Ship dynamic tracking method and system based on Beidou positioning

Abstract

This invention belongs to the field of ship tracking and positioning technology, and discloses a ship dynamic tracking method and system based on BeiDou positioning. It uses a shipborne BeiDou satellite receiver to determine the ship's location in real time and determine whether a ship distress alarm has been triggered. The distressed ship is marked and distress alarm information is sent to the BeiDou integrated application service platform. The distressed ship is located on an electronic nautical chart, the distress area is marked, and surrounding ships or global ocean meteorological models are queried to generate a vector ocean field of the distress area and predict the high-probability drift zone of the distressed ship. A list of reserve rescue vessels is searched for, a minimum-cost path is generated, and the estimated arrival time is calculated. A list of reserve rescue vessels is generated, and rescue requests are sent to the reserve rescue vessels. Based on the responses, the actual rescue vessel is marked. Parallel obstacle detection and obstacle coordination are performed on the actual rescue vessel. This invention uses BeiDou dynamic tracking technology to obtain the ship's position and status in real time, realizing full-process tracking and rescue from distress alarm to rescue execution.

Description

Technical Field

[0001] This invention belongs to the field of ship tracking and positioning technology, specifically a ship dynamic tracking method and system based on BeiDou positioning. Background Technology

[0002] Ensuring the safety of ship navigation has always been a core issue in the global shipping industry. As the shipping industry moves towards intelligent and unmanned operations, building a comprehensive ship dynamic tracking and emergency response system covering hazard detection, precise positioning, dynamic tracking, trajectory prediction, and intelligent rescue has become an urgent technical challenge. The BeiDou Navigation Satellite System, as my country's independently controllable global satellite navigation system, offers a new technical path for achieving continuous, reliable, and high-precision dynamic tracking of ships due to its short message communication, high-precision positioning, and timing capabilities. However, existing ship dynamic tracking systems are mostly limited to position reporting and trajectory display. How to deeply integrate BeiDou positioning technology with real-time ship status perception, trajectory drift prediction, and intelligent dispatch of rescue resources remains a key issue that has not yet been fully resolved in current dynamic tracking technology.

[0003] In existing technologies, ship dynamic tracking largely relies on discrete position reporting, lacking continuous intelligent identification and environmental coupling analysis of ship status. Hazard detection still largely depends on single sensors or manual alarms, resulting in delayed hazard response and insufficient accuracy in positioning and drift prediction within the tracking system. Furthermore, traditional ship tracking systems still suffer from multiple bottlenecks in positioning, especially in certain scenarios where they rely on external systems such as GPS, making it difficult to meet the requirements for high reliability and high autonomy in dynamic tracking. Existing drift prediction models are mostly based on historical statistical data and do not effectively utilize surrounding ships as moving observation nodes, leading to a disconnect between trajectory prediction and actual sea conditions in the tracking system, thus limiting the accuracy and environmental adaptability of dynamic tracking.

[0004] There are significant deficiencies in rescue route planning that extends from dynamic tracking. Most tracking systems only provide vessel position display and do not integrate information on obstacles such as no-navigation zones and shoals on electronic charts, resulting in insufficient connection between tracking and rescue dispatch. At the same time, existing tracking systems lack multi-vessel coordinated navigation and automatic obstacle detection mechanisms. When multiple vessels converge on the same area at the same time, route conflicts are likely to occur in narrow or densely packed waterways, thereby affecting the coordination and dispatch safety of the tracking system. In terms of prioritizing rescue resources, most existing dynamic tracking systems only sort by distance and do not comprehensively consider the actual capabilities of vessels, rescue equipment, etc., and cannot provide a reliable dispatch basis for dynamic tracking systems.

[0005] To address the aforementioned issues, this invention proposes a ship dynamic tracking method and system based on BeiDou positioning, which not only enables real-time and reliable tracking of ship position and status, but also integrates environmental data to achieve trajectory prediction, path planning, and multi-ship collaboration. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0007] The technical solution adopted by this invention to solve the technical problem is: a ship dynamic tracking method based on Beidou positioning, comprising: The ship's location is determined in real time by using a shipborne Beidou satellite receiver, and it is determined whether a ship emergency alarm is triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Based on the received distress alarm information, the Beidou integrated application service platform locates the distressed vessel on the electronic nautical chart, marks the distress area, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the distress area. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability area of ​​drift of the distressed vessel. Track the distressed vessel and prepare rescue vessels, generate minimum cost paths for the rescue vessels based on high-probability drift areas, calculate the estimated arrival time of the rescue vessels based on their location and vector ocean field, prioritize the rescue vessels, and generate a list of rescue vessels. Rescue requests are sent to the reserve rescue vessels based on the list of reserve rescue vessels, and the actual rescue vessels are marked based on the responses from the reserve rescue vessels. Parallel obstruction detection and obstruction coordination are carried out for the actual rescue vessels. The method for determining whether a ship emergency alarm has been triggered is as follows: The shipborne Beidou satellite receiver is used to detect ship hazards in real time. Ship hazards include sinking detection, severe tilting detection, dismantling detection, and no-navigation zone detection. If any ship hazard exists, a ship hazard alarm is triggered and the ship hazard is recorded as sinking. The vector ocean field is obtained as follows: If the number of surrounding vessels is less than the preset standard, wind and current field data provided by the global marine meteorological forecast model are received to generate a vector ocean field within the danger zone. Otherwise, ocean current and wind field analysis is performed on the danger zone through surrounding vessels to obtain the wind and current vectors of surrounding vessels. Kriging interpolation is used to calculate the weight of each surrounding vessel. The wind and current vectors of each surrounding vessel are interpolated and fused together with the calculated weights to obtain the vector ocean field within the danger zone. The wind and ocean current vectors of the surrounding vessels are obtained as follows: The wind current vector of the surrounding ships is obtained by using the meteorological station sensors installed on the top of the mast of the surrounding ships. The position and actual speed vector of the surrounding ships are collected and calculated by the shipborne Beidou satellite receiver of the surrounding ships. The engine speed of the surrounding ships is collected by the ship's main engine monitoring system. The planned speed vector of the surrounding ships is estimated by combining the empirical formula of speed. The actual speed vector and the planned speed vector are processed to obtain the ocean current vector of the surrounding ships. The high-probability drift region is obtained as follows: The trajectory prediction period is set, and multiple Monte Carlo simulations are performed using a vector ocean field and a particle filter algorithm. Each simulation yields a possible drift path for the distressed vessel. All paths are then merged to obtain a probability distribution map of the simulated drift area of ​​the distressed vessel. Areas with a probability greater than the probability threshold are marked as high-probability drift areas. The minimum cost path is generated as follows: For each reserve rescue vessel, a rescue path is planned using the Dijkstra algorithm. Starting from the vessel's position coordinates, a high-probability drift zone is obtained, and the center coordinates of the high-probability drift zone are set as the theoretical intersection point. Using the theoretical intersection point as the endpoint, obstacle avoidance parameters are set, including no-navigation zones, shoals and reefs, and densely trafficked areas. The path cost is quantified in nautical miles, and the minimum cost path for the reserve rescue vessel is calculated using the Dijkstra algorithm. The method for generating the list of reserve rescue vessels is as follows: For each reserve rescue vessel, the maximum safe speed of the reserve rescue vessel is obtained according to the planned minimum cost path. At the same time, the influence of wind current vector and ocean current vector in the vector ocean field on the speed is considered, and the estimated arrival time of each reserve rescue vessel is calculated. The reserve rescue vessels are sorted from shortest to longest estimated arrival time, and the sorting number is used as the priority of the reserve rescue vessels to generate a list of reserve rescue vessels, including the priority order of the reserve rescue vessels and the least cost path. The parallel obstacle detection method is as follows: Mark the sea area covered by the minimum cost path of all actual rescue vessels as the rescue sea area, divide the rescue sea area into grid cells evenly, obtain the grid cells passed by the minimum cost path of each actual rescue vessel, and if there is a grid cell in which more than 1 actual rescue vessels pass, mark the grid cell as a coordinate obstacle cell. Obtain the estimated obstruction time windows of all actual rescue vessels passing through the coordinate obstruction unit on the coordinate obstruction unit, determine whether there is an overlapping period of the estimated obstruction time windows, and if so, determine that the actual rescue vessels corresponding to the estimated obstruction time windows with overlapping periods are obstructed in parallel. The method for obtaining the expected time window of obstruction is as follows: Obtain the actual rescue vessel that passes through the coordinate obstacle cell via the minimum cost path, set the departure time for the actual rescue vessel, combine the departure time with the minimum cost path, calculate the time when the actual rescue vessel arrives at the coordinate obstacle cell, mark it as the expected obstacle time of the actual rescue vessel, expand the expected obstacle time into an expected obstacle time window with the expected obstacle time as the midpoint, and obtain the expected obstacle time window of the actual rescue vessel on the coordinate obstacle cell. The manner in which coordination is hindered is as follows: For actual rescue vessels that are simultaneously hindered, the duration of the overlapping period of the expected hinderment time windows of the two actual rescue vessels is obtained and marked as the duration of the hinderment between the two actual rescue vessels; Actual rescue vessels that are obstructing each other are grouped into the same obstruction coordination group. The actual rescue vessels in the same obstruction coordination group are sorted according to priority to obtain an obstruction coordination sequence. Obstruction coordination is carried out on two adjacent actual rescue vessels in the obstruction coordination sequence in sequence. For the first pair of adjacent actual rescue vessels in the obstruction coordination sequence, the departure time of the later actual rescue vessel is postponed for a period of time equal to the obstruction time between the two target rescues. The departure time of the next actual rescue vessel is then changed based on the postponed departure time.

[0008] A ship dynamic tracking system based on BeiDou positioning includes: Dynamic tracking alarm module: The ship uses a shipborne Beidou satellite receiver to determine the ship's location in real time and determine whether a ship emergency alarm has been triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Hazard Analysis and Location Module: Based on the received hazard alarm information, the Beidou Integrated Application Service Platform locates the distressed vessel on the electronic nautical chart, marks the hazard range, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the hazard range. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability drift zone of the distressed vessel. The distress tracking and analysis module tracks and prepares rescue vessels for distressed ships, generates minimum-cost paths for these vessels based on high-probability drift zones, calculates their estimated arrival time using vector ocean fields and prioritizes them, and generates a list of prepared rescue vessels. The distress vessel identification module sends distress requests to the reserve rescue vessels based on the reserve rescue vessel list, marks the actual rescue vessels based on the responses from the reserve rescue vessels, and performs parallel obstruction detection and obstruction coordination for the actual rescue vessels.

[0009] The beneficial effects of this invention are as follows: 1. This invention achieves multi-dimensional real-time monitoring of hazards through a shipborne BeiDou receiver. It integrates technologies such as water-soluble materials and water pressure sensing mechanisms, as well as dynamic calculations using a three-axis sensor, enabling accurate detection of four types of hazards, including shipwrecks and severe tilting, avoiding the problems of missed or false alarms from single sensors. By combining BeiDou short message communication with electronic chart projection positioning, hazard alarm information is synchronized to the service platform in real time, providing accurate initial coordinates for rescue operations and solving the problems of delayed hazard response and large positioning errors in existing technologies.

[0010] 2. This invention innovatively uses surrounding ships as mobile observation stations to generate a vector ocean field. It predicts high-probability drift areas through a particle filtering algorithm, reducing trajectory prediction errors compared to traditional models. Based on a path planning algorithm, it constructs a minimum-cost path model that integrates ocean environmental resistance. Combined with priority ranking and spatiotemporal obstacle coordination mechanisms, it reduces the error in the estimated arrival time of rescue ships and avoids path intersections between multiple ships. Compared to traditional rescue dispatching, this invention improves efficiency and significantly optimizes the collaborative efficiency of maritime rescue resources. Attached Figure Description

[0011] The invention will now be further described with reference to the accompanying drawings.

[0012] Figure 1 This is a flowchart of the steps of the ship dynamic tracking method based on Beidou positioning described in Embodiment 1 of the present invention; Figure 2 This is a flowchart of the parallel obstacle detection and obstacle coordination steps in the ship dynamic tracking method based on Beidou positioning described in Embodiment 1 of the present invention. Detailed Implementation

[0013] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0014] Example 1

[0015] Please see Figures 1-2 As shown in the embodiment of the present invention, the ship dynamic tracking method based on BeiDou positioning includes the following steps: S1: The ship's location is determined in real time by the shipborne Beidou satellite receiver and it is determined whether a ship emergency alarm is triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Shipborne Beidou satellite receivers are used to monitor the ship's position and condition in real time to detect ship hazards, including sinking detection, severe tilting detection, dismantling detection, and detection in prohibited navigation areas. For shipwreck detection, the shipborne Beidou satellite receiver is equipped with a water-repellent device. The water-repellent device uses a dual mechanism of water-soluble materials and water pressure sensing. When the ship sinks and the device comes into contact with water at a depth of 0.5 meters or more, the water-soluble material dissolves, and at the same time the water pressure sensor detects the preset water pressure value. The water-repellent device automatically detaches from the hull and floats up, triggering a ship emergency alarm and recording the ship emergency as a shipwreck. For severe tilt detection, the shipborne Beidou satellite receiver has a built-in three-axis sensor to measure the acceleration changes of the ship in the X, Y, and Z axes in real time. The tilt angle of the ship is calculated. When the tilt angle of the ship exceeds the preset angle threshold and the duration reaches the preset duration, it is determined that the ship has tilted severely, triggering a ship emergency alarm and recording the ship emergency as severe tilt. For disassembly detection, the shipborne Beidou satellite receiver is equipped with a connection sensor. When the receiver is disassembled, the connection sensor detects that the circuit is broken, generates a change in electrical signal, triggers the ship's emergency alarm, and records the ship's emergency as receiver disassembly. For the detection of restricted navigation areas, the shipborne Beidou satellite receiver has pre-stored electronic nautical charts and the coordinate range of the restricted navigation area. The shipborne Beidou satellite receiver receives signals from multiple satellites in real time, calculates the ship's position coordinates through a positioning algorithm, and compares them with the coordinate range of the restricted navigation area. If the ship's position coordinates fall within the coordinate range of the restricted navigation area, a ship emergency alarm is triggered and the ship emergency is recorded as entering the restricted navigation area. Both the ship's position coordinates and the coordinate range of the restricted navigation area are latitude and longitude coordinates. If a ship distress alarm is triggered, the ship will be marked as a distressed vessel. The shipborne Beidou satellite receiver will send the distress alarm information to the Beidou Integrated Application Service Platform in the format specified by the Beidou Short Message Protocol. The distress alarm information includes the ship ID, ship position coordinates, ship speed vector, and the ship distress situation. Among them, the vessel ID is a unique identifier assigned by the maritime administration department when the vessel is registered; the vessel speed vector represents the vessel's speed of movement including direction; and vessel emergencies include sinking, severe listing, receiver disassembly, and entering a restricted area. It should be noted that the purpose of this step is to detect ship hazards in real time through a multi-sensor fusion mechanism and automatically send alarm information using the BeiDou short message protocol, thereby achieving early detection and automated reporting of hazards, reducing human delays. The multi-dimensional detection mechanism covers common types of maritime hazards, improving alarm reliability. BeiDou short message ensures that alarm information can still be transmitted in sea areas without public network signals. It integrates multiple sensors and electronic nautical charts for dynamic comparison of restricted areas, enabling intelligent identification and classification of hazard types for reporting. S2: Based on the received distress alarm information, the Beidou integrated application service platform locates the distressed vessel on the electronic nautical chart, marks the distress area, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the distress area. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability area of ​​drift of the distressed vessel. The Beidou Integrated Application Service Platform is equipped with a decryption module that pre-stores the AES key corresponding to the shipborne Beidou satellite receiver. If a hazard alarm is received, the Beidou Integrated Application Service Platform uses the decryption module to decrypt the received hazard alarm to obtain the plaintext of the hazard alarm. The Beidou integrated application service platform calls the electronic nautical chart system, which contains geographic information such as sea depth, islands, navigation marks, and ports. It uses the Gauss-Kruger projection algorithm to convert the ship's position coordinates in the hazard alarm information to plane coordinates on the electronic nautical chart and marks them on the electronic nautical chart system to accurately locate the distressed ship. After positioning is completed, the Beidou integrated application service platform marks the distressed vessel with a flashing red icon on the electronic nautical chart system, and starts a real-time monitoring program to refresh the vessel's position coordinates in real time and record the trajectory of the vessel's position coordinate changes, generating a dynamic monitoring log. For the vessel's position coordinates when the distressed vessel triggers the vessel distress alarm, a marine field analysis radius is set for the distressed vessel, and the range of position coordinates within the marine field analysis radius of the distressed vessel is obtained and marked as the distress range. Vessels equipped with shipborne Beidou satellite receivers within the distress range are queried through the Beidou Integrated Application Service Platform and marked as surrounding vessels. If the number of surrounding vessels is less than the preset standard, it is determined that the ocean current and wind field analysis of the danger area cannot be performed based on the surrounding vessels. The Beidou integrated application service platform switches to the backup data source, accesses the existing global marine meteorological forecast model, receives the pre-calculated wind field and current field data covering the whole globe provided by the global marine meteorological forecast model, and generates the vector ocean field within the danger area. If the number of surrounding vessels is greater than or equal to the preset number standard, the ocean current and wind field analysis of the danger area is carried out through the surrounding vessels to generate a vector ocean field within the danger area. The vector ocean field includes the wind current vector and ocean current vector at each coordinate within the danger area. It should be noted that by using surrounding vessels to analyze the ocean current and wind field within the hazard area, and treating the surrounding vessels as mobile meteorological and hydrological observation stations, the resulting vector ocean field within the hazard area is more accurate and closer to the actual environment. Specifically, the wind vectors of the surrounding ships are obtained by using meteorological station sensors installed on the top of the mast of the surrounding ships; For each surrounding vessel i, calculate the ocean current vector of the surrounding vessels. : ; in, The vector representing the actual speed of surrounding vessel i is obtained by collecting and calculating data from the shipborne BeiDou satellite receivers of the surrounding vessels. The vector representing the planned speed of the surrounding vessel i is estimated by collecting the engine speed of the surrounding vessel i through the ship's main engine monitoring system and combining it with empirical formulas for speed. It should be noted that the actual movement of a ship at sea is the result of the combined effect of its own power and the marine environment. When a ship sails along a planned route, the difference between its actual speed vector and the planned speed vector is mainly caused by ocean currents. The purpose of this step is to obtain ocean current data at discrete points by inverting the ocean current vector through surrounding ships. Within the danger zone, the weight of each surrounding vessel is calculated using the Kriging interpolation method. The wind field vector and ocean current vector of each surrounding vessel are then interpolated and fused together with the calculated weights to obtain the vector ocean field within the danger zone. The vector ocean field includes the wind current vector and ocean current vector at each coordinate within the danger zone. Set the trajectory prediction period, use the obtained vector ocean field as the driving force, and use the particle filter algorithm to perform multiple Monte Carlo simulations. Each simulation yields a possible drift path for the distressed vessel. All paths are merged to obtain a probability distribution map of the simulated drift area of ​​the distressed vessel. Areas with a probability greater than the probability threshold are marked as high-probability drift areas. It should be noted that this step is to locate the distressed vessel on the electronic nautical chart based on the alarm information, generate a vector ocean field by combining the surrounding vessels or global meteorological models, predict the high probability zone of the distressed vessel's drift through particle filtering, improve the accuracy of the environmental field by using ocean current data inverted from the surrounding vessels, adapt the particle filtering Monte Carlo simulation to the uncertainty of the ocean environment, improve the reliability of drift prediction, support redundancy backup of multiple data sources, enhance the robustness of the system, use the surrounding vessels as mobile observation stations, invert ocean currents through speed vectors and engine speed, achieve low-cost, high-resolution ocean environment reconstruction, introduce Kriging interpolation to fuse discrete wind and current data, generate a continuous vector ocean field, and support refined drift simulation. S3: Search for backup rescue vessels for the distressed vessel, generate minimum cost paths for backup rescue vessels based on high drift probability areas, calculate the estimated arrival time of backup rescue vessels by combining vector ocean field, prioritize backup rescue vessels, and generate a backup rescue vessel list; Obtain information on nearby vessels, and determine whether a vessel has rescue equipment and personnel by querying its registration information and equipment configuration. If so, mark the nearby vessels as reserve rescue vessels. Obtain the number of prepared rescue vessels. If the number of prepared rescue vessels is less than the minimum expected number, gradually expand the search area until the number of prepared rescue vessels reaches the minimum expected number. For each reserve rescue vessel, a rescue path is planned using the Dijkstra algorithm. Starting from the vessel's position coordinates, a high-probability drift zone is obtained, and the center coordinates of the high-probability drift zone are set as the theoretical intersection point. Using the theoretical intersection point as the endpoint, obstacle avoidance parameters are set, including no-navigation zones, shoals and reefs, and densely trafficked areas. The path cost is quantified in nautical miles. The minimum cost path from the starting point to the ending point is calculated using the Dijkstra algorithm. The path point sequence of the minimum cost path and the total length S are output. The path point sequence includes a latitude and longitude point every 0.5 nautical miles on the minimum cost path. Based on the obtained minimum cost path, the maximum safe speed V of the reserve rescue vessel is determined. Considering the influence of wind and ocean current vectors in the vector ocean field on the speed, the estimated arrival time T is calculated using the following formula: ; in, The average current velocity along the minimum-cost path is represented by the spatial averaging of the current vectors along the minimum-cost path in the vector ocean field. This represents the angle between the spatially averaged ocean current vector and the ship's heading. The average wind speed along the minimum-cost path is obtained by spatial averaging of the wind flow vectors along the minimum-cost path in the vector ocean field. This represents the angle between the spatially averaged wind vector and the ship's heading. For the multiple reserve rescue vessels obtained, plan the corresponding minimum cost path for each reserve rescue vessel, calculate the estimated arrival time of each reserve rescue vessel based on the minimum cost path, sort the reserve rescue vessels from smallest to largest according to the estimated arrival time, use the sort number as the priority of the reserve rescue vessels, and generate a list of reserve rescue vessels, including the priority order of the reserve rescue vessels and the minimum cost path. It should be noted that the purpose of this step is to dynamically search for nearby vessels with rescue capabilities, plan the minimum cost path for obstacle avoidance, calculate the estimated arrival time, generate a rescue list according to priority, and filter rescue capabilities by combining vessel registration information to improve rescue effectiveness. The path planning takes into account obstacles such as no-navigation zones and shoals to ensure navigation safety. Wind current vectors are introduced to correct the speed and improve the accuracy of time estimation. The center of the high-probability drift zone is proposed as the path endpoint to balance search efficiency and rescue success rate, and achieve more realistic speed and time delay estimation. S4: Send rescue requests to the reserve rescue vessels according to the list of reserve rescue vessels, and mark the actual rescue vessels according to the responses from the reserve rescue vessels, and perform parallel obstruction detection and obstruction coordination for the actual rescue vessels; like Figure 2As shown, the specific steps of parallel obstacle detection and obstacle coordination are as follows: Based on the list of reserve rescue vessels, the BeiDou Integrated Application Service Platform sends rescue requests to the reserve rescue vessels in the list and waits for confirmation from the reserve rescue vessels. If no confirmation is received from the actual rescue vessel within a preset time, the BeiDou Integrated Application Service Platform automatically resends the rescue request. If the number of rescue requests sent exceeds the preset limit, or if the reserve rescue vessel refuses the rescue request, the reserve rescue vessel will be removed from the list of reserve rescue vessels. Mark the remaining reserve rescue vessels in the reserve rescue vessel list as actual rescue vessels. If the number of actual rescue vessels is 0, expand the search range and search for actual rescue vessels again until an actual rescue vessel is found. If the actual number of rescue vessels is not zero, obtain the minimum cost path of the actual rescue vessels, and perform parallel obstacle detection on the minimum cost path of all actual rescue vessels. Specifically, a hindrance detection method combining spatial grid partitioning and time windows is used to perform parallel hindrance detection on the minimum cost paths of all actual rescue vessels. The sea areas covered by all minimum cost paths are marked as rescue sea areas. The rescue sea areas are evenly divided into several grid cells. The grid cells traversed by the minimum cost path of each actual rescue vessel are obtained. It is determined whether there are more than 1 actual rescue vessels passing through the same grid cell. If so, the grid cell is marked as a coordinate hindrance cell. For a coordinate obstruction unit, obtain the actual rescue vessel that passes through the coordinate obstruction unit via the minimum cost path, set the departure time for the actual rescue vessel, combine the departure time with the minimum cost path, calculate the time when the actual rescue vessel arrives at the coordinate obstruction unit, mark it as the expected obstruction time of the actual rescue vessel, and expand the expected obstruction time into an expected obstruction time window with the expected obstruction time as the midpoint. Obtain the estimated obstruction time windows of all actual rescue vessels passing through the coordinate obstruction unit on the coordinate obstruction unit, and determine whether there is an overlap in the estimated obstruction time windows. If there is no overlap, determine that there is no parallel obstruction of actual rescue vessels on the coordinate obstruction unit. If there is overlap, determine that the actual rescue vessels corresponding to the estimated obstruction time windows with overlapping time windows have parallel obstruction. For any two actual rescue vessels with parallel obstruction, obtain the duration of the overlap in the time between the two actual rescue vessels and mark it as the obstruction duration of the two actual rescue vessels. Actual rescue vessels that are obstructing each other are grouped into the same obstruction coordination group. The actual rescue vessels in the same obstruction coordination group are sorted according to priority to obtain an obstruction coordination sequence. The obstruction coordination is carried out on the two actual rescue vessels that are sequentially adjacent in the obstruction coordination sequence. For the first pair of sequentially adjacent actual rescue vessels in the obstruction coordination sequence, the departure time of the actual rescue vessel that is later in the sequence is postponed for a period of time equal to the obstruction time between the two target rescues. The departure time of the next actual rescue vessel is then changed based on the postponed departure time. After all obstruction coordination groups have been coordinated, the departure time, minimum cost path, distress alarm information and high drift probability area of ​​the distressed vessel allocated to the actual rescue vessel are integrated and packaged to obtain packaged information. The Beidou integrated application service platform sends the packaged information to the corresponding actual rescue vessel and arranges the actual rescue vessel to rescue the distressed vessel. It should be noted that the purpose of this step is to send a request to the rescue vessel and confirm the actual rescuers, perform spatiotemporal obstacle detection on its path, resolve obstacles by dynamically adjusting the departure time, avoid missing rescue requests through a multi-confirmation mechanism, detect path intersection risks in advance through spatiotemporal grid obstacle detection, coordinate the navigation of multiple vessels based on a priority-based time offset strategy to avoid collisions, propose a time-space grid obstacle detection method, transform parallel obstacles into the overlap judgment of grid cells and time windows, quantify the degree of obstacle by using obstacle duration, and dynamically adjust the departure time through a priority sequence to achieve distributed collaborative obstacle avoidance; The technical solution of this invention is as follows: A shipborne BeiDou satellite receiver is used to determine the ship's location in real time and to determine whether a ship distress alarm has been triggered. If triggered, the distressed ship is marked and distress alarm information is sent to the BeiDou Integrated Application Service Platform. Based on the received distress alarm information, the BeiDou Integrated Application Service Platform locates the distressed ship on an electronic nautical chart, marks the distress area, and queries surrounding ships or global ocean meteorological models to generate a vector ocean field of the distress area. Based on the vector ocean field, a particle filter algorithm is used to predict the high-probability drift zone of the distressed ship, search for reserve rescue ships for the distressed ship, and generate a minimum-cost path for the reserve rescue ships based on the high-probability drift zone. The estimated arrival time of the reserve rescue ships is calculated in conjunction with the vector ocean field, and the reserve rescue ships are prioritized and a list of reserve rescue ships is generated. Rescue requests are sent to the reserve rescue ships according to the list, and the actual rescue ship is marked based on the responses from the reserve rescue ships. Parallel obstacle detection and obstacle coordination are performed on the actual rescue ships.

[0016] Example 2

[0017] A ship dynamic tracking system based on BeiDou positioning includes: Dynamic tracking alarm module: The ship uses a shipborne Beidou satellite receiver to determine the ship's location in real time and determine whether a ship emergency alarm has been triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Hazard Analysis and Location Module: Based on the received hazard alarm information, the Beidou Integrated Application Service Platform locates the distressed vessel on the electronic nautical chart, marks the hazard range, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the hazard range. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability drift zone of the distressed vessel. The distress tracking and analysis module tracks and prepares rescue vessels for distressed ships, generates minimum-cost paths for these vessels based on high-probability drift zones, calculates their estimated arrival time using vector ocean fields and prioritizes them, and generates a list of prepared rescue vessels. The distress vessel identification module sends distress requests to the reserve rescue vessels based on the reserve rescue vessel list, marks the actual rescue vessels based on the responses from the reserve rescue vessels, and performs parallel obstruction detection and obstruction coordination for the actual rescue vessels.

[0018] Example 3

[0019] The BeiDou-based ship dynamic tracking method described in this invention is applicable not only to maritime vessels but also to the dynamic tracking and emergency rescue of inland waterway vessels (including rivers, lakes, canals, etc.). Specifically, it includes: The ship's location is determined in real time by using a shipborne Beidou satellite receiver, and it is determined whether a ship emergency alarm is triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. In addition to shipwrecks, severe listing, and dismantling inspections, the following specialized inspections are now included for inland waterway vessel incidents: Collision detection: Using AIS (Automatic Identification System) or radar data, the distance, relative speed and encounter situation between the vessel and surrounding vessels are calculated in real time. If there is a risk of collision (such as the distance being less than the safety threshold or DCPA / TCPA exceeding the limit), a collision alarm is triggered. Grounding detection: The shipborne Beidou receiver has a built-in electronic river chart / channel chart, which compares the ship's position with the channel depth, reefs, sunken ships and other obstructions in real time. If the ship's track deviates from the channel or enters shallow water, a grounding risk alarm is triggered. Drift / loss of control detection: The ship's main engine monitoring system and rudder angle sensor monitor abnormal states such as main engine shutdown and loss of rudder effectiveness in real time. If the ship's speed is below the threshold and its course is out of control when it is not anchored, a drift / loss of control alarm will be triggered. Based on the received distress alarm information, the platform locates the distressed vessel on the electronic nautical chart, marks the distress area, and queries surrounding vessels or inland waterway hydrological models to generate a vector flow field within the distress area. Based on the vector flow field, a particle filter algorithm is used to predict the high probability area of ​​drift of the distressed vessel. If there are a sufficient number of surrounding vessels within the danger zone (equipped with flow velocity sensors or capable of track inversion), a continuous vector flow field is generated using the real-time flow velocity and direction data reported by each vessel and the Kriging interpolation method. If there are not enough vessels in the vicinity, the real-time vector flow field of the incident section can be obtained by connecting to the inland waterway hydrological monitoring system (such as hydrological stations, ADCP online monitoring data) or the inland waterway hydrological model. Track the distressed vessel and prepare rescue vessels, generate minimum cost paths for the rescue vessels based on high drift probability areas, calculate the estimated arrival time based on the location of the rescue vessels and the vector water flow field, prioritize the rescue vessels, and generate a list of rescue vessels. Rescue requests are sent to the reserve rescue vessels based on the list of reserve rescue vessels, and the actual rescue vessels are marked based on the responses from the reserve rescue vessels. Parallel obstruction detection and obstruction coordination are then carried out for the actual rescue vessels.

[0020] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A ship dynamic tracking method based on BeiDou positioning, characterized in that: include: The ship's location is determined in real time by using a shipborne Beidou satellite receiver, and it is determined whether a ship emergency alarm is triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Based on the received distress alarm information, the Beidou integrated application service platform locates the distressed vessel on the electronic nautical chart, marks the distress area, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the distress area. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability area of ​​drift of the distressed vessel. The vector ocean field is obtained as follows: If the number of surrounding vessels is less than the preset standard, wind and current field data provided by the global marine meteorological forecast model are received to generate a vector ocean field within the danger zone. Otherwise, ocean current and wind field analysis is performed on the danger zone through surrounding vessels to obtain the wind and current vectors of surrounding vessels. Kriging interpolation is used to calculate the weight of each surrounding vessel. The wind and current vectors of each surrounding vessel are interpolated and fused together with the calculated weights to obtain the vector ocean field within the danger zone. The wind and ocean current vectors of the surrounding vessels are obtained as follows: The wind current vector of the surrounding ships is obtained by using the meteorological station sensors installed on the top of the mast of the surrounding ships. The position and actual speed vector of the surrounding ships are collected and calculated by the shipborne Beidou satellite receiver of the surrounding ships. The engine speed of the surrounding ships is collected by the ship's main engine monitoring system. The planned speed vector of the surrounding ships is estimated by combining the empirical formula of speed. The actual speed vector and the planned speed vector are processed to obtain the ocean current vector of the surrounding ships. The high-probability drift region is obtained as follows: The trajectory prediction period is set, and multiple Monte Carlo simulations are performed using a vector ocean field and a particle filter algorithm. Each simulation yields a possible drift path for the distressed vessel. All paths are then merged to obtain a probability distribution map of the simulated drift area of ​​the distressed vessel. Areas with a probability greater than the probability threshold are marked as high-probability drift areas. Track the distressed vessel and prepare rescue vessels, generate minimum cost paths for the rescue vessels based on high-probability drift areas, calculate the estimated arrival time of the rescue vessels based on their location and vector ocean field, prioritize the rescue vessels, and generate a list of rescue vessels. Rescue requests are sent to the reserve rescue vessels based on the list of reserve rescue vessels, and the actual rescue vessels are marked based on the responses from the reserve rescue vessels. Parallel obstruction detection and obstruction coordination are then carried out for the actual rescue vessels.

2. The ship dynamic tracking method based on BeiDou positioning according to claim 1, characterized in that: The minimum cost path is generated as follows: For each reserve rescue vessel, a rescue path is planned using the Dijkstra algorithm. Starting from the vessel's position coordinates, a high-probability drift zone is identified, and the center coordinates of this zone are set as the theoretical intersection point. Using this theoretical intersection point as the endpoint, obstacle avoidance parameters are set, including no-navigation zones, shoals and reefs, and densely trafficked areas. The path cost is quantified in nautical miles, and the minimum cost path for the reserve rescue vessel is calculated using the Dijkstra algorithm.

3. The ship dynamic tracking method based on BeiDou positioning according to claim 2, characterized in that: The list of reserve rescue vessels is generated as follows: For each reserve rescue vessel, the maximum safe speed of the reserve rescue vessel is obtained according to the planned minimum cost path. At the same time, the influence of wind current vector and ocean current vector in the vector ocean field on the speed is considered, and the estimated arrival time of each reserve rescue vessel is calculated. The reserve rescue vessels are sorted from shortest to longest estimated arrival time, and the sorting number is used as the priority of the reserve rescue vessels to generate a reserve rescue vessel list, which includes the priority order of the reserve rescue vessels and the least cost path.

4. The ship dynamic tracking method based on BeiDou positioning according to claim 1, characterized in that: The parallel obstacle detection method is as follows: Mark the sea area covered by the minimum cost path of all actual rescue vessels as the rescue sea area, divide the rescue sea area into grid cells evenly, obtain the grid cells passed by the minimum cost path of each actual rescue vessel, and if there is a grid cell in which more than 1 actual rescue vessels pass, mark the grid cell as a coordinate obstacle cell. Obtain the expected obstruction time windows of all actual rescue vessels passing through the coordinate obstruction unit on the coordinate obstruction unit, determine whether there are overlapping periods in the expected obstruction time windows, and if so, determine that the actual rescue vessels corresponding to the expected obstruction time windows with overlapping periods are obstructed in parallel.

5. The ship dynamic tracking method based on BeiDou positioning according to claim 4, characterized in that: The method for obtaining the expected time window of disruption is as follows: Obtain the actual rescue vessel that passes through the coordinate obstacle cell via the minimum cost path, set the departure time for the actual rescue vessel, and calculate the arrival time of the actual rescue vessel at the coordinate obstacle cell by combining the departure time and the minimum cost path. Mark this as the expected obstacle time of the actual rescue vessel. Expand the expected obstacle time into an expected obstacle time window with the expected obstacle time as the midpoint to obtain the expected obstacle time window of the actual rescue vessel on the coordinate obstacle cell.

6. The ship dynamic tracking method based on BeiDou positioning according to claim 5, characterized in that: The manner in which coordination is hindered is as follows: For actual rescue vessels that are simultaneously hindered, the duration of the overlapping period of the expected hinderment time windows of the two actual rescue vessels is obtained and marked as the duration of the hinderment between the two actual rescue vessels; Actual rescue vessels that are obstructing each other are grouped into the same obstruction coordination group. The actual rescue vessels in the same obstruction coordination group are sorted according to priority to obtain an obstruction coordination sequence. Obstruction coordination is carried out on two adjacent actual rescue vessels in the obstruction coordination sequence in sequence. For the first pair of adjacent actual rescue vessels in the obstruction coordination sequence, the departure time of the later actual rescue vessel is postponed for a period of time equal to the obstruction time between the two target rescues. The departure time of the next actual rescue vessel is then changed based on the postponed departure time.

7. A ship dynamic tracking system based on BeiDou positioning, based on the ship dynamic tracking method based on BeiDou positioning as described in any one of claims 1 to 6, characterized in that: include: Dynamic tracking alarm module: The ship uses a shipborne Beidou satellite receiver to determine the ship's location in real time and determine whether a ship emergency alarm has been triggered. If triggered, the distressed ship is marked and the emergency alarm information is sent to the Beidou integrated application service platform. Hazard Analysis and Location Module: Based on the received hazard alarm information, the Beidou Integrated Application Service Platform locates the distressed vessel on the electronic nautical chart, marks the hazard range, and tracks and queries surrounding vessels or global marine meteorological models to generate a vector ocean field of the hazard range. Based on the vector ocean field, a particle filter algorithm is used to predict the high probability drift zone of the distressed vessel. The distress tracking and analysis module tracks and prepares rescue vessels for distressed ships, generates minimum-cost paths for these vessels based on high-probability drift zones, calculates their estimated arrival time using vector ocean fields and prioritizes them, and generates a list of prepared rescue vessels. The distress vessel identification module sends distress requests to the reserve rescue vessels based on the reserve rescue vessel list, marks the actual rescue vessels based on the responses from the reserve rescue vessels, and performs parallel obstruction detection and obstruction coordination for the actual rescue vessels.

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