Simulation analysis method for aviation rescue task of maritime search and rescue

Abstract

The invention relates to the technical field of safety rescue, in particular to an aviation rescue task simulation analysis method for maritime search and rescue, which comprises the following steps: acquiring input information of an aviation rescue task, acquiring a task area based on the input information, determining rescue equipment, and determining a detection mode and a search track of search simulation analysis. Determining a rescue mode of rescue simulation analysis; deploying rescue equipment in the task area, and based on execution of the search simulation analysis, if an object in distress is found in the search process, executing rescue simulation analysis in the rescue mode; obtaining result data of search and rescue simulation analysis, and generating effect indexes including a success rate index and a time index; the simulation analysis method can adapt to complex search and rescue environments and improve the accuracy and the collaboration of simulation analysis.

Description

Technical Field

[0001] This invention relates to the field of safety rescue technology, specifically to a simulation analysis method for aviation rescue missions in maritime search and rescue. Background Technology

[0002] In maritime rescue operations, aerial search and rescue plays a crucial role. However, current maritime aerial search and rescue faces numerous challenges. On the one hand, the maritime environment is complex and changeable, with weather conditions (such as strong winds, heavy rain, and low visibility) and sea conditions (wave height and currents) significantly impacting search and rescue efficiency and success rates. On the other hand, existing search and rescue technologies lack precision and efficiency in mission planning and execution. Traditional search and rescue decisions often rely on experience, making it difficult to fully consider the impact of various complex factors on the search and rescue mission, leading to resource waste and rescue delays. Furthermore, different types of aerial search and rescue equipment lack a systematic and effective coordination mechanism in practical applications, failing to fully leverage their advantages.

[0003] In some past maritime search and rescue operations, inaccurate target location predictions have led to aircraft spending extended periods searching in the wrong areas, consuming large amounts of fuel and missing optimal rescue opportunities. Furthermore, in some search and rescue missions, poor information transmission between different pieces of equipment has hindered efficient collaborative operations. Therefore, it is essential to develop a simulation analysis method for maritime aerial search and rescue missions that can comprehensively consider multiple factors and achieve accurate mission planning and efficient collaboration. Summary of the Invention

[0004] In view of the above problems, the present invention provides a simulation analysis method for aviation rescue missions in maritime search and rescue, which solves the technical problems in the prior art that it is difficult to consider the complexity of the environment and make accurate and collaborative decisions during simulation analysis.

[0005] This invention provides a simulation analysis method for aviation rescue missions in maritime search and rescue, including step S1: acquiring input information for the aviation search and rescue mission, including the type of distressed object, approximate location, meteorological information, and time information; Step S2: Based on the input information, obtain the mission area, determine the rescue equipment, determine the detection mode and search trajectory for search simulation analysis, and determine the rescue method for rescue simulation analysis; Step S3: Deploy rescue equipment in the mission area, determine multiple search and rescue plans based on the detection mode, search trajectory, survival model of the person who fell into the water, and aircraft fuel consumption model, and perform the search simulation analysis. If the distressed object is found during the search process, perform rescue simulation analysis in accordance with the rescue method. Step S4: Obtain the results data of search and rescue simulation analysis of multiple search and rescue plans, generate effect indicators, and determine the optimal search and rescue plan based on the effect indicators of each search and rescue plan.

[0006] Preferably, step S1 includes: obtaining the type and approximate location of the distressed object based on input from the user interface, and obtaining the meteorological information based on input from the user interface or a meteorological data source.

[0007] Preferably, in step S2, the step of obtaining the task area specifically includes: obtaining multiple possible drift trajectories based on the rough position and time information in the input information; and expanding the rough position based on the multiple possible drift trajectories to form the task area.

[0008] Preferably, the step of forming the task region includes: calculating the convex hull of multiple points on multiple possible drift trajectories; for each edge of the convex hull, obtaining the farthest point, the parallel limit point, and the vertical limit point to determine multiple candidate bounding rectangles; and determining the candidate bounding rectangle with the smallest area as the task region.

[0009] Preferably, in step S2, the step of determining the rescue equipment specifically includes: The rescue equipment is determined according to the type of distressed object, and the rescue equipment includes a single helicopter, a helicopter formation, and helicopter and ship coordination. The steps for determining the detection mode and search trajectory in the search simulation analysis specifically include: The search simulation analysis determines the detection mode based on the type of distressed object and meteorological information; The search track is selected based on the shape of the mission area, the type of distressed object, and meteorological information. The search track includes parallel line search, lateral line search, extended rectangle search, fan shape search, and contour line search. The steps for determining the rescue method in the rescue simulation analysis specifically include: The rescue method is determined based on the type of distressed object and meteorological information, and the rescue simulation analysis is used to determine the rescue method.

[0010] Preferably, in step S3, the step of determining multiple search and rescue plans based on the detection mode, search trajectory, survival model of the person who fell into the water, and aircraft fuel consumption model, and performing the search simulation analysis specifically includes: The target detection probability is obtained based on the detection mode; The survival model for people who fall into the water determines the survival time of a person after falling into the water based on prior statistical information, and then compares the time when the aircraft arrives at the location of the person who fell into the water with the survival time to determine whether the person has survived. The aircraft fuel consumption model determines the aircraft's maximum range based on the fuel consumption rate; Multiple search and rescue plans are randomly generated, each with different rescue equipment, detection modes, search tracks, and rescue methods; For each search and rescue plan, a search simulation analysis is performed based on the target discovery probability, search trajectory, maximum range, and whether personnel survived, to determine whether the distressed object can be found. Preferably, the step of obtaining the target detection probability based on the detection mode specifically includes: The detection modes include visual search, radar detection, and photoelectric detection; For visual search mode, the target detection probability is obtained based on the distance relationship between the aircraft and the target. For radar detection mode, the initial radar detection probability is obtained by inputting radar performance parameters and calculation process parameters. Based on the input visibility data, the initial radar detection probability is corrected to obtain the final target detection probability of radar detection that takes into account environmental factors. For photoelectric detection mode, the solid angle occupied by the target in the system's field of view is determined based on the input photoelectric performance parameters and target and environmental parameters. The signal-to-noise ratio of the target and background noise is calculated, and the target detection probability of photoelectric detection is determined by the signal-to-noise ratio.

[0011] Preferably, in step S3, the step of performing rescue simulation analysis in the rescue method specifically includes: The rescue methods include rappelling rescue, helicopter descent rescue, water landing rescue, airdrop rescue, and aerial hoisting rescue; For rappelling rescue, input rappelling parameters and sea state parameters, determine different sea state influence factors for different visibility, and finally calculate the rescue duration and number of rescuers. For air-drop rescue, input the number of people to be transferred and the maximum passenger capacity of the aircraft, determine the number of round trips, distinguish between primary and subsequent transport, and record the data of multiple round trips to obtain the rescue duration and the number of people rescued. For water rescue, input sea state parameters to obtain data on aircraft flight and lifeboat movement after water landing, and obtain the rescue duration and number of people rescued; For airdrop rescue, the difference between wind resistance and descent speed is taken into account to calculate the rescue duration corresponding to the descent of supplies. For aerial hoisting rescue, input the number of personnel to be hoisted and the hoisting height parameters to calculate the rescue duration and the number of people to be rescued throughout the entire hoisting process.

[0012] Preferably, step S4 includes: Based on the results of search and rescue simulation analysis of multiple search and rescue plans, effectiveness indicators are generated, including search process efficiency, rescue process efficiency, and transportation process efficiency. The effectiveness indicators are weighted to obtain a comprehensive score, and the search and rescue plan with the highest comprehensive score is determined as the optimal search and rescue plan.

[0013] Compared with the prior art, the present invention has at least the following beneficial effects: (1) This invention introduces a variety of task elements and environmental parameters. After obtaining the input information, the logical architecture of the maritime search mission is divided into three parts: input, task plan generation, and output. The mission execution process includes two stages: search and rescue. By introducing a drift trajectory model and a search area generation model, the search and rescue mission area is determined, which improves the accuracy of the search and rescue mission. By introducing a survival model for people who have fallen into the water and an aircraft fuel consumption model, the search simulation analysis is made more in line with the actual situation.

[0014] (2) The simulation analysis process of this invention can enhance the coordination capabilities between different rescue equipment. It clarifies the cooperation modes under various equipment combinations, such as single-unit operation, formation operation, and helicopter-ship cooperation. Based on different rescue methods, such as rappelling, helicopter landing, water landing, airdrop, and aerial hoisting, corresponding rescue process models are constructed, and simulation analysis is conducted on the operation procedures, required time, and number of people that can be rescued for each type of rescue method. This improves the efficiency of equipment collaborative operations in complex tasks and solves the problem of coordination chaos caused by unclear task methods and inconsistent execution processes in existing simulation methods.

[0015] (3) Through detailed simulation of the search and rescue process, this invention has developed multi-dimensional quantitative indicators, including mission preparation time, average search and rescue time, total flight time, and rescue success rate, which significantly improves the scientific nature of decision-making. Based on these simulation data, dynamic optimization of air search and rescue resources can be achieved, flight missions and manpower scheduling can be rationally arranged, and operating costs can be reduced. Attached Figure Description

[0016] The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of the invention.

[0017] Figure 1 The diagram illustrates the steps of the simulation analysis method for maritime search and rescue aviation rescue missions provided by this invention.

[0018] Figure 2 The diagrams provided by this invention illustrate parallel lines, horizontal lines, extended squares, and sector-shaped search trajectories.

[0019] Figure 3 This is a cross-sectional view of a typical water rescue operation provided by the present invention.

[0020] Figure 4 This is a schematic diagram of a single-machine task provided by the present invention.

[0021] Figure 5 This is a schematic diagram of a formation task provided by the present invention.

[0022] Figure 6 This is a schematic diagram of the system task provided by the present invention.

[0023] Figure 7 This is a schematic diagram of a ship-machine collaborative task provided by the present invention. Detailed Implementation

[0024] To better understand the above-described objectives, features, and advantages of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other. Furthermore, the present invention can be implemented in other ways different from those described herein; therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0025] This invention addresses the organizational structure and operational relationships of various forces within frontline domestic air search and rescue units. It analyzes air search and rescue procedures, organizational methods, and equipment usage patterns, taking into account mission requirements and typical scenarios. Multiple operational processes are categorized at the mission and system levels. Furthermore, various simulation models for air search and rescue missions are established based on the working characteristics and mission load performance of different types of air search and rescue equipment. This provides theoretical and technical support for the application simulation and verification research of air emergency rescue equipment systems.

[0026] like Figure 1 As shown, a simulation analysis method for aviation rescue missions in maritime search and rescue is disclosed, including the following steps: Step S1: Obtain input information for the air search and rescue mission, including the type of distressed object, approximate location, weather information, and time information.

[0027] This invention divides the aerial search and rescue mission for maritime targets into three parts: acquiring input information, generating mission plans, and outputting performance indicators. In this step, the first step is to acquire the input information for the simulation analysis of the aerial search and rescue mission for maritime targets. This input information may include the type of distressed object, its approximate location, and meteorological information.

[0028] The distress object type indicates the category of the object currently requiring rescue, which can be a person in the water, a vessel, or a life raft, etc. Different distress object types will be assigned corresponding rescue equipment and detection modes in subsequent steps. The approximate location of the distress object indicates the general location of the distressed person or vessel. The meteorological information may include ocean current data and wind field data, representing the current meteorological conditions in the rescue environment.

[0029] In some embodiments, the distressed object type and approximate location can be obtained through various methods such as manual input, automatic reception of distress signals, and access to a disaster monitoring system. The integrated meteorological information sources can be based on multiple data sources such as meteorological forecasting systems, marine environmental monitoring systems, geographic information systems, and sensor networks, obtained through automated collection. The system may also include data preprocessing and format conversion steps, cleaning, correcting, and converting the collected meteorological information to ensure its effective use by subsequent models.

[0030] The time information includes the time when the distressed object was discovered, the duration of the distress from its occurrence to the present, and other information. Step S2: Based on the rough location, obtain the mission area, determine the rescue equipment, determine the detection mode and search trajectory for search simulation analysis based on the type of distressed object and meteorological information, and determine the rescue method for rescue simulation analysis. In this step, a task plan including search and rescue simulation analysis is generated based on the input information. The specific steps are described below.

[0031] First, the approximate location of the distressed personnel or vessel is expanded to form the task area, and subsequent task plans are implemented within this task area.

[0032] In some embodiments, the present invention invokes a personnel drift trajectory model and a search area generation model to expand the region and form the task area. The personnel drift trajectory model obtains multiple possible drift trajectories based on information such as the approximate location and the duration of the incident, and the search area generation model expands the approximate location based on the multiple possible drift trajectories to form the task area.

[0033] The drift trajectory model employs a Monte Carlo-based ocean drift model, specifically a model that considers both drift caused by current pressure and drift caused by wind pressure to account for the drift of people and objects falling into the water. The calculation of the drift model for people and objects falling into the water is primarily achieved by simulating the motion trajectory of these individuals and objects in the ocean. This model comprehensively considers the influence of factors such as wind and ocean currents on the position of people and objects falling into the water.

[0034] The search area generation model, namely the maritime search and rescue rectangular search area model, calculates and determines the smallest rectangular search area containing a given set of latitude and longitude coordinates. The model input is a series of drift trajectory points of the person who fell into the water. The model calculation is mainly based on the minimum enclosing rectangle algorithm to obtain the minimum rectangular range surrounding the drift trajectory of the person who fell into the water.

[0035] In some embodiments, the search region generation model can calculate the convex hull of multiple points on the drift trajectory using OpenCVSharp. Then, for each edge of the convex hull, multiple candidate bounding rectangles are determined by finding the farthest point and the parallel / perpendicular limit points. Finally, the smallest bounding rectangle is selected from all candidate rectangles as the minimum bounding rectangle, thereby delineating the task region.

[0036] The rescue equipment of the present invention is then determined, including: a single helicopter, a helicopter formation, and helicopter and ship coordination, etc.

[0037] In some embodiments, the rescue equipment can be determined according to the type of distressed object. For example, a single helicopter can be used when there is a single distressed person, a helicopter formation can be used when there are many distressed persons, and ship-to-ship coordination can be used when a ship or life raft is in distress.

[0038] In some embodiments, the type of distressed object and meteorological information determine the detection mode for search simulation analysis. The detection modes of the present invention include visual search, radar detection, and photoelectric detection.

[0039] The search tracks described in this invention include: parallel line search, lateral line search, extended rectangle search, fan-shaped search, and contour line search methods, etc.

[0040] In some embodiments, search tracks can be selected based on the shape of the mission area, the type of distressed object, and weather information. For example, when the search area is large and rectangular or square, parallel line search or lateral line search can be used to achieve uniform coverage; when the target location is relatively certain, but the distressed object may have drifted slightly, an extended rectangular search extending outward from the reference point can be used; if the target location is very certain and the search area is small, and a single aircraft or helicopter is used, a fan-shaped search can be used to quickly cover high-probability areas near the reference point; and when the search area is along a coastline, island edge, or specific terrain features (such as mountains), a contour line search can be used. One or more of the above-mentioned tracks can be selected manually or automatically when acquiring search tracks.

[0041] The rescue methods described in this invention include models for rappelling rescue, air assault rescue, water landing rescue, airdrop rescue, and aerial hoisting rescue. The models of the above rescue methods simulate the rescue based on information about sea conditions and visibility in meteorological information, as well as information about the fuel consumption and flight time of the rescue equipment, and obtain information on the number of people rescued, the rescue time, and other effects.

[0042] In some embodiments, the rescue method can be determined based on the type of distressed object and meteorological information in the rescue simulation analysis. Through the above steps, the present invention determines the task scheme for search and rescue simulation analysis, which is used for subsequent simulation execution of the task scheme.

[0043] Step S3: Deploy rescue equipment in the mission area, determine multiple search and rescue plans based on the detection mode, search trajectory, survival model of the person who fell into the water, and aircraft fuel consumption model, and perform the search simulation analysis. If the distressed object is found during the search process, perform rescue simulation analysis in accordance with the rescue method. Based on the task area determined in step S2 and the rescue equipment, the present invention randomly generates multiple search and rescue plans based on the survival model of the person who fell into the water and the aircraft fuel consumption model, and performs the search simulation analysis for each search and rescue plan.

[0044] Multiple search and rescue plans are randomly generated, each with different rescue equipment, detection modes, search tracks, and rescue methods; For each search and rescue plan, the survival model for people who have fallen into the water determines the survival time of a person after falling into the water based on prior statistical information, and then compares the time when the aircraft arrives at the location of the person who fell into the water with the survival time to determine whether the person has survived.

[0045] The aircraft fuel consumption model is divided into a helicopter fuel consumption model and an amphibious fixed-wing aircraft fuel consumption model. Based on data such as fuel consumption curves in the flight manual, the model fits a fuel consumption function that reflects the aircraft's fuel consumption rate as a function of different variables (temperature, altitude, weight). Using this fuel consumption function, and inputting real-time flight data (temperature, altitude, weight), the real-time fuel consumption rate can be obtained. Then, the total fuel consumption for each flight segment can be calculated based on the flight time.

[0046] The present invention searches using the detection modes determined in the aforementioned steps. The detection modes of the present invention include visual search, radar detection, and photoelectric detection, as described in detail below.

[0047] The visual search mode models the visual search of helicopters, inputting data such as the distance between the helicopter and the target, visibility, wave height, and target type. It selects a visual model based on the distance relationship between the aircraft and the target, and obtains the target discovery probability of the visual search based on the visual model.

[0048] The radar detection mode models radar detection by inputting radar performance parameters and calculation process parameters, obtaining the minimum detectable signal, and then obtaining the preliminary radar detection probability. Based on the input visibility data, the preliminary radar detection probability is corrected to obtain the final target detection probability that takes environmental factors into account.

[0049] The photoelectric detection mode models photoelectric and infrared detection, determines the solid angle occupied by the target in the system's field of view based on the input system performance parameters and target and environmental parameters, and then calculates the signal-to-noise ratio of the detector pixel to the target signal and background noise. The signal-to-noise ratio is then substituted into the relationship between the signal-to-noise ratio and the detection probability to determine the target detection probability of photoelectric detection.

[0050] The present invention searches using the search tracks described in the aforementioned steps. Figure 2 These are schematic diagrams of parallel line search models, lateral line search models, extended square search models, and sector search models. This invention plans a trajectory based on the boundary corner points of the task area, performs straight-line movement, turning, and other operations, and searches according to the planned trajectory.

[0051] If the search simulation analysis finds a distressed object, then a rescue simulation analysis is performed using the rescue method described above. The models for different rescue methods are described in detail below.

[0052] The rappelling rescue model calculates the time required for rescue by inputting parameters such as rappelling height, rappelling speed, visibility, and sea state. It determines sea state influencing factors based on sea state, for example, setting a specific value for sea state between 0 and 3, and a specific value for visibility between 3 and 6 nautical miles. Finally, it calculates the rescue duration and the number of people to be rescued using the rappelling time formula.

[0053] Airborne rescue model: Based on the number of people to be transferred and the maximum passenger capacity of the aircraft, the number of round trips required to complete the entire transportation mission is calculated by rounding up. Within each flight mission, distinguishing between the initial transport and subsequent transports, multiple round trips are recorded to obtain information such as the rescue duration and the number of people rescued.

[0054] Amphibious aircraft water rescue model: such as Figure 3 As shown, after the aircraft arrives at the mission area, it searches according to a preset search path. Upon locating the target, it selects a suitable body of water for a water landing, taking into account wind force, waves, and ocean current direction. After landing, the aircraft can approach the person in distress via its onboard lifeboat, or approach and rescue them by gliding on the water or by swimming. The landing and rescue simulation analysis records the time taken, obtaining information such as the rescue duration and the number of people rescued.

[0055] Airdrop rescue model: There are two airdrop methods: no parachute and parachute. The differences in wind resistance and descent speed are considered respectively to calculate the rescue duration corresponding to the descent of supplies.

[0056] Aerial hoisting model: By inputting parameters such as the number of personnel to be hoisted, hoisting height, and ascent and descent speeds, the model calculates information such as the rescue duration and the number of people to be rescued during the entire hoisting process.

[0057] In some embodiments, after the rescue is completed, a medical evacuation process is also included, in which the rescuers are sent to the corresponding resettlement point or hospital according to the type of the rescued persons, such as missing persons, injured persons, or persons requiring resettlement, and the evacuation time and number of persons evacuated are obtained.

[0058] Step S4: Obtain the results data of search and rescue simulation analysis of multiple search and rescue plans, generate effect indicators, and determine the optimal search and rescue plan based on the effect indicators of each search and rescue plan.

[0059] After completing the search and rescue simulation analysis of the mission plan, the execution result data of the search and rescue simulation analysis are obtained, and performance indicators are generated. These performance indicators include search process efficiency, rescue process efficiency, and transportation process efficiency. Table 1 shows the meaning of the indicators reflecting the performance of the search and rescue mission.

[0060] Table 1

[0061] Table 2 shows the weights of each evaluation indicator.

[0062] Table 2

[0063] When scoring the simulation plan, the lower bound of the simulation plan needs to be determined first. The method for determining the lower bound is as follows: assume that the distressed personnel can be found without searching once the aircraft arrives at the mission area, that is, there is no distressed personnel search process. When there are multiple distressed personnel, they are treated as if there is only one distressed personnel, that is, all distressed personnel are found at the same location simultaneously. Based on the above, the simulation plan only has the stages of traveling to the mission area, rescuing distressed personnel, and medical evacuation, and the lower bounds of each indicator in the simulation plan are determined accordingly.

[0064] The task plan was simulated and the values ​​of each indicator were obtained. Due to the different units of the original indicator values, there is a problem with adding the indicators. Therefore, it is necessary to process the original indicator values ​​to obtain summable evaluation indicator values. In this report, the original indicator values ​​are compared with the lower bound values ​​to obtain the evaluation indicator values. The processed data is located in the range [0, 100]. The indicator data processing formula used is as follows:

[0065] in, For the first The evaluation value of each indicator, The original value, This is the lower bound value.

[0066] The above eight indicators are divided into two categories: positive indicators and negative indicators, as shown in Table 3.

[0067] Table 3

[0068] The processed indicator is multiplied by its corresponding weight, and these weighted indicators are then summed to obtain the overall score. The calculation formula is as follows:

[0069] Where z is the overall score of the performance indicators. For the first The weight of each indicator, For the first Evaluation values ​​of each indicator.

[0070] 1) Search process efficiency (1) Search time for target I21 (contrarian indicator) This metric represents the time from when an aircraft arrives at the mission area to when the distressed target is located. The time taken to search for a target is an important aspect of assessing search and rescue capabilities. A sound search strategy includes the selection of search patterns, the planning of search areas and search routes, so as to locate the distressed target in the shortest possible time.

[0071] [Original Value]: When the aircraft performs a mission, the timer starts when it begins searching for a target. The total time taken to search for the target is the value of the target search time index.

[0072] [Lower Bound]: Calculates the straight-line distance d between the aircraft and the target when the aircraft enters the mission area, and the time it takes for the aircraft to travel to the target location in a straight line.

[0073]

[0074] in, This indicates the straight-line distance between the aircraft and the target when the aircraft enters the mission area. This indicates the speed of the aircraft search.

[0075] (2) Search coverage I22 (positive indicator) This metric represents the search coverage rate when an aircraft is performing a search and rescue mission.

[0076] When an aircraft completes a search, a calculation is triggered. If no target is found, the coverage rate is 1. If a target is found, the ratio of the search route to the total search route is calculated, which is the current coverage rate.

[0077] This metric does not require normalization; the search coverage rate is:

[0078] 2) Efficiency of the rescue process (1) Time taken to rescue target I31 (reverse indicator) This indicator represents the time from when an aircraft lands on water to when it completes a rescue and takes off again. The water rescue time reflects the amphibious aircraft's rescue capability; once a distressed target is located, the personnel in distress should be rescued and brought onto the aircraft as quickly as possible. At the same time, it is also disadvantageous for the amphibious aircraft itself to remain on the sea surface for an extended period of time.

[0079] [Original Value] Rescue operations begin once the aircraft reaches the vicinity of the target, and timing starts. Timing stops once the person who fell into the water is rescued and boarded the aircraft. This duration is the time taken to reach the rescue target.

[0080] [Lower Boundary Value] The ideal rescue time per person is 3 minutes. The lower bound value of this indicator is the number of people multiplied by 3 minutes.

[0081]

[0082] in, This indicates the total number of people awaiting rescue.

[0083] (2) Success rate of rescue I32 (positive indicator) This indicator represents the proportion of people successfully rescued by aircraft out of the total number of people in distress.

[0084] If the target is found and rescue operations are carried out within the longest waiting time for the distressed personnel, the rescue rate is 1; otherwise, the value is 0.

[0085] This indicator does not require normalization; the rescue success rate is:

[0086] (3) Onboard rescue capability I51 (positive indicator) This indicator is used to represent the onboard medical treatment capabilities of amphibious aircraft, and it does not require normalization.

[0087]

[0088] 3) Transportation process efficiency (1) Aircraft departure time I11 (reverse indicator) This indicator represents the time from receiving a search and rescue mission to arriving at the mission area, including pre-flight preparations and support operations. It reflects the aircraft's rapid deployment capability and is part of its support capability. The aircraft's deployment time determines when it can begin searching, which is crucial for the success of the search and rescue mission. On the one hand, due to drift effects, the location of the distressed target gradually deviates from its initial position, and the accuracy of drift prediction decreases over time, further increasing the difficulty of the search. On the other hand, the survival time of distressed personnel, especially those who have fallen into the water, is limited, requiring search and rescue forces to arrive at the mission area as quickly as possible.

[0089] [Original value]: When the aircraft receives the rescue information, the timer starts and stops when the aircraft reaches the mission search area. This time is the aircraft's departure time.

[0090] [Lower Bound]: Time taken for the aircraft to reach the search area while flying in a straight line.

[0091] in, This indicates the aircraft's cruising speed; the data is sourced from the flight manual.

[0092] (2) Flight return time I12 (reverse indicator) This indicator represents the time it takes for an aircraft to take off from the water and arrive at its destination airport, reflecting the aircraft's ability to quickly transfer people in distress. The return flight time determines when people in distress can receive further medical treatment. Although large amphibious aircraft have the capability to provide initial medical treatment, for critically ill people in distress, especially in the mid-to-long-range maritime search and rescue missions discussed in this article, they should be able to quickly reach shore-based facilities so that other rescue forces can subsequently transport the injured to hospitals.

[0093] [Original value]: The timer starts when the aircraft takes off after completing the rescue of personnel and ends when the aircraft returns to the base. This duration is the aircraft's return trip time.

[0094] [Lower Boundary]: The time it takes for the aircraft to return by flying in a straight line.

[0095]

[0096] (3) Wave resistance level I41 (positive indicator) Because water landing rescue is constrained by sea conditions, a wave resistance rating index is introduced. This index represents the maximum sea state level at which amphibious aircraft can land for rescue.

[0097] [Original Value] Wave Resistance [Lower Boundary Value] 2m The generated performance indicators will be used to determine the optimal search and rescue plan based on the performance indicators of each plan.

[0098] After completing the search and rescue simulation analysis, the execution result data of the search and rescue simulation analysis are obtained, and the comprehensive score z of the effect index is generated. The search and rescue plan with the highest comprehensive score z is determined as the optimal search and rescue plan.

[0099] This invention constructs a comprehensive and accurate simulation model to achieve precise simulation of maritime air search and rescue missions, providing a scientific basis for mission planning, resource allocation, and decision-making, thereby improving the efficiency and success rate of maritime air search and rescue.

[0100] To illustrate the effectiveness of the method proposed in this invention, the above technical solution of this invention will be described in detail below through specific embodiments.

[0101] Example 1 This embodiment demonstrates the specific simulation analysis process of near-shore rescue missions.

[0102] Based on the three search targets—personnel, life rafts, and vessels—the logical architecture of the maritime search mission is divided into three parts: input, mission plan generation, and output. Specifically, the mission execution process is divided into two phases: search and rescue. After receiving mission information about personnel or vessels in distress, the system collects ocean current data and wind field data, calls a drift model, calculates the location of the distressed personnel and vessels, and generates a mission area. Then, depending on the target being searched, the system can select the mission payload of rescue equipment or use visual methods to search for the target. It then matches and corrects the search trajectory and discovery probability based on meteorological data. In the search simulation analysis, it calls the survival model for people in the water and the aircraft fuel consumption model. If the target is found, the rescue model is used to carry out rescue and evacuation, after which the mission ends. If the target is not found, the mission needs to be terminated based on conditions such as the search end time. After the mission ends, the system outputs data such as identification success rate, mission success rate, personnel survival rate, mission preparation time, average search time, average rescue time, and total flight time.

[0103] Example 2 This embodiment demonstrates the specific simulation analysis process of a deep-sea rescue mission.

[0104] The operational logic of offshore search and rescue missions is similar to that of near-shore missions. Based on three types of search targets, the logical architecture of maritime search missions is divided into three parts: input, mission plan generation, and output. The main difference lies in the rescue phase of the mission execution. In offshore search and rescue missions, after the rescue target is located, depending on weather and wave conditions, two methods will be chosen: water rescue or airdropping rescue supplies. If conditions permit, water rescue will be used, deploying a lifeboat or having rescuers directly rescue and evacuate the target. If the target is not found, the mission needs to be terminated based on factors such as the search end time. After the mission concludes, the output will include data such as identification success rate, mission success rate, personnel survival rate, mission preparation time, average search time, average rescue time, and total flight time.

[0105] Example 3 This embodiment demonstrates the simulation analysis process for various detection modes, including: (1) Helicopter visual search and detection model: Input data such as the distance between the aircraft and the person in the water, visibility, wave height, and target type into the model. After obtaining these input parameters, the model first determines the distance between the aircraft and the target. If the distance is within 2km, the corrected visual model is selected; if the distance is greater than 2km, it is determined whether it exceeds the range of 3.5km for small targets, 5km for medium targets, and 10km for large targets. If it exceeds the range, the detection probability is set to 0; if it does not exceed the range, the uncorrected visual model is selected. For the uncorrected visual model, the detection probability is determined according to different target types (person in the water, life raft, ship), according to the corresponding detection probability and distance relationship table (e.g., the detection probability of a small target at a distance of 0.2km is 0.98), combined with the actual distance of the target. For the corrected visual model, the corresponding distance correction parameter is selected based on the visibility data (e.g., when the visibility is 3km, the distance correction parameter r13 = 4.375 for a small target), and the probability correction value is determined based on the sea state (e.g., when the small target is in sea state 2, the probability correction value e12 = -10). Combining these parameters, the probability of target detection is calculated according to the corrected formula.

[0106] (2) Radar Detection Model: Input radar performance parameters (such as theoretical detection range, theoretical target radar cross-sectional area, etc.) and calculation process parameters (actual distance, actual target radar cross-sectional area, visibility, etc.). Calculate the received signal power according to the radar equation and determine whether the received signal power is greater than the minimum detectable signal. If it is greater, the radar can detect the target. Obtain the maximum radar detection range through the minimum detectable signal, and then calculate the radar detection probability using the ratio method. In the specific calculation process, the radar detection probability is derived through a series of formulas based on parameters such as theoretical false alarm probability, actual false alarm probability, theoretical detection range, actual distance, theoretical target radar cross-sectional area, and actual target radar cross-sectional area. Finally, based on visibility data, select an appropriate weather correction factor from the visibility and weather correction factor correspondence table to correct the radar detection probability, obtaining the final radar target detection probability.

[0107] (3) Photoelectric (Infrared) Detection Model: Input photoelectric (infrared) performance parameters (optical system entrance pupil diameter, detectivity, etc.) and calculation process parameters (detection target brightness, detection target area, etc.). First, calculate the solid angle of the system to the target, and then obtain the response voltage of the pixel to the detection target and background noise. Calculate the signal-to-noise ratio (SNR) through the difference between the two response voltages. Based on the relationship between the false alarm probability and the detection probability, and given the false alarm probability, calculate the threshold level T corresponding to the minimum SNR using the Neyman-Pearson criterion. Calculate the infrared detection probability using the formula relating the SNR and the detection probability. In the actual calculation process, the parameters are interrelated. For example, parameters such as the optical system entrance pupil diameter and the target detection distance affect the calculation of the solid angle, which in turn affects the calculation results of the response voltage and the SNR, ultimately determining the infrared detection probability.

[0108] Example 4 This embodiment demonstrates the simulation analysis process for various rescue equipment, including: (1) Single-machine operation process: applicable to search and rescue missions in coastal and land areas. Figure 4 This is a schematic diagram of a single-unit mission. Before the mission begins, mission planning is performed, selecting appropriate search methods and rescue equipment based on acquired distress information and environmental data. The search phase begins, executing the search task according to the selected method (e.g., helicopter visual search or radar search), and calculating the target discovery probability using the corresponding usage model. If a target is found, the rescue phase begins. In the rescue phase, an appropriate rescue model (e.g., rappelling rescue or air assault rescue) is used to carry out the rescue operation based on the target type. After the rescue is completed, the medical evacuation phase begins, planning the optimal evacuation route to transport the rescued personnel to a medical facility. Finally, after completing the mission, the mission returns to base. Each phase consists of sub-tasks, and each sub-task uses a usage model to complete the simulation, ensuring the accuracy and efficiency of mission execution.

[0109] (2) Formation operation procedure: applicable to search and rescue missions in coastal and land areas. Figure 5This is a formation mission diagram. In the formation operation process, the command center first organizes a formation of aircraft of the same type based on mission requirements and the status of each aircraft. After the formation is formed, each aircraft performs its mission according to the individual aircraft operation process, including mission planning, search, rescue, and medical evacuation. In the search simulation analysis, each aircraft works collaboratively according to a predetermined search strategy to expand the search area and improve search efficiency. For example, when using a formation search method, each aircraft maintains a certain distance and search angle to ensure that no search area is missed. In the rescue simulation analysis, aircraft in the same formation rationally allocate rescue resources according to the situation on site. For example, when there are many rescue targets, some aircraft are responsible for rappelling rescue, while others are responsible for air assault rescue or transporting rescue supplies. The aircraft share information in real time through the communication system to collaboratively complete the rescue mission. After the rescue is completed, in accordance with the requirements of the medical evacuation and return-to-base procedures, the rescued personnel are sent to medical institutions and returned to base.

[0110] (3) System operation process: applicable to search and rescue missions in earthquake and flood disasters. Figure 6 This is a schematic diagram of the system's mission. In the system's operational process, multiple scenarios and equipment collaborate to execute tasks. At the start of the mission, drones take off first, undertaking emergency communication tasks, establishing a temporary communication network to ensure smooth communication between the rescue site, the command center, and various rescue equipment. Helicopters perform sub-tasks according to mission requirements, including aerial reconnaissance, rappelling rescue, airdrop rescue, aerial hoisting, air assault rescue, and pre-hospital emergency care. For example, in earthquake disaster search and rescue, helicopters first conduct aerial reconnaissance, using onboard optoelectronic (infrared) equipment and radar detection equipment to obtain information such as the distribution of people and terrain in the disaster area, and transmit this information to the command center in real time. Based on the reconnaissance results, the command center issues rescue orders, and helicopters perform rappelling or air assault rescue missions to rescue trapped personnel. Simultaneously, fixed-wing medical aircraft perform long-distance medical rescue missions in the mission scenario, receiving seriously injured patients transferred by helicopters and transporting them to large medical institutions for further treatment. Throughout the rescue simulation analysis, the various equipment share information and collaborate through the communication network, improving rescue efficiency.

[0111] (4) Ship and engine operation process: applicable to search and rescue missions in coastal and offshore areas. Figure 7This is a schematic diagram of a ship-aircraft coordinated mission. In the ship-aircraft operation process, helicopters and ships cooperate with each other. After the mission begins, the helicopter and ship depart simultaneously and enter the search phase. The helicopter executes the search mission according to the search area determined by the maritime search area planning model and the selected search method (such as parallel line search or fan-shaped search), and calls the corresponding usage mode model to calculate the target discovery probability. The ship searches in the designated area according to the predetermined search path. During the search, the helicopter and ship maintain uninterrupted communication and share search information. Once the helicopter or ship discovers the target, the rescue phase immediately begins. If the helicopter discovers the target, it will call the rescue operation model, such as rappelling rescue, helicopter rescue, or airdrop rescue, depending on the target type and the situation on site; if the ship discovers the target, it can conduct salvage or provide support to the helicopter. After the rescue is completed, the medical evacuation and return-to-base phase begins, where the rescued personnel are transported to medical facilities and returned to base.

[0112] While the specific embodiments of the present invention depict actions or steps in a particular order, this should be understood as requiring such actions or steps to be performed in the specific order shown or in sequential order, or requiring all illustrated actions or steps to be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.

[0113] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A simulation analysis method for aviation rescue missions in maritime search and rescue, characterized in that, Includes the following steps: Step S1: Obtain input information for the air search and rescue mission, including the type of distressed object, approximate location, weather information, and time information; Step S2: Based on the input information, obtain the mission area, determine the rescue equipment, determine the detection mode and search trajectory for search simulation analysis, and determine the rescue method for rescue simulation analysis; Step S3: Deploy rescue equipment in the mission area, determine multiple search and rescue plans based on the detection mode, search trajectory, survival model of the person who fell into the water, and aircraft fuel consumption model, and perform the search simulation analysis. If the distressed object is found during the search process, perform rescue simulation analysis in accordance with the rescue method. In step S3, multiple search and rescue plans are determined based on the detection mode, search trajectory, survival model of the person who fell into the water, and aircraft fuel consumption model. The specific steps of performing the search simulation analysis include: The target detection probability is obtained based on the detection mode; The survival model for people who fall into the water determines the survival time of a person after falling into the water based on prior statistical information, and then compares the time when the aircraft arrives at the location of the person who fell into the water with the survival time to determine whether the person has survived. The aircraft fuel consumption model determines the aircraft's maximum range based on the fuel consumption rate; Multiple search and rescue plans are randomly generated, each with different rescue equipment, detection modes, search tracks, and rescue methods; For each search and rescue plan, a search simulation analysis is performed based on the target discovery probability, search trajectory, maximum range, and whether personnel survived to determine whether the distressed object can be found. Step S4: Obtain the results data of search and rescue simulation analysis of multiple search and rescue plans, generate effect indicators, and determine the optimal search and rescue plan based on the effect indicators of each search and rescue plan.

2. The simulation analysis method for maritime search and rescue aviation rescue missions according to claim 1, characterized in that, In step S2, the step of obtaining the task area specifically includes: Multiple possible drift trajectories are obtained based on the rough position and time information in the input information; The approximate location is expanded based on the multiple possible drift trajectories to form the task area.

3. The simulation analysis method for maritime search and rescue aviation rescue missions according to claim 2, characterized in that, The step of forming the task region includes: Calculate the convex hull of multiple points on multiple possible drift trajectories. For each edge of the convex hull, obtain the farthest point, parallel limit point, and vertical limit point to determine multiple candidate bounding rectangles. The candidate bounding rectangle with the smallest area is determined as the task region.

4. The simulation analysis method for maritime search and rescue aviation rescue missions according to claim 3, characterized in that, In step S2, the step of determining the rescue equipment specifically includes: The rescue equipment is determined according to the type of distressed object, and the rescue equipment includes a single helicopter, a helicopter formation, and helicopter and ship coordination. The steps for determining the detection mode and search trajectory in the search simulation analysis specifically include: The search simulation analysis determines the detection mode based on the type of distressed object and meteorological information; The search track is selected based on the shape of the mission area, the type of distressed object, and meteorological information. The search track includes parallel line search, lateral line search, extended rectangle search, fan shape search, and contour line search. The steps for determining the rescue method in the rescue simulation analysis specifically include: The rescue method is determined based on the type of distressed object and meteorological information, and the rescue simulation analysis is used to determine the rescue method.

5. The simulation analysis method for maritime search and rescue aviation rescue missions according to claim 4, characterized in that, The step of obtaining the target detection probability based on the detection mode specifically includes: The detection modes include visual search, radar detection, and photoelectric detection; For visual search mode, the target detection probability is obtained based on the distance relationship between the aircraft and the target. For radar detection mode, the initial radar detection probability is obtained by inputting radar performance parameters and calculation process parameters. Based on the input visibility data, the initial radar detection probability is corrected to obtain the final target detection probability of radar detection that takes into account environmental factors. For photoelectric detection mode, the solid angle occupied by the target in the system's field of view is determined based on the input photoelectric performance parameters and target and environmental parameters. The signal-to-noise ratio of the target and background noise is calculated, and the target detection probability of photoelectric detection is determined by the signal-to-noise ratio.

6. The simulation analysis method for aviation rescue missions in maritime search and rescue according to claim 5, characterized in that, In step S3, the step of performing rescue simulation analysis using the rescue method specifically includes: The rescue methods include rappelling rescue, helicopter descent rescue, water landing rescue, airdrop rescue, and aerial hoisting rescue; For rappelling rescue, input rappelling parameters and sea state parameters, determine different sea state influence factors for different visibility, and finally calculate the rescue duration and number of rescuers. For air-drop rescue, input the number of people to be transferred and the maximum passenger capacity of the aircraft, determine the number of round trips, distinguish between primary and subsequent transport, and record the data of multiple round trips to obtain the rescue duration and the number of people rescued. For water rescue, input sea state parameters to obtain data on aircraft flight and lifeboat movement after water landing, and obtain the rescue duration and number of people rescued; For airdrop rescue, the difference between wind resistance and descent speed is taken into account to calculate the rescue duration corresponding to the descent of supplies. For aerial hoisting rescue, input the number of personnel to be hoisted and the hoisting height parameters to calculate the rescue duration and the number of people to be rescued throughout the entire hoisting process.

7. The simulation analysis method for maritime search and rescue aviation rescue missions according to claim 6, characterized in that, Step S4 includes: Based on the results of search and rescue simulation analysis of multiple search and rescue plans, effectiveness indicators are generated, including search process efficiency, rescue process efficiency, and transportation process efficiency. The effectiveness indicators are weighted to obtain a comprehensive score, and the search and rescue plan with the highest comprehensive score is determined as the optimal search and rescue plan.

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