the satellites can be adjusted in a timely manner as the rescue requirements change, ensuring the optimal allocation of resources.

[0015] It is understandable that through precise satellite scheduling, it is ensured that rescue units can obtain real-time position information, navigation support, and communication guarantee within the shortest time, avoiding waste of resources and improving rescue efficiency. Through the comprehensive analysis of regional actual situation information and unit function information, emergency satellites and rescue units are rationally allocated to ensure that different types of rescue tasks can receive appropriate satellite support, avoiding the situation of over-concentration or insufficient allocation of resources, and optimizing the allocation of rescue resources. The dynamic scheduling of satellites can cope with different emergency scenarios, including uncertain factors such as weather changes and traffic blockades in the disaster area. Satellite units can flexibly adjust their tasks and orbits to make the rescue plan more adaptable and executable.

[0016] More specifically, positioning satellites provide real-time and precise positioning information for rescue units, ensuring efficient coordination and communication in rescue operations, which is crucial for emergency rescue in complex environments, especially in remote or severely disaster-stricken areas. Through real-time satellite data feedback, regional actual situation information, and task dynamics, the command center can make accurate decisions based on satellite images and data, ensuring the directionality and strategy of rescue task execution, and enhancing the scientificity and effectiveness of emergency command and decision-making. Through the above technical steps and effects, it can ensure the smooth execution of emergency rescue tasks, improve rescue efficiency, and reduce rescue delays caused by improper resource allocation or information lag.

[0017] Specifically, in step S2 of the embodiment provided by the present invention, the satellite activates its image acquisition and positioning functions in orbit according to the predetermined task path and geographical area. The emergency satellite unit has various image acquisition capabilities, including high-definition visible light images, infrared imaging, radar imaging, etc., to meet the image requirements under different weather, lighting, and terrain conditions. Using the satellite's sensor system (such as optical sensors, infrared sensors, synthetic aperture radar (SAR), etc.), image acquisition is carried out on the designated area. These satellite sensors will select suitable bands (such as visible light, infrared, millimeter wave, etc.) according to the task requirements to cope with various weather and environmental conditions. Satellite image acquisition includes real-time shooting of the disaster area, monitoring of key facilities (such as roads, bridges, buildings, etc.), and detailed scanning of terrain and obstacles.

[0018] More specifically, the satellite obtains precise positioning data of the emergency rescue area through its positioning system (such as the Global Navigation Satellite System (GNSS)), including the longitude, latitude, elevation, and other relevant information of the disaster area. These positioning information is crucial for subsequent rescue unit navigation, path planning, and target positioning. The satellite also establishes a signal link with the ground command center or emergency rescue units through its communication module. The signal link function can ensure the smooth transmission of information between the satellite and the ground, as well as between different emergency satellite units, including image data, positioning information, and other rescue-related data. The satellite image data is transmitted to the ground station or command center in real-time through the satellite's communication link. At the receiving end, the image data will be processed, analyzed, and stored. The processing of the image data can include image enhancement, target recognition, obstacle detection, post-disaster assessment, etc. During the transmission process, the satellite signal link function can ensure the stability of data transmission and avoid signal interference or loss.

[0019] More specifically, the satellite signal link function not only transmits image data but also can transmit real-time communication data, video surveillance information, and other multimedia data. The ground command center can receive feedback from each rescue unit in real-time through the satellite signal link to ensure the coordination and information sharing of rescue tasks. Emergency rescue units can receive updated positioning information, disaster area dynamics, and other rescue instructions through the satellite signal link, so as to make adjustments and plans. The collected satellite image data and signal link data are fused through an advanced analysis system. The analysis system will integrate satellite images and signal data to conduct disaster area condition assessment, personnel positioning, resource distribution analysis, etc., and generate decision support information. For search and rescue tasks, the system can use the target recognition function in the image to automatically mark the positions of trapped people or damaged facilities and provide accurate target coordinates for rescue units.

[0020] More specifically, based on the feedback of satellite images and signal link data, the command center can adjust the rescue task in real-time. For example, according to the updated information provided by satellite images and signal data, the command center can adjust the action path of the rescue team, dispatch new rescue units, or adjust the configuration of equipment and resources. If new obstacles or changes occur during the rescue process, the satellite images and signal link data can be quickly updated and provided to the rescue units for timely response.

[0021] It is understandable that through the high-precision positioning function and image acquisition technology of satellites, real-time and accurate positioning information of the disaster area can be obtained, avoiding positioning errors in traditional rescue methods and improving the accuracy of rescue tasks. Satellites can comprehensively monitor the disaster area through different types of sensors (such as visible light, infrared, radar, etc.). Even in bad weather, complex terrain or at night, satellites can still provide effective image data to ensure that rescue units obtain a comprehensive and clear picture of the disaster area. The real-time transmission of satellite images and signal data enables the command center to make quick decisions based on the latest dynamics of the disaster area. Data analysis and fusion technology provide a scientific basis for the scheduling, target positioning and resource allocation of rescue tasks, avoiding resource waste and improving rescue efficiency.

[0022] More specifically, satellite signal links ensure information sharing and real-time communication among emergency rescue units. Through the communication link of the satellite, different units can quickly exchange important data to ensure the smooth execution of tasks and avoid the phenomenon of information islands. The satellite image acquisition function can continuously monitor the disaster area dynamically, which not only helps to evaluate the initial disaster situation, but also can track the progress of post-disaster recovery and environmental changes. This provides valuable information support for long-term rescue and recovery work. In case of emergencies, satellite images and signal link data can quickly respond to rescue needs and update the dynamic changes of the disaster area in a timely manner, ensuring that rescue decisions are highly flexible and adaptable.

[0023] Specifically, in step S3 of the embodiment provided by the present invention, satellite image data includes high-definition images, infrared images, radar images, etc., which reflect information such as the terrain, buildings, traffic conditions and disaster distribution of the disaster area. Signal link data includes the positioning information of the satellite, signal strength, communication status between the satellite and ground units, transmission speed, etc., which are used to describe the communication status between the satellite and rescue units.

[0024] More specifically, extract geomorphic features from satellite images, including the distribution of terrain, roads, rivers, buildings, etc., analyze the geographical environment of the disaster area, and use image recognition algorithms (such as object detection, terrain classification, etc.) to automatically identify important geographical information and provide a detailed geographical background for subsequent rescue tasks.

[0025] More specifically, based on satellite positioning data, analyze the current position and relative position of each emergency rescue unit. By comparing the position of the emergency rescue unit with geographical data, judge whether it is in a terrain suitable for carrying out rescue. If the unit is located in an unfavorable terrain (such as mountainous areas, damaged urban areas, etc.), path optimization needs to be carried out according to geographical information and the action route needs to be re-planned. For the self-positioning data of each unit, the relative position with other units can also be analyzed to ensure that path planning and task allocation can be optimized when multiple units work together.

[0026] More specifically, using satellite images and signal link data, the specific locations of rescue targets (such as trapped persons, damaged buildings, damaged transportation facilities, etc.) are located. For specific targets, combining the positioning data and image analysis, the coordinate information of the targets is accurately calculated. These positioning information is transmitted to the command center or rescue units through signal links, used to adjust the rescue strategy in real time, further combining the positioning data of each rescue unit to optimize the target approach path and ensure approaching the rescue target quickly and effectively.

[0027] More specifically, the above-analyzed landform features, unit self-positioning relationships, and rescue target positioning relationships are integrated to form a comprehensive emergency rescue situation model. This model not only shows the geographical information of the disaster area but also can display the positions of each rescue unit, the positions of rescue targets, and the distances and relationships between them. Through data fusion technology, information from different data sources (images, positioning, signals, etc.) is correlated and analyzed to construct a multi-dimensional rescue situation model.

[0028] More specifically, based on the results of multiple content analyses, an emergency rescue situation model is generated in the form of digital feedback. This model can include the following information: positioning data of emergency rescue units: the current positions, task statuses, and relative positions with other units of each rescue unit; landform and transportation network data: the terrain, road conditions, obstacles, etc. in the disaster area, as well as the accessibility of relevant transportation networks; rescue target positioning data: the precise positions, types (such as trapped persons, damaged buildings, broken roads, etc.), and statuses (such as the degree of damage, distance, etc.) of each rescue target. The emergency rescue situation model is presented graphically or digitally to facilitate decision-makers to quickly understand and make decisions.

[0029] More specifically, the generated rescue situation model is verified to check the accuracy and rationality of the data. Based on the feedback results, the model is optimized to ensure that the model can adapt to the changing rescue needs. During the rescue process, the model is updated in real time. Through continuous input of satellite images and signal data, the model can be continuously adjusted to reflect the latest rescue situation.

[0030] It is understandable that by comprehensively analyzing the relationship between landforms, unit positioning, and target positioning, and precisely identifying and dispatching rescue resources, rescue units can take the quickest and safest routes based on the real-time feedback information, reducing unnecessary detours and time waste. The rescue situation model integrates various information such as the geographical environment, unit locations, and rescue targets to form a comprehensive decision-making support system. The command center can optimize rescue tasks from different perspectives (such as terrain, distance, time, etc.) to avoid decision-making mistakes caused by incomplete information. The rescue situation model supports real-time updates and dynamic adjustments. During the rescue process, with the input of new satellite images and signal data, the model will immediately reflect new terrain changes, unit status, and target positioning, thus helping the command center promptly adjust rescue strategies and resource allocation.

[0031] More specifically, through precise self-positioning and target positioning, multiple rescue units can effectively cooperate. Information sharing and task allocation among units are more efficient, avoiding duplicate or inefficient actions, enhancing rescue efficiency and coordination. By combining satellite images and signal data, high-precision positioning of rescue targets (such as trapped people, collapsed buildings, etc.) can be achieved. For large-scale disasters, quickly and accurately positioning targets is the key to ensuring rescue efficiency and effectiveness. Based on multiple content analyses, the allocation of emergency resources can be dynamically adjusted. The model can reasonably arrange the departure time, route selection, and task priorities of rescue teams according to real-time data feedback, maximizing the utilization efficiency of rescue resources. The rescue situation model provides a panoramic view of the disaster area for monitoring, helping the command center clearly understand the real-time situation in all aspects and ensuring that decision-makers can make quick, reasonable, and effective decisions.

[0032] Specifically, in step S4 of the embodiment provided by the present invention, obtain the current positions of each rescue unit from the emergency rescue situation model, including their geographical coordinates, existing tasks, capabilities (such as available resources, number of personnel, etc.), and status (such as whether they are currently performing tasks, whether they need supplies, etc.). By analyzing the task descriptions of each rescue unit, clarify the priorities, time windows, and task requirements (such as rapid rescue, resource allocation, medical assistance, etc.) of their current tasks, and ensure the rationality and feasibility of the tasks.

[0033] More specifically, according to information such as the landform, traffic conditions, resource requirements, and disaster situation distribution in the disaster area, use the emergency rescue situation model to divide the disaster area into regions. Each region is refined according to the characteristics of the disaster (such as areas where people are trapped, areas where infrastructure is damaged, areas with medical needs, etc.). Match the tasks of each emergency rescue unit with specific regions in the disaster area. For example, units with medical rescue capabilities will be assigned to areas where the injured are concentrated, and units with fire-fighting capabilities will be assigned to areas with fires or chemical leaks.

[0034] More specifically, satellite image data is utilized to conduct a search and analysis of each potential target in the disaster area. Based on the results of the image analysis, key targets such as trapped people, damaged buildings, and impassable roads can be quickly identified. Satellite images can assist in determining the optimal routes for rescue units and search areas. By combining the high-altitude images of drones with satellite images, a more detailed ground search can be carried out. Drones can obtain detailed information about the disaster area while uploading images in real time, helping rescue units quickly identify targets. Based on various algorithms (such as Dijkstra's algorithm, A* algorithm, etc.), path optimization is performed by integrating geographical information, transportation networks, obstacle data, etc., ensuring that rescue units can reach the target area in the shortest time.

[0035] More specifically, based on the real-time updates of satellite image data and signal link data, the dynamic changes in the disaster area are monitored. For example, if a new disaster situation occurs in a certain area (such as a secondary disaster or a new fire), the tasks of the current rescue units are adjusted in real time. During the rescue process, the search strategies of each rescue unit are dynamically adjusted. For example, through real-time data feedback, a rescue unit may need to adjust the task priority, adjust the search area, or even re-plan the travel route to adapt to the changes in the disaster area environment.

[0036] More specifically, multiple rescue plans are generated according to different task requirements and search strategies. Each rescue plan will consider factors such as different routes, search sequences, time limits, etc., to ensure that different disaster situations can be dealt with. For example, one plan may focus on quickly searching for and rescuing people, while another plan may focus on traffic restoration or infrastructure reconstruction. All the generated rescue plans are evaluated, and different plans are ranked based on effectiveness and efficiency indicators (such as response time, rescue success rate, resource consumption, etc.), so as to select the optimal rescue plan.

[0037] More specifically, the multiple search plans and their evaluation results are transmitted to the command center or rescue units in the form of digital feedback. By comprehensively presenting the advantages and disadvantages, key decision-making points, and feasibility analysis of different plans, it helps the command center make the final decision. The specific implementation plans of each rescue unit are digitally described, including the estimated task completion time, search routes, action steps, etc., ensuring that rescue units can accurately understand the tasks and their implementation processes.

[0038] More specifically, according to the output results of the decision support system, the execution of multiple rescue plans is initiated. Each emergency rescue unit departs within the shortest time according to the instructions and conducts operations in accordance with the formulated multiple search plans. During the rescue execution process, through real-time feedback data such as satellite signal links and drones, the execution status of each rescue unit is continuously monitored, and the rescue operations are adjusted in a timely manner according to the feedback results to ensure the efficiency and effectiveness of the rescue work.

[0039] It is understandable that through the design of a multiple search plan, the optimal allocation of rescue resources can be ensured. Each rescue unit is assigned to the most suitable task area according to its characteristics and the actual needs of the disaster area, maximizing the utilization rate of resources. The multiple search method combines various technologies such as satellite images, drones, and ground searches, greatly improving the efficiency and accuracy of the search. Different search means cooperate with each other to ensure that the rescue target can be quickly locked and the task can be effectively executed in complex terrains.

[0040] More specifically, during the rescue process, with the change of the disaster area environment, the real-time updated emergency rescue situation model provides comprehensive dynamic feedback to the command center. Based on this information, the order of task execution and the rescue path can be dynamically adjusted to ensure that rescue units can flexibly respond to the changing disaster situation. The design and evaluation of the multiple rescue plan ensure the selection of the most effective route and task among multiple alternative plans, thus reducing time waste, avoiding redundant actions, and improving the overall response speed. Through the integration of the multiple search method and the transmission of digital feedback, each emergency rescue unit can better cooperate. The command center can real-time grasp the action status and task progress of each unit, thereby improving the decision-making efficiency and ensuring that each unit can effectively cooperate in the coordination, reducing misunderstandings and information islands.

[0041] More specifically, after adopting the multiple search method, rescue units can cover a wider disaster area, including areas that are difficult to reach. The combination of satellite images and drones enables rescue personnel to quickly lock in areas that are difficult to reach and quickly dispatch corresponding units for rescue. Through digital feedback and detailed plan analysis, decision-makers can clearly understand the advantages and disadvantages of each rescue plan, providing a scientific basis for the final decision. This transparent decision-making process improves the accuracy and credibility of the decision.

[0042] Specifically, in step S5 of the embodiment provided by the present invention, according to the pre-developed multiple rescue plan, the command center assigns different rescue tasks to each emergency rescue unit. Each unit will receive detailed task instructions, including information such as the task area, search route, time window, task priority, available resources, etc. Through means such as wireless communication networks and satellite connections, it is ensured that the rescue task information is quickly and accurately conveyed to each emergency rescue unit. All task instructions will be real-time synchronized and updated to the operation platforms or mobile terminals of each unit to ensure error-free communication between the command center and the rescue units.

[0043] More specifically, each emergency rescue unit conducts search work according to the task instructions. Depending on the task content, it may include different types of tasks such as personnel search and rescue, material transportation, disaster area investigation, fire extinguishing, etc. Each rescue unit will use its equipment (such as drones, satellite images, ground vehicles, etc.) to conduct real-time area searches. During the execution of the search task, the rescue unit collects real-time rescue data through various sensors, cameras, drones, or handheld terminal devices. This data includes the geographical information of the search area, rescue progress, discovered target locations, road conditions, encountered obstacles, etc.

[0044] More specifically, the collected data will be uploaded to the command center or rescue command system through a wireless communication network for real-time processing and analysis. The command center or rescue command system will input the search information feedback from each rescue unit into the emergency rescue situation model in real-time. The model will integrate and analyze the newly obtained data, update the current rescue status, including target location, resource allocation, task progress, etc. Based on the real-time updated data, the situation model will dynamically adjust the rescue strategy, evaluate the priority and urgency of each task area, and ensure the efficient use of resources and the smooth progress of tasks.

[0045] More specifically, the system will analyze the execution effect of the rescue task in real-time according to the newly input search information, evaluate the performance of each rescue plan. Key indicators such as task completion progress, target discovery rate, resource consumption, time consumption, etc. will be automatically monitored by the system. According to the feedback of the search data, if the rescue effect in a certain task area is not good or new difficulties occur (such as traffic interruption, rescue unit obstruction, etc.), the emergency rescue situation model will make real-time adjustments, re-evaluate the task assignment, search path, and priority, and optimize or switch the plan if necessary.

[0046] More specifically, the system uses artificial intelligence and machine learning algorithms to intelligently process the data accumulated during the rescue process, predict the next rescue needs, and propose better solutions to ensure the execution efficiency and effect of the rescue task. The emergency rescue task is a dynamic process. As each rescue unit continuously provides search feedback information, the entire rescue process will cycle continuously. Each round of task execution may lead to the optimization and adjustment of the plan, thereby improving the efficiency of the entire rescue process. After each execution cycle ends, the command center will obtain new data, then substitute it into the situation model for re-analysis, generate a new rescue plan, and distribute it to relevant units. In this way, through multiple rounds of cyclic optimization, the entire rescue process gradually approaches the optimal state.

[0047] More specifically, when the rescue mission is completed or the predetermined goal is reached, all relevant rescue information and execution data are aggregated to form the final report of the rescue process. By analyzing the execution effects of each task, the overall effects of multiple rescue plans are evaluated. The completed tasks and the experience feedback during the process will be recorded and used to optimize the design of future rescue plans, resource allocation, and decision-making models, providing references for future rescue tasks.

[0048] It can be understood that by circularly executing and real-time adjusting the rescue plan, the waste of resources of rescue units can be effectively avoided, ensuring that each unit exerts its maximum effectiveness in the areas and tasks where it is most needed, thereby improving the efficiency of the entire rescue process. Based on real-time data and a dynamic adjustment mechanism, the rescue command system can provide intelligent decision-making support in a changing environment. Through automated data analysis and optimized plan design, decision-makers can respond more accurately. Each rescue unit continuously adjusts its tasks and action paths according to real-time feedback, enabling the most reasonable allocation of resources (such as personnel, equipment, and materials), and avoiding unnecessary repetitive labor or resource waste.

[0049] More specifically, by obtaining search information in real time, rescue units can accurately lock the locations of affected people or damaged facilities and respond quickly, which greatly shortens the response time of the rescue. Especially in time-sensitive tasks (such as rescuing trapped people, extinguishing fires, etc.), the effect is particularly significant. Changes that occur during the rescue process (such as new disasters, resource shortages, etc.) can quickly adjust the task plan through the dynamic feedback of the system, making the rescue operation more adaptable and capable of flexibly coping with emergencies. Since rescue tasks are distributed, multiple emergency rescue units need to cooperate. Through a unified command platform and real-time data synchronization, each rescue unit can cooperate efficiently to ensure the successful completion of the task.

[0050] More specifically, the circular feedback and analysis of rescue tasks provide valuable data support for post-disaster recovery. Through the post-evaluation of the entire rescue process, the system can summarize experience and lessons, providing a basis for improvement in future emergency management. Every action during the rescue process is recorded in detail, including data collection, task execution, plan adjustment, etc. Through this transparent process, the execution of rescue operations can be tracked throughout the whole process, ensuring traceability for each link.

[0051] The present invention provides an emergency rescue method based on satellite positioning, having the following beneficial effects: The present invention obtains regional actual situation information and emergency unit function information, schedules satellites for image acquisition and signal connection, analyzes satellite images and signal data, constructs an emergency rescue actual situation model, formulates multiple search plans according to the model and distributes them to each emergency rescue unit, executes the search work and dynamically adjusts the rescue plan according to the feedback information, forming a loop execution mechanism. This method provides real-time and accurate data support through satellite technology, improves the efficiency, accuracy and response ability of emergency rescue, ensures rapid and effective disaster area rescue, and solves the problem of poor linkage between satellites and ground units in emergency rescue in the prior art.

[0052] Preferably, the steps of obtaining the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue unit, and performing emergency scheduling on the positioning satellites reserved for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units include: S11: Obtain the delineated range data of the emergency rescue area, retrieve the associated regional topographic map and regional path map in the specified geographic database according to the delineated range data, and at the same time obtain the real-time meteorological information and emergency event information of the emergency rescue area, and perform a live simulation on the regional topographic map according to the real-time meteorological information and the emergency event information to obtain the regional actual situation information of the emergency rescue area; S12: Obtain the unit function information of the emergency rescue units that are going to and have arrived at the emergency rescue area, and perform a feature conversion of the executable rescue methods on the unit function information to obtain the overall rescue method features corresponding to each emergency rescue unit; S13: Obtain the satellite function information of the positioning satellites reserved for rescue, and perform a feature conversion of the positioning assistance methods on the satellite function information of each positioning satellite to obtain the satellite positioning assistance method features; S14: Perform a satellite positioning assistance requirement analysis on the overall rescue method features according to the regional actual situation information, and select auxiliary satellites for the satellite positioning assistance method features according to the analysis results to obtain a number of emergency satellite units; wherein, the emergency satellite units include image positioning satellites and signal connection satellites.

[0053] Specifically, first define the scope of the emergency rescue area, which may be a disaster area, an accident site or an affected area. This data is usually provided by GIS (Geographic Information System) tools and may include latitude and longitude coordinates, administrative divisions, and other geographical features. Using the defined delineated range data, query the relevant regional topographic map and regional path map. The regional topographic map contains geographical information such as terrain, elevation, and land use, while the regional path map shows path information related to rescue such as transportation networks and path densities.

[0054] More specifically, obtain real-time meteorological information of the emergency rescue area, including meteorological elements such as temperature, wind speed, precipitation, etc. These information can be obtained through meteorological satellites, ground meteorological stations or meteorological forecasting systems. At the same time, collect relevant information about the current emergency event, including event type (such as earthquake, fire, flood, etc.), event scale, emergency level, known number of affected people, etc.

[0055] More specifically, simulate the regional topographic map based on real-time meteorological data and emergency event information. This can help understand the possible impacts of meteorological factors (such as wind speed, precipitation, etc.) on terrain, disasters and rescue routes. For example, wind speed may affect the spread speed of fire, and precipitation may affect the expansion of flood areas. Through simulation, obtain the actual situation information of the emergency rescue area, including dynamic changes of disasters, real-time situation of the disaster area (such as changes in affected areas, feasibility of rescue routes, etc.) and possible future trends.

[0056] More specifically, obtain the function information of the units participating in the rescue. This may include resource allocation, task capabilities, action radius, etc. of various emergency rescue teams (such as fire brigades, rescue teams, medical teams, etc.). Perform feature transformation on the function information of each rescue unit and convert it into features of executable rescue methods. For example, the functions of a fire brigade may include fire extinguishing, evacuation, rescue, etc., and each function feature will map to different rescue requirements.

[0057] More specifically, collect the function information of positioning satellites, including satellite positioning accuracy, orbital parameters, visible range, imaging capabilities, etc. The satellite function information determines its usage scenarios in rescue. For example, image positioning satellites can provide high-resolution images, and signal link satellites can provide communication support. According to the satellite function information, convert it into features of positioning assistance methods. These features include positioning accuracy, coverage area, satellite orbit, imaging technology, communication capabilities, etc. Different satellites can support different types of positioning and communication requirements.

[0058] More specifically, based on the previous actual situation information of the area, analyze which types of satellites can provide positioning and communication assistance for the current rescue task. For example, if there is a communication break problem in a certain area, signal link satellites may be needed to provide communication support; if precise positioning of rescue targets is required in a certain area, image positioning satellites may be needed to provide ground images and geolocation support. Combine the actual situation information of the area with the function requirements of each rescue unit to form a demand model for different satellite positioning assistance methods and clarify the usage requirements of each satellite in different situations.

[0059] More specifically, according to the results of the requirements analysis, appropriate satellites are selected for support. During the selection process, requirements such as the positioning accuracy, coverage area, and real-time performance of the satellites are taken into account. Finally, based on the results of the requirements analysis, a number of emergency satellite units are determined. These satellite units include image positioning satellites and signal link satellites, which provide positioning, imaging, and communication support for different rescue tasks respectively.

[0060] It can be understood that through accurate satellite scheduling, the required positioning and communication information can be obtained in a timely manner in the disaster area or emergency site, significantly improving the rescue efficiency. The image positioning satellite can provide real-time ground images to help locate the victims or key facilities in the disaster area; the signal link satellite can provide communication restoration support for remote or communication-disrupted areas. By integrating the actual situation information, meteorological data, and emergency event information of the emergency area, the system can provide accurate decision-making support for the command center. By simulating different meteorological and disaster scenarios, potential difficulties in the rescue mission can be better predicted, and the satellite resource scheduling strategy can be optimized.

[0061] More specifically, by combining the function information of different rescue units with the positioning assistance requirements of the satellites, the system can select the appropriate satellite type and function configuration according to the actual situation of the rescue mission. This dynamic resource allocation method can avoid waste of resources and maximize the role of the satellites. According to the functional characteristics and real-time requirements of the satellites, the most suitable satellite is accurately selected for scheduling, thereby improving the utilization rate of satellite resources. In this way, different types of satellites can be reasonably allocated and used according to the requirements, avoiding unnecessary reuse of satellites.

[0062] More specifically, during the actual emergency rescue process, the situation changes rapidly, and the rescue requirements may also change at any time. By obtaining the actual situation of the area in real time and conducting dynamic analysis, the system can flexibly adjust the task allocation and scheduling of the satellites to ensure the adaptability and real-time performance of the rescue operation. After the rescue mission is completed, the data provided by the satellites (such as images and communication logs) can provide important data support for post-disaster recovery. For example, the damaged situation of the disaster area can be evaluated through satellite images, and then a more effective recovery plan can be formulated. The entire satellite scheduling process can be processed by an automated decision-making system, using technologies such as machine learning and data analysis to automatically select the most suitable satellite for scheduling, thereby reducing the intervention of manual decision-making and improving the scheduling efficiency.

[0063] Preferably, the step of collecting satellite image data of the emergency rescue area through the image positioning function of the emergency satellite unit includes: S21: Perform an initial positioning task assignment for the image positioning satellite serving as the emergency satellite unit to assign an initial image collection task to the image positioning satellite; S22: Have the image positioning satellite analyze the task execution instructions for the initial image acquisition task, and adjust and execute the working parameters of the image positioning satellite according to the task execution instructions corresponding to the initial image acquisition task, so as to drive the image positioning satellite to acquire images of the first observation scale for the emergency rescue area, and obtain a regional observation framework formed by splicing a number of satellite images of the first observation scale; S23: Based on the regional observation framework, further adjust and execute the working parameters of the image positioning satellite, so that the image positioning satellite acquires images of the second observation scale for the emergency rescue area, and fill in the detailed content of the regional observation framework according to the image acquisition results. Loop and execute this step to fill in the detailed content of the regional observation framework according to the image acquisition results of more observation scales until the image acquisition of the initial image acquisition task is completed, and satellite image data is obtained.

[0064] Specifically, first, according to the requirements of the emergency rescue area, allocate the initial positioning task to the image positioning satellite, which is used as an emergency satellite unit. This task includes determining basic parameters such as the area range, image resolution, and observation angle of the satellite images to be acquired. The initial task may include confirming the image area to be collected (such as the specific location of the disaster area), the desired image resolution (such as high resolution or low resolution), as well as the flight orbit and observation timing of the satellite.

[0065] More specifically, before the image positioning satellite executes the task, it is necessary to analyze the task execution instructions for image acquisition. These instructions are based on the initial task allocation and specify the detailed working parameters required for the satellite during image acquisition. By analyzing the task execution instructions, the working parameters of the image positioning satellite are adjusted, including camera angle, focal length, sensor settings, etc. These parameter adjustments enable the satellite to acquire image data of the target area at the set observation scale.

[0066] More specifically, after adjusting the working parameters, the image positioning satellite starts to execute the task and acquires images of the emergency rescue area. The goal of this process is to obtain images of the first observation scale of the area (i.e., preliminary image data). After multiple image acquisitions, a number of satellite images of the first observation scale will be obtained, and these images will be combined into a regional observation framework through splicing to form a preliminary image view of the overall area.

[0067] More specifically, based on the image stitching results at the first observation scale, a preliminary regional observation framework is formed. Next, the working parameters of the image positioning satellite are further adjusted so that the satellite can collect second-observation-scale images of the region with higher resolution. After adjusting the working parameters, the satellite starts to collect second-observation-scale images, which usually include more refined regional details to help better identify the specific situation in the disaster area. Based on the image collection results at the second observation scale, the details of the regional observation framework are filled in, which means integrating higher-resolution image data into the preliminary observation framework and gradually improving the details of the region.

[0068] More specifically, by adjusting the working parameters multiple times and collecting images, the satellite can continue to collect data at different observation scales. Each image collection provides more details for the regional observation framework, gradually improving the overall framework. This process will be repeated until all the image collection tasks of the initial mission are completed, ensuring that the satellite image data is detailed and comprehensive enough to cover all the key parts of the emergency rescue area. After completing the above steps, a complete satellite image dataset is finally obtained through the satellite image positioning function. This dataset includes images at multiple observation scales and covers all the areas to be collected and their detailed information.

[0069] It can be understood that through multiple observations and parameter adjustments, the image positioning satellite can gradually optimize the image quality, making the final satellite images have high-resolution data at different observation scales. This gradually optimized method ensures the accurate presentation of image details and helps with emergency rescue decision-making. By adjusting the working parameters of the image positioning satellite, images can be flexibly collected at different observation scales. This flexibility enables the satellite images to provide both a macroscopic view of the region and high-precision local images to meet different rescue needs.

[0070] More specifically, by stitching and integrating images at different observation scales, a complete regional observation framework is formed. This framework not only includes preliminary image data but also is continuously improved through detail filling, ultimately ensuring the integrity and accuracy of the image data. The generated satellite image data can support emergency rescue decision-making. The high-resolution image data enables rescue personnel to clearly understand key information such as the geographical layout, disaster situation, and traffic conditions in the disaster area, thus organizing rescue operations more effectively. Through real-time satellite image collection and analysis, the changes in the emergency rescue area can be quickly reflected, providing accurate real-time information about the disaster area. This real-time update ability is particularly important in emergency situations and can help decision-makers respond in a timely manner.

[0071] More specifically, through the detailed image data analysis of the area, resource scheduling can be carried out more precisely. For example, satellite images can help determine which areas are the most urgent, so as to prioritize the scheduling of resources such as rescue teams and supplies. The satellite image data can be shared with different rescue units and decision-makers, which helps the collaborative operation between different departments. This information sharing helps improve the coordination and efficiency of the overall rescue operation.

[0072] Preferably, the step of obtaining the signal link data of the emergency rescue area by satellite signal linking the emergency rescue area through the signal link function of the emergency satellite unit includes: S24: Assign an initial positioning task to the signal link satellite serving as the emergency satellite unit to allocate an initial signal link task to the signal link satellite; S25: Instruct the signal link satellite to parse the task execution instructions for the initial signal link task, and adjust and execute the working parameters of the signal link satellite according to the task execution instructions corresponding to the initial signal link task, so as to drive the signal link satellite to perform the signal link work between the emergency rescue unit and the emergency rescue target in the emergency rescue area, so that each emergency rescue unit and potential emergency rescue target are in a signal link state with the signal link satellite; wherein, the emergency rescue unit is a unit preparing to carry out emergency rescue work in the emergency rescue area, and the emergency rescue target is the intelligent terminal held by the object waiting for rescue in the emergency rescue area; S26: Perform signal positioning work through the signal link state between the emergency rescue unit and the emergency rescue target to obtain the signal positioning information of the emergency rescue unit and the emergency rescue target; S27: Send the surrounding environment positioning program to the emergency rescue unit and the emergency rescue target through the signal link state between the emergency rescue unit and the emergency rescue target for the emergency rescue unit and the emergency rescue target to execute the surrounding environment positioning program. The emergency rescue unit and the emergency rescue target obtain the surrounding environment image data by executing the surrounding environment positioning program to realize their own positioning based on the surrounding environment and obtain their own positioning information; S28: The signal positioning information and the self-positioning information of each emergency rescue unit and emergency rescue target together constitute the signal link data.

[0073] Specifically, according to the emergency response requirements of the disaster-stricken area, first assign an initial task to the signal link satellite, clarify its coverage area, link priority (such as rescue command center first vs. ordinary trapped persons), signal strength, frequency band and other technical parameters, and the system automatically or manually schedules satellite resources with communication capabilities to cover the emergency rescue area and complete the rapid link deployment.

[0074] More specifically, after the signal-link satellite receives the initial mission, it analyzes the mission execution instructions, identifies the types of communication links required to be completed (such as voice, text, data), the identities of the objects (rescue units, affected people), and the link quality requirements. According to the analysis results, it adjusts the operating parameters of the satellite, such as link frequency, beam direction, power output, etc., to make it enter the communication-ready state.

[0075] More specifically, professional rescue organizations of emergency rescue units carrying communication equipment and dispatching terminals, and intelligent terminals (such as mobile phones, smart bracelets, satellite communication equipment, etc.) held by ordinary people and affected people as emergency rescue targets. After the satellite completes parameter adjustment, it starts a communication link search to establish a real-time communication link with emergency rescue units and emergency rescue targets on the ground, forming a stable link state between the "satellite - user".

[0076] More specifically, once a signal link is established, the satellite will use wireless positioning technologies such as signal strength, time-of-arrival (ToA) ranging, and angle-of-arrival (AoA) to perform signal spatial positioning on each link object, forming signal positioning information for each link object (unit or target), including relative geographical coordinates, motion state, signal stability, etc.

[0077] More specifically, the satellite sends a "surrounding environment positioning program" to each emergency rescue unit and target terminal; the program has the function of collecting, identifying, and transmitting back image information, supports the device to obtain the surrounding scene through the camera, and after the terminal executes the program, it automatically collects or guides the user to collect the current surrounding image data, which may contain key elements such as landmarks, buildings, and terrain; the program performs image recognition and analysis locally or through the satellite to assist the user in self-positioning based on environmental features.

[0078] More specifically, through image comparison and matching with the satellite database, self-positioning accurate to blocks, buildings, and roads is achieved, and the positioning results are transmitted back to the signal-link satellite system together with the signal positioning information.

[0079] More specifically, the signal positioning information and self-positioning information of each emergency rescue unit and rescue target are unified and fused to form a structured signal-link data set, which can be used for analysis, dispatching, and visualization display by the backend platform.

[0080] It is understandable that satellites can quickly build a temporary communication network without relying on ground base stations or local communication facilities, providing emergency connection guarantees for disaster-stricken areas. Satellites can not only actively connect with users but also send tasks to them (such as environmental perception programs), enabling two-way information flow, promoting real-time interaction and disaster perception, and providing a basis for personalized rescue decisions. By combining wireless signal positioning (such as ToA, AoA) with image environment recognition positioning, it makes up for the blind spots of single positioning means; it is especially suitable for extreme disaster areas where traditional positioning (such as GPS) fails or is interfered with.

[0081] More specifically, through the collected signal link data, the command center can accurately grasp the spatial distribution of rescue units and targets; determine the priority rescue targets based on location information and link status; dynamically optimize resource allocation and improve rescue efficiency. Through the environmental image data collected by the terminal, the disaster area environmental scene can be reconstructed, used to judge the degree of building damage; plan the evacuation route for personnel; generate situation maps, heat maps, etc. to assist in rescue decisions.

[0082] More specifically, the system framework is applicable to various natural disasters such as earthquakes, floods, and landslides; it is also compatible with a variety of terminal devices (mobile phones, Beidou terminals, professional rescue equipment); it can be extended for information connection and control of subsequent intelligent devices such as drones and ground robots.

[0083] Preferably, the steps of performing multiple content analyses on the satellite image data and the signal link data for the landform where the emergency rescue unit is located, the self-positioning relationship of the unit, and the rescue target positioning relationship, and expressing the results of the multiple content analyses in the form of digital feedback to obtain the emergency rescue actual situation model include: S31: Perform three-dimensional digital modeling on the emergency rescue area according to the satellite image data to obtain a regional basic model; S32: According to the signal positioning information and self-positioning information of each emergency rescue unit and emergency rescue target in the signal link data, perform double-level positioning node conversion and positioning node connection for each emergency rescue unit and emergency rescue target to obtain a positioning node topology network constructed by a number of interconnected positioning nodes; wherein, the positioning node topology grid is used to describe the self-positioning relationship of the emergency rescue unit and the rescue target positioning relationship. S33: Based on the regional basic model, perform positioning verification and node deployment on the positioning node topology network to deploy the positioning node topology network to the regional basic model, and perform in-depth detailed three-dimensional modeling on the part of the regional basic model where the positioning nodes are deployed according to the satellite image data to obtain the emergency rescue actual situation model.

[0084] Specifically, first, obtain high-resolution satellite images of the emergency rescue area. Through image recognition technology and remote sensing data processing, convert the satellite images into analyzable geographical data. For 3D modeling, use topographic maps, geomorphic data, and satellite image data to perform 3D digital modeling, including: constructing the basic terrain of the area, such as the three-dimensional representation of mountains, rivers, roads, buildings, etc.; auxiliary information such as the height of buildings, ground conditions, natural obstacles, etc. The basic model of the area is finally established through these data to describe the natural and human environment of the disaster area.

[0085] More specifically, for signal link data processing and positioning node conversion, analyze the signal link data from emergency rescue units and rescue targets, and extract the signal positioning information contained therein (such as angle of arrival, time difference of arrival ranging, signal strength, etc.). For dual-level positioning, for the positioning of emergency rescue units, determine their positions in the three-dimensional space according to the signal positioning information and their own positioning information of the emergency rescue units. For the positioning of rescue targets, extract the positioning information of each affected target (such as ordinary people, trapped persons) in the disaster area and determine their precise positions relative to the satellite.

[0086] More specifically, convert the position points of each rescue unit and rescue target into positioning nodes. These nodes are subjected to dual-level conversion according to multi-dimensional information such as signal data, geographical data, and positioning accuracy. The nodes form a positioning node topological network through topological connection, and this network shows the spatial relationship and their interaction between the rescue units and the targets.

[0087] More specifically, construct an interconnected positioning node topological network by connecting the positioning nodes. This network not only represents the relative position relationship between the rescue units and the targets, but also can show the flow and cooperation paths of both in complex terrains. Perform interactive verification between the topological network and the basic model of the area. By comparing the actual environment (such as obstacles, buildings, roads) with the node positions, ensure that the node layout is reasonable and conforms to the actual terrain. The positioning verification is completed through existing satellite images and positioning data to ensure the accuracy and consistency of the model.

[0088] More specifically, deploy the verified positioning node topology network into the regional basic 3D model to overlay the spatial relationship layer between rescue units and targets onto the disaster area terrain, and conduct further in-depth detailed 3D modeling on the areas containing positioning nodes in the basic 3D model. These details can include the interior of buildings, optimization of rescue routes, precise distribution of personnel, etc. Use satellite image data, analyze the surrounding environment and combine with Geographic Information System (GIS) to refine the specific details around each positioning node (such as building height, road traffic conditions, potential obstacles, etc.). Integrate the detailed model and the positioning node topology network to construct an emergency rescue actual situation model, which shows the real-time spatial layout, relative positions, environmental factors, and task assignments between rescue units and targets.

[0089] It can be understood that the 3D basic model constructed through satellite images and remote sensing data provides a highly accurate description of the real terrain, buildings, and natural environment for subsequent positioning and environmental analysis, realizes the 3D modeling of complex disaster area environments, helps the rescue command center comprehensively understand the spatial layout of the disaster area, achieves the precise positioning of emergency rescue units and targets using signal link data, and provides high-precision spatial position data through double-level positioning node conversion. Through the positioning node topology network, the spatial relationships between different units and targets are clarified, facilitating the optimization of rescue plans.

[0090] More specifically, through the construction of the positioning node topology network, the command center can view the positions, environmental conditions, and task execution status of each rescue unit and target in real time, greatly enhancing the real-time, accuracy, and reliability of auxiliary decision-making, helping to quickly adjust rescue strategies in the dynamically changing disaster area environment. The combination of refined 3D modeling and positioning data can reflect the terrain changes and environmental dynamics in the disaster area in real time (such as building damage, road blockage, etc.), improving the spatial perception ability of rescue. The deep integration of environmental and positioning data enables the command system to comprehensively evaluate the accessibility of rescue units, the contactability of targets, and potential dangerous areas.

[0091] More specifically, through the construction of the model and the real-time update of positioning information, the rescue plan can be intelligently adjusted, resource allocation optimized, and the efficient implementation of rescue operations ensured. This system can automatically generate emergency rescue plans and dynamic emergency response strategies without manual intervention, improving rescue efficiency. Combining satellite images and positioning data, it can continuously monitor changes in the disaster area environment, including terrain damage, personnel migration, road traffic, etc., ensuring that the command center can obtain the most accurate disaster situation dynamics in real time.

[0092] Preferably, the specific implementation plan analysis of the multiple search method for each of the emergency rescue units relative to the emergency rescue area according to the emergency rescue actual situation model to obtain the multiple rescue plans for each of the emergency rescue units includes the following steps: S41: According to the unit function information of each of the emergency rescue units, simulate the movement paths of the emergency rescue units and the coverage areas of the multiple search methods on the emergency rescue actual situation model to obtain the expected search feature distributions of each of the emergency rescue units; wherein, the expected search feature distributions include a number of expected search features, and the expected search features are used to describe the areas that can be covered by the emergency rescue unit using a specified search method under a specified movement path, and the search methods include machine vision search, sound broadcast search, microwave radar search, and signal matching search; S42: Perform predictive analysis of potential emergency rescue targets on the emergency rescue actual situation model using a machine learning model trained with historical data to assign potential values of emergency rescue targets to specific locations in the emergency rescue actual situation model; S43: Take the positioning information of each detected emergency rescue target in the emergency rescue actual situation model as the first task target, and take the potential values of emergency rescue targets assigned to specific locations in the emergency rescue actual situation model as the second task target. Perform comprehensive analysis and task assignment of the first task target and the second task target on the emergency rescue actual situation model according to the expected search feature distributions of each of the emergency rescue units to obtain the expected search paths and expected search tasks of each of the emergency rescue units; S44: Combine the expected search paths and expected search tasks of the emergency rescue units to obtain the multiple rescue plans of the emergency rescue units.

[0093] Specifically, first collect the function information of each emergency rescue unit, such as rescue vehicles, medical teams, search and rescue dog teams, etc., to understand the specific functions, capabilities and limitations of each unit. These information are used to determine the roles of each unit in the task. According to the three-dimensional actual situation model of the emergency rescue area and the function information of each emergency rescue unit, use path planning algorithms (such as A* algorithm, Dijkstra algorithm, etc.) to simulate the movement paths of each unit. These paths should take into account factors such as road passability, terrain obstacles, and traffic conditions.

[0094] More specifically, simulate the coverage ranges of different search methods (such as machine vision search, sound broadcast search, microwave radar search, signal matching search) on different paths. Each search method has different efficiencies and coverage ranges under specific paths, so simulations are needed to obtain the expected search feature distributions of each unit.

[0095] More specifically, based on the functions of each emergency rescue unit and the technologies available to it, appropriate search methods are selected. For example, ground rescue teams use machine vision for search, aerial drones use microwave radar for search, and medical teams use voice broadcasts for search, etc. For each search method, according to the movement path, speed, and search ability of the emergency rescue unit, the coverage area along the path is simulated. The size and shape of the coverage area will be affected by many factors, such as the detection range of the search equipment, the complexity of the environment (such as obstacles, weather, etc.), and the unit's mobility. The expected search characteristics describe the area that an emergency rescue unit can cover using a specified search method along a specific movement path. The characteristics of this area can reflect the unit's search effectiveness, search efficiency, limiting factors, and possible areas of omission.

[0096] More specifically, historical data is used to conduct potential prediction analysis on emergency rescue targets. The historical data can include the occurrence frequency of targets in past disasters, the target distribution in specific environments, etc. Machine learning models (such as regression analysis, clustering analysis, neural networks, etc.) are used to train this historical data to predict potential emergency rescue targets that may exist in the current disaster area. The potential emergency rescue targets at each specific location are predicted through the machine learning model, and a potential value is assigned to each location according to the urgency, importance, and rescue difficulty of the target. These potential values will be used for the decision-making of subsequent task allocation.

[0097] More specifically, the positioning information of the known emergency rescue targets (such as trapped persons, fire sources, damaged facilities, etc.) is taken as the first task target. These targets are the determined location points and the key objects of the rescue task. The potential value of the potential emergency rescue targets at each location in the model is taken as the second task target. These targets represent possible dangers or rescue needs and need to be rescued according to priority and value. Based on the expected search characteristic distribution of each emergency rescue unit (i.e., the search ability and range of each unit), the first task target and the second task target are comprehensively analyzed. This analysis will evaluate the tasks that each unit can complete within its respective search range and assign reasonable task targets to each unit.

[0098] More specifically, the first task target (known target) is preferentially assigned to the unit closest to it within the search range; the second task target (potential target) is assigned tasks according to the potential value and search ability to ensure that important targets are processed in a timely manner.

[0099] More specifically, the expected search paths of each emergency rescue unit are combined with the expected task objectives to form the rescue tasks of the unit on different paths. For example, the ground rescue team may search for and rescue specific targets on the passable paths, while the aerial drones are responsible for a wider search. Based on the combination of the path and the task objective, multiple rescue plans are generated. Each plan can cover the search tasks of different units in different regions, and the cooperation and complementarity between different units are considered. These plans provide the emergency command center with multiple options to respond to different disaster situations.

[0100] It can be understood that by analyzing the expected search paths and task objectives of each emergency rescue unit, tasks can be accurately allocated and the action paths of each unit can be optimized. This not only improves the resource utilization efficiency but also maximizes the rescue effect of each unit. Based on the predictive analysis of the machine learning model, the positions and values of potential emergency rescue targets can be updated in real time, so as to dynamically adjust the emergency rescue tasks. Even in the case of continuous changes in the disaster area environment, the model can still make a rapid and accurate response.

[0101] More specifically, the multiple rescue plans consider the functions, paths, search methods, and task objectives of different units, making the rescue work more flexible and diverse. The emergency command center can select the plan most suitable for the current disaster situation to ensure the efficient completion of the rescue task. By simulating the coverage areas of different search methods, the rescue units can more accurately determine which areas need to be searched first and which potential targets need the most attention. Through the expected search feature distribution, resource waste can be avoided, and the accuracy and timeliness of the rescue can be improved. The multiple rescue plans can also promote the collaborative cooperation between different rescue units, avoid duplicate searches and task conflicts, and improve the overall rescue efficiency. The task allocation and area coverage between different units ensure the optimal integration of rescue resources.

[0102] Preferably, the steps of distributing the multiple rescue plans to the corresponding emergency rescue units, instructing the emergency rescue units to perform the search work corresponding to the multiple rescue plans, obtaining the rescue search information and substituting it into the emergency rescue actual situation model, and cyclically analyzing and executing the rescue plans of the emergency rescue units include: S51: Distribute the multiple rescue plans to the corresponding emergency rescue units, drive the emergency rescue units to the designated expected search paths in sequence according to the multiple rescue plans, and perform the expected search tasks through the designated search methods to obtain the rescue search information; S52: Substituting the rescue search information obtained by each of the emergency rescue units into the emergency rescue real-time model to perform real-time correction of model parameters of the emergency rescue real-time model, and analyzing the continued execution reference value of the multiple rescue plans of each of the emergency rescue units according to the real-time corrected emergency rescue real-time model to obtain the continued execution reference value of each of the multiple rescue plans; S53: performing scheme simulation adjustment and execution value evaluation on multiple rescue schemes of each of the emergency rescue units according to the emergency rescue real-time model, so as to obtain an adjusted rescue scheme of each of the emergency rescue units and an adjusted execution reference value corresponding to the adjusted rescue scheme; S54: Comprehensively evaluate the continued execution reference value of each of the multiple rescue plans and the adjusted execution reference value of each of the adjusted rescue plans to determine a subsequent rescue plan of the emergency rescue unit.

[0103] Specifically, the emergency rescue command center assigns tasks to various emergency rescue units according to the formulated multiple rescue plans, task type, unit function and path requirements. Each unit will receive a detailed rescue plan containing its designated expected search path, search method and mission objectives. Based on the issued task information, each emergency rescue unit will proceed in sequence along the specified expected search path, which includes providing route guidance through the path planning system and ensuring that the unit moves according to the established path and speed.

[0104] More specifically, search missions are carried out and rescue search information is collected. Based on the capabilities of each unit and the selected search method (such as machine vision, sound broadcasting, microwave radar, signal matching, etc.), the search of the designated area is started. This process includes real-time collection of sensor data and detection of targets. Each emergency rescue unit uploads the rescue information obtained during the search process (such as the location of the target found, the target status, the coverage effect of the search area, etc.) to the command center. This information is the basis for executing subsequent tasks.

[0105] More specifically, the rescue search information uploaded by each emergency rescue unit is substituted into the real-time emergency rescue model, and the model parameters are modified in real time according to the latest search information, that is, key information such as target location, potential danger area, resource distribution, etc. are updated in real time. The updated model can reflect the real-time location of the emergency rescue unit, the completion status of the current task, as well as new rescue targets and dynamic environmental changes. This enables the command center to grasp the rescue situation in real time and ensure that subsequent plans are more accurate.

[0106] More specifically, based on the emergency rescue situation model corrected according to the actual situation, a reference value analysis is carried out on the original rescue plans of each emergency rescue unit. This analysis is based on the data after model correction, such as the update of the target location, the optimization suggestions for the search path, and the new resource requirements, to evaluate the rationality of continuing to execute the original plan. The evaluation criteria for the reference value analysis will consider the following aspects: the completion of the current task objective; the effectiveness and coverage of the search path; the value and search priority of new potential targets.

[0107] More specifically, according to the results of the reference value analysis, a simulation adjustment is carried out on the multiple rescue plans of the emergency rescue unit, which includes optimizing the search path, adjusting the selection of the search method, and updating the priority of the task objective. The new plan will make full use of real-time data for dynamic optimization, and evaluate the execution value of the adjusted rescue plan. The evaluation criteria mainly rely on the following factors: whether the new plan can cover the new target area more efficiently; whether the search task can be completed at the expected speed and quality; whether it can better coordinate resources and avoid duplicate searches.

[0108] More specifically, a comprehensive analysis is carried out on the reference value of continuing to execute and the reference value of adjusted execution to obtain the optimal subsequent rescue plan. During the evaluation process, trade-offs will be made according to factors such as the urgency of the task, the difficulty of task completion, and the efficiency of resource utilization. Finally, the subsequent task execution plans of the emergency rescue unit will be determined. These plans will be based on the current emergency rescue situation model and the requirements of each task, maximizing the advantages of each unit and ensuring the efficient and rapid progress of the rescue task.

[0109] It can be understood that by collecting rescue information in real time and correcting the situation model, the rescue plan can be dynamically adjusted and optimized, which ensures that the emergency rescue unit can respond flexibly in a changing environment and will not be trapped in inefficient or wrong actions due to changes in resources or targets. After each task execution, the system can analyze the execution effect of the task according to the latest search data, and timely adjust the search path, search method, and task priority, which can ensure that the rescue unit maximally covers the potential target area in the disaster area and avoids missing important tasks.

[0110] More specifically, through the reference value analysis of execution and the simulation adjustment of the plan, the execution effect of each plan can be evaluated, and the strategy can be adjusted according to the actual situation, which greatly improves the execution success rate of each task and avoids the continuation of outdated or unrealistic plans. The comprehensively evaluated and adjusted rescue plan can promote the collaborative cooperation among emergency rescue units, avoid duplicate actions and resource waste. At the same time, by real-time correcting the task objective and path planning, each unit can better integrate resources and improve the overall rescue efficiency.

[0111] More specifically, by comprehensively analyzing the implementation value of multiple solutions, multiple emergency rescue options are provided for the command center to ensure the flexibility of command decisions. Such a decision support system can quickly make the optimal choice in case of emergency, avoid the decline of rescue effect caused by decision-making mistakes, and the real-time search information collection and model update keep the entire rescue system in a rapid response state. Each adjusted plan is the optimal choice based on the latest data, greatly improving the emergency response speed and rescue efficiency, and ensuring that the rescue operation can be completed as soon as possible.

[0112] Referring to Figure 2 As shown, in a second aspect, the present invention provides an emergency rescue system based on satellite positioning for implementing any one of the methods for emergency rescue based on satellite positioning in the first aspect, including: A satellite scheduling module, configured to obtain the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue units, and perform emergency scheduling on the positioning satellites reserved for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units; A data acquisition module, configured to perform satellite image acquisition and satellite signal connection on the emergency rescue area through the image positioning function and signal connection function of the emergency satellite units to obtain the satellite image data and signal connection data of the emergency rescue area; An actual situation simulation module, configured to perform multiple content analyses on the satellite image data and the signal connection data, including the landform where the emergency rescue units are located, the self-positioning relationship of the units, and the rescue target positioning relationship, and express the results of the multiple content analyses in the form of digital feedback to obtain an emergency rescue actual situation model; A rescue search module, configured to analyze the specific implementation plans of multiple search methods of each emergency rescue unit relative to the emergency rescue area according to the emergency rescue actual situation model to obtain multiple rescue plans for each emergency rescue unit; A continuous execution module, configured to send the multiple rescue plans to the corresponding emergency rescue units, instruct the emergency rescue units to perform the search work corresponding to the multiple rescue plans, obtain rescue search information and substitute it into the emergency rescue actual situation model to circularly analyze and execute the rescue plans of the emergency rescue units.

[0113] In this embodiment, for the specific implementation of each module in the above system embodiment, please refer to that described in the above method embodiment, and details will not be repeated here.

[0114] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An emergency rescue method based on satellite positioning, characterized in that, Including: Obtain the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue units, and perform emergency scheduling on the positioning satellites reserved for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units; Perform satellite image collection and satellite signal linking on the emergency rescue area through the image positioning function and signal linking function of the emergency satellite units to obtain the satellite image data and signal linking data of the emergency rescue area; Perform multiple content analyses on the satellite image data and the signal linking data, including the landform where the emergency rescue units are located, the self-positioning relationship of the units, and the rescue target positioning relationship, and express the results of the multiple content analyses in the form of digital feedback to obtain an emergency rescue actual situation model; Analyze the specific implementation plans of multiple search methods for each of the emergency rescue units relative to the emergency rescue area according to the emergency rescue actual situation model to obtain multiple rescue plans for each of the emergency rescue units; Send the multiple rescue plans to the corresponding emergency rescue units, instruct the emergency rescue units to execute the search work corresponding to the multiple rescue plans, obtain rescue search information and substitute it into the emergency rescue actual situation model to cyclically analyze and execute the rescue plans of the emergency rescue units.

2. The emergency rescue method based on satellite positioning according to claim 1, wherein The steps of obtaining the regional actual situation information of the emergency rescue area and the unit function information of the emergency rescue units, and performing emergency scheduling on the positioning satellites reserved for rescue according to the regional actual situation information and the unit function information to obtain a number of emergency satellite units include: Obtain the enclosed range data of the emergency rescue area, retrieve the associated regional topography map and regional path map from the specified geographical database according to the enclosed range data, and at the same time obtain the real-time meteorological information and emergency event information of the emergency rescue area, and perform real-time simulation on the regional topography map according to the real-time meteorological information and the emergency event information to obtain the regional actual situation information of the emergency rescue area; Obtain the unit function information of the emergency rescue units that are preparing to go to and have arrived at the emergency rescue area, and perform feature conversion on the unit function information for the executable rescue methods to obtain the overall rescue method features corresponding to each of the emergency rescue units; Obtain the satellite function information of the positioning satellites reserved for rescue, and perform feature conversion on the satellite function information of each positioning satellite for the positioning assistance method to obtain the satellite positioning assistance method features; Perform satellite positioning assistance requirement analysis on the overall rescue method features according to the regional actual situation information, and select auxiliary satellites according to the analysis results for the satellite positioning assistance method features to obtain a number of emergency satellite units; among them, the emergency satellite units include image positioning satellites and signal linking satellites.

3. The emergency rescue method based on satellite positioning according to claim 1, wherein The steps of performing satellite image collection on the emergency rescue area through the image positioning function of the emergency satellite units to obtain the satellite image data of the emergency rescue area include: Perform initial positioning task allocation on the image positioning satellite that is an emergency satellite unit to allocate the initial image collection task for the image positioning satellite; Instructing the image positioning satellite to perform task execution instruction analysis on the image acquisition initial task, so as to adjust and execute working parameters of the image positioning satellite according to the task execution instruction corresponding to the image acquisition initial task, thereby driving the image positioning satellite to perform image acquisition of the emergency rescue area at a first observation scale, and obtaining a regional observation framework obtained by splicing a plurality of satellite images at the first observation scale; Based on the regional observation framework, the working parameters of the image positioning satellite are further adjusted and executed so that the image positioning satellite collects images of the emergency rescue area at a second observation scale, and fills in the details of the regional observation framework according to the image collection results. This step is repeated to fill in the details of the regional observation framework according to the image collection results of more observation scales until the image collection of the initial image collection task is completed to obtain satellite image data.

4. The emergency rescue method based on satellite positioning according to claim 1, wherein The step of performing satellite signal linking on the emergency rescue area through the signal linking function of the emergency satellite unit to obtain signal linking data of the emergency rescue area comprises: Allocating an initial positioning task to a signal link satellite serving as an emergency satellite unit, so as to allocate a signal link initial task to the signal link satellite; The signal link satellite is instructed to perform task execution instruction analysis on the signal link initial task, and the working parameters of the signal link satellite are adjusted and executed according to the task execution instruction corresponding to the signal link initial task, so as to drive the signal link satellite to perform signal link work between the emergency rescue unit and the emergency rescue target in the emergency rescue area, so that each of the emergency rescue units and potential emergency rescue targets is in a signal link state with the signal link satellite; wherein the emergency rescue unit is a unit that is ready to perform emergency rescue work on the emergency rescue area, and the emergency rescue target is a smart terminal held by a subject waiting for rescue in the emergency rescue area; Perform signal positioning work based on the signal link status between the emergency rescue unit and the emergency rescue target to obtain signal positioning information between the emergency rescue unit and the emergency rescue target; Sending a surrounding environment positioning program to the emergency rescue unit and the emergency rescue target through the signal link state with the emergency rescue unit and the emergency rescue target, so that the emergency rescue unit and the emergency rescue target can execute the surrounding environment positioning program, and the emergency rescue unit and the emergency rescue target can obtain surrounding environment image data by executing the surrounding environment positioning program to realize self-positioning based on the surrounding environment and obtain self-positioning information; The signal positioning information of each of the emergency rescue units and the emergency rescue target and the self-positioning information together constitute the signal link data.

5. The emergency rescue method based on satellite positioning according to claim 4, characterized in that The steps of performing multiple content analysis on the satellite image data and the signal link data, including the topography of the emergency rescue unit, the unit's self-positioning relationship, and the rescue target's positioning relationship, and expressing the results of the multiple content analysis in the form of digital feedback to obtain the emergency rescue real-time model include: Perform three-dimensional digital modeling on the emergency rescue area based on the satellite image data to obtain a regional basic model; Based on the signal positioning information and self-positioning information of each emergency rescue unit and the emergency rescue target in the signal link data, perform double-level positioning node conversion and positioning node connection for each emergency rescue unit and the emergency rescue target to obtain a positioning node topology network constructed by a number of interconnected positioning nodes; wherein, the positioning node topology network is used to describe the unit self-positioning relationship and rescue target positioning relationship between the emergency rescue unit and the emergency rescue target; Perform positioning verification and node deployment on the positioning node topology network based on the regional basic model to deploy the positioning node topology network to the regional basic model, and perform in-depth detailed three-dimensional modeling on the part of the regional basic model where positioning nodes are deployed according to the satellite image data to obtain an emergency rescue actual situation model.

6. The emergency rescue method based on satellite positioning according to claim 1, wherein The steps of analyzing the specific implementation plan of multiple search methods for each emergency rescue unit relative to the emergency rescue area based on the emergency rescue actual situation model to obtain multiple rescue plans for each emergency rescue unit include: According to the unit function information of each emergency rescue unit, simulate the movement path of the emergency rescue unit and the coverage area of multiple search methods on the emergency rescue actual situation model to obtain the expected search feature distribution of each emergency rescue unit; wherein, the expected search feature distribution includes a number of expected search features, and the expected search feature is used to describe the area that the emergency rescue unit can cover when using a specified search method on a specified movement path, and the search methods include machine vision search, sound broadcast search, microwave radar search, and signal matching search; Perform predictive analysis of potential emergency rescue targets on the emergency rescue actual situation model using a machine learning model trained based on historical data to assign potential values of emergency rescue targets to specific locations on the emergency rescue actual situation model; Take the positioning information of each known emergency rescue target in the emergency rescue actual situation model as the first task target, take the potential value of the emergency rescue target assigned to each specific location of the emergency rescue actual situation model as the second task target, and perform comprehensive analysis and task allocation of the first task target and the second task target on the emergency rescue actual situation model according to the expected search feature distribution of each emergency rescue unit to obtain the expected search path and expected search task of each emergency rescue unit; Combine the expected search paths and expected search tasks of the emergency rescue unit to obtain a multiple rescue plan for the emergency rescue unit.

7. The emergency rescue method based on satellite positioning according to claim 1, wherein The steps of issuing the multiple rescue plan to the corresponding emergency rescue unit, instructing the emergency rescue unit to perform the search work corresponding to the multiple rescue plan, obtaining rescue search information and substituting it into the emergency rescue actual situation model to circularly perform the rescue plan analysis and execution of the emergency rescue unit include: Sending the multiple rescue plans to corresponding emergency rescue units, driving the emergency rescue units to go to the specified expected search paths in sequence according to the multiple rescue plans, and executing the expected search tasks through the specified search methods to obtain rescue search information; Substituting the rescue search information obtained by each of the emergency rescue units into the emergency rescue real-time model to perform real-time corrections on the model parameters of the emergency rescue real-time model, and analyzing the reference value of continuing to execute the multiple rescue plans of each of the emergency rescue units based on the real-time corrected emergency rescue real-time model to obtain the reference value of continuing to execute the multiple rescue plans; According to the emergency rescue real-time model, multiple rescue plans of each of the emergency rescue units are simulated and adjusted, and their execution value is evaluated to obtain the adjusted rescue plans of each of the emergency rescue units and the adjusted execution reference value corresponding to the adjusted rescue plans; A comprehensive assessment is performed on the continued execution reference value of each of the multiple rescue plans and the adjusted execution reference value of each of the adjusted rescue plans to determine the subsequent rescue plan of the emergency rescue unit.

8. An emergency rescue system based on satellite positioning, characterized in that, A satellite positioning-based emergency rescue method for implementing any one of claims 1 to 7, comprising: A satellite dispatching module is used to obtain the regional real-time information of the emergency rescue area and the unit function information of the emergency rescue unit, and perform emergency dispatch on the positioning satellites prepared for rescue according to the regional real-time information and the unit function information to obtain a number of emergency satellite units; A data acquisition module, used to acquire satellite images and link satellite signals of the emergency rescue area through the image positioning function and signal link function of the emergency satellite unit, so as to obtain satellite image data and signal link data of the emergency rescue area; A real-time simulation module is used to perform multiple content analysis on the satellite image data and the signal link data, including the terrain where the emergency rescue unit is located, the unit's self-positioning relationship, and the rescue target's positioning relationship, and to express the results of the multiple content analysis in the form of digital feedback to obtain a real-time emergency rescue model; A rescue search module, used for analyzing the specific implementation scheme of the multiple search modes for each of the emergency rescue units relative to the emergency rescue area according to the emergency rescue real-time model, so as to obtain multiple rescue schemes for each of the emergency rescue units; The continue execution module is used to send the multiple rescue plans to the corresponding emergency rescue units, order the emergency rescue units to perform the search work corresponding to the multiple rescue plans, obtain the rescue search information and substitute it into the emergency rescue real-time model, so as to cyclically perform the rescue plan analysis and execution of the emergency rescue units.

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