Ship relative positioning adjustment method and device based on multi-source fusion and electronic equipment

Abstract

The application relates to a ship relative positioning adjustment method and device based on multi-source fusion and electronic equipment, and the method comprises the following steps: acquiring target point information, the target point information being a coordinate in a preset local Cartesian coordinate system; acquiring global navigation satellite system positioning data of a slave ship and acquiring relative ranging data between the slave ship and a reference ship tail center point measured by a laser range finder; based on the positioning data and the relative ranging data, respectively solving a first estimated position and a second estimated position of the slave ship in the local Cartesian coordinate system; inputting the first estimated position and the second estimated position into a Kalman filter for data fusion to obtain a fused position of the slave ship in the local Cartesian coordinate system; and generating a control instruction to adjust the power system of the slave ship according to the position deviation between the fused position and the target point information. The application realizes high-precision relative positioning, and can still maintain effective positioning when communication is temporarily interrupted.

Description

Technical Field

[0001] This invention relates to the field of ship navigation and positioning technology, and in particular to a ship relative positioning adjustment method, device and electronic equipment based on multi-source fusion. Background Technology

[0002] In salvage and rescue operations (such as shipwreck lifting and personnel transfer) and marine engineering construction (such as offshore wind power installation and subsea pipeline laying), multiple vessels (such as mother ships, crane ships, and construction support vessels) are typically required to conduct high-precision collaborative operations in close proximity. These operations place extremely stringent requirements on the relative positioning accuracy between vessels. For example, in scenarios such as offshore wind power foundation hoisting, construction vessels and crane ships need to maintain a relative positional deviation at the centimeter level to ensure operational safety and efficiency. To achieve vessel platooning and collaborative operations, various solutions have been proposed. One typical solution is to enhance environmental perception and platooning control capabilities through multi-sensor data fusion. For instance, patent application CN120469422A discloses an intelligent vessel platooning navigation control method. This method collects multi-source data through Automatic Identification System (AIS) sensors, weather radar echo sensors, and underwater sonar detection sensors, and combines satellite communication and VHF communication for data transmission. Finally, it uses a deep hybrid network model (H-Net) to fuse the data and extract features for navigation control and formation maintenance of ship formations. The formation maintenance deviation threshold is usually set at the meter level (e.g., ±3 meters).

[0003] However, this type of solution has significant limitations when applied to specific high-precision operational scenarios such as salvage and rescue, and marine engineering construction. First, its positioning accuracy cannot meet the requirements. These solutions typically use AIS sensors as the core positioning data source, but the positioning data provided by AIS has limited accuracy, usually ±5-10 meters, which is far lower than the centimeter or decimeter-level accuracy required for salvage and rescue (within ±0.5 meters) and marine engineering construction (within ±0.3 meters). Directly relying on this level of accuracy for relative position control can easily lead to collision risks during precision lifting, equipment docking, and other operations, causing significant economic losses. Second, this solution does not construct a dedicated coordinate system suitable for short-distance, high-precision calculations. It typically uses the latitude and longitude coordinates provided by AIS directly to calculate the relative positions and distances between ships. Within a short operational range (e.g., several hundred meters), factors such as the curvature of the Earth and projection distortion introduce non-negligible calculation errors. For example, when two ships are 300 meters apart, the relative distance calculation error due to coordinate system issues alone can reach 8-12 meters. This severely distorts the calculated relative position, making it unsuitable for accurately guiding high-precision operations. Furthermore, its communication architecture lacks robustness, making it difficult to guarantee the continuity of positioning. Despite employing dual-mode communication, it lacks an effective data compensation and positioning maintenance mechanism in the event of communication link interruptions (such as strong electromagnetic interference or signal blockage). Once communication with the reference ship is interrupted, subordinate ships cannot obtain crucial reference position information, causing the relative positioning link to immediately fail. In critical operational phases such as salvage and rescue, such interruptions can directly lead to loss of ship attitude control and safety accidents. These scenarios typically require the system to have several minutes of communication-free fault tolerance. In addition, there is a mismatch between the sensor configuration and the requirements of the target scenario. The equipped weather radar, underwater sonar, and other sensors primarily serve environmental perception and obstacle avoidance during navigation in open waters, rather than the core task of "close-range, high-precision relative positioning." In complex environments such as ports and nearshore areas, these sensors are susceptible to interference, while sensors that can directly and accurately measure the distance and angle between ships (such as high-precision laser rangefinders), which are urgently needed to achieve high-precision relative positioning, have not been included in the core data acquisition system. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, device, and electronic equipment for adjusting ship relative positioning based on multi-source fusion, which addresses the current difficulty in achieving and maintaining centimeter-level high-precision relative positioning in extremely demanding operational scenarios such as salvage and rescue and marine engineering construction, while also maintaining effective positioning during temporary communication interruptions.

[0005] This invention provides a method for adjusting the relative positioning of ships based on multi-source fusion, the method comprising: Obtain target point information, which is the coordinates of the target operation point of the ship in a preset local Cartesian coordinate system, wherein the local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the heading of the reference ship as the positive X-axis. The system acquires the ship's own global navigation satellite system positioning data and the relative distance data between the center point of the stern of the reference ship and the reference ship, measured by a laser rangefinder. Based on the positioning data and the relative ranging data, the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system are calculated respectively. The first estimated position and the second estimated position are input into a Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system. Based on the positional deviation between the fused position and the target point information, control commands are generated to adjust the power system of the slave ship. When the slave ship cannot obtain the updated information provided by the reference ship, the Kalman filter makes a prediction based on the relative ranging data and historical status to maintain the validity of the fused position.

[0006] In one embodiment, the relative ranging data includes the straight-line distance between the center point of the stern of the slave ship and the reference ship, measured by the laser rangefinder. and the angle between the laser beam and the direction from the bow. The step of calculating the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system based on the positioning data and the relative ranging data includes: Based on the positioning data, the real-time latitude and longitude coordinates of the ship will be... Converted to coordinates relative to the center point of the stern of the reference ship. latitude and longitude difference The first estimated position is calculated using the following formula. : , , In the formula, The average radius of the Earth; Based on the straight-line distance Angle and the bow angle between the ship and the reference ship. The second estimated position is calculated using the following formula. : .

[0007] In one embodiment, the state vector of the Kalman filter is defined as ,in, , Let k be the position of the ship in the local Cartesian coordinate system at time k. , The rate of change of position; The state transition equation of the Kalman filter is: Among them, state transition shift matrix , The sampling period is This is the process noise vector.

[0008] In one embodiment, the observation equation of the Kalman filter is: , where the observation vector Observation matrix , For the observed noise vector; The observed noise vector covariance matrix The settings are as follows: the observation noise variance corresponding to the first estimated position is 0.5, and the observation noise variance corresponding to the second estimated position is 0.0025, i.e. .

[0009] In one embodiment, when the slave ship cannot obtain updated information provided by the reference ship, the Kalman filter makes a prediction based on the relative ranging data and historical states, including: Stop inputting observations calculated based on the location data; State prediction is performed based on the state transition matrix and the state estimate from the previous time step: ; The process noise vector is corrected based on the rate of change of the relative ranging data. covariance matrix To maintain positioning accuracy for a preset period of time after network outage.

[0010] In one embodiment, generating control commands to adjust the slave ship's propulsion system based on the positional deviation between the fused position and the target point information includes: Calculate the fused position Information on target locations Position deviation in the local Cartesian coordinate system: , ; like or Then, control commands are generated to adjust the speed of the ship's propellers.

[0011] In one embodiment, the method further includes: Obtain the current heading angle of the ship. With the target heading angle And calculate the orientation deviation. Wherein, the target heading angle relative to the bow of the reference ship Consistent; if Then, control commands are generated to adjust the rudder heading of the slave ship.

[0012] In one embodiment, obtaining the target location information includes: Receive target latitude and longitude coordinates sent by the reference ship ; Based on the coordinates of the center point of the stern of the reference ship and the target latitude and longitude coordinates The target point information is obtained by conversion using the following formula. : , , , ,in, This is the average radius of the Earth.

[0013] In one embodiment, the XY plane of the preset local Cartesian coordinate system is parallel to the deck plane of the reference ship.

[0014] The present invention also provides a ship relative positioning adjustment device based on multi-source fusion, the device comprising: The communication module is used to acquire target location information, which is the coordinates of the target operation point of the ship in a preset local Cartesian coordinate system, wherein the local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the bow direction of the reference ship as the positive X-axis. The data acquisition module is used to acquire the ship's own global navigation satellite system positioning data and to acquire the relative distance data between the center point of the stern of the ship and the reference ship, measured by a laser rangefinder. The data processing module is used to calculate the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system based on the positioning data and the relative ranging data. The data fusion module, with a built-in Kalman filter, is used to fuse the first estimated position and the second estimated position to obtain the fused position of the ship in the local Cartesian coordinate system. The control module is used to generate control commands to adjust the power system of the slave ship based on the positional deviation between the fused position and the target point information; wherein, the data fusion module is configured to: when the communication module cannot obtain the updated information provided by the reference ship, control the Kalman filter to make predictions based on the relative ranging data and historical states to maintain the validity of the fused position.

[0015] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the ship relative positioning adjustment method based on multi-source fusion as described above.

[0016] The aforementioned ship relative positioning adjustment method, device, and electronic equipment based on multi-source fusion first establishes a local Cartesian coordinate system with the center point of the stern of the reference ship as the origin and its bow direction as the positive X-axis. This ensures that all position calculations are performed based on this unified coordinate system parallel to the working plane, eliminating significant errors introduced by the Earth's curvature and projection distortion when directly using geographic latitude and longitude coordinates for short-distance calculations. This provides an accurate mathematical foundation for high-precision relative positioning. Furthermore, it synchronously acquires its own Global Navigation Satellite System (GNSS) positioning data and relative distance data between itself and the center point of the reference ship's stern measured by a laser rangefinder. This integrates the absolute position reference of the GNSS with the high-precision relative distance and angle information from laser ranging, specifically replacing the traditional, insufficiently accurate AIS sensor data source. This directly addresses the stringent requirements for centimeter-level positioning accuracy in salvage and rescue, and marine engineering construction scenarios. Furthermore, by inputting the first and second estimated positions calculated from the two types of data respectively into a Kalman filter for data fusion, noise and abnormal fluctuations from a single data source can be effectively suppressed. Utilizing the optimal estimation characteristics of the Kalman filter, the accuracy and stability of the fused position are improved, thereby raising the relative positioning accuracy to a level far exceeding that of AIS sensors. In particular, a contingency mechanism is in place for situations where updated information from a reference ship cannot be obtained (e.g., communication interruption). The Kalman filter then uses continuously acquired laser relative ranging data and historical status for prediction, ensuring that the system can maintain effective relative positioning output for a period of time even in the event of communication link failure. This avoids immediate interruption of positioning and enhances the continuity and safety of the operation. Finally, dynamic control is applied based on the deviation between the fused high-precision, high-stability position and the target point, enabling precise and smooth ship position adjustments. Overall, through a series of synergistic technical means such as coordinate system optimization, high-precision dual-source data fusion, dynamic filtering and noise reduction, and network outage prediction and fault tolerance, the system systematically solves the problems of insufficient positioning accuracy, large coordinate system error, failure upon communication interruption, and mismatch between sensor configuration and scenario requirements in the current solution. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a ship relative positioning adjustment method based on multi-source fusion, as an example. Figure 2This is a schematic diagram of a ship relative positioning adjustment device based on multi-source fusion, as shown in one embodiment. Figure 3 This is an internal structural diagram of an electronic device according to one embodiment. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The following is combined with Figures 1-3 This invention describes a ship relative positioning adjustment method, apparatus, and electronic device based on multi-source fusion.

[0021] like Figure 1 As shown, in one embodiment, a ship relative positioning adjustment method based on multi-source fusion includes the following steps: Step S110: Obtain target point information, which is the coordinates of the target operation point from the ship in a preset local Cartesian coordinate system.

[0022] In this local Cartesian coordinate system, the origin is the center point of the stern of the reference ship involved in the collaborative operation, and the positive X-axis is the bow direction of the reference ship. Specifically, the process of acquiring target point information is performed by the slave ship. The target point information consists of the coordinates of the target operation point of the slave ship in the preset local Cartesian coordinate system. The establishment process of this coordinate system is as follows: the reference ship acquires its own center latitude and longitude coordinates through its GNSS (Global Navigation Satellite System) receiver. as high as the earth Simultaneously, the ship uses a lidar system (sampling frequency 10Hz) to scan its stern feature points, and combines this with hull line data to calculate the precise latitude and longitude coordinates of the stern center point. The reference ship's heading (i.e., the positive X-axis direction) is determined by its GNSS heading angle. Determined; subsequently, a local Cartesian coordinate system O-XY is established with the center point of the stern as the origin O, where the positive direction of the X-axis is along the bow of the reference ship (i.e., from the stern to the bow), the Y-axis is perpendicular to the X-axis and has a positive direction along the port side of the reference ship, and the XY plane of this coordinate system is parallel to the deck plane of the reference ship; this construction process receives and utilizes the coordinates of the origin provided by the reference ship from the ship's side. With heading information; before operations, the target operation point coordinates of the vessel are set in this O-XY coordinate system according to the collaborative operation requirements. And convert the local coordinates into latitude and longitude coordinates. For transmission, the conversion process is as follows: first convert the local coordinates... Directly mapped to Cartesian coordinate increments Then use the formula and Convert the plane increment to latitude and longitude increments, where The average radius of the Earth (e.g.) (meters), finally passed and Obtain the target latitude and longitude. The reference ship transmits the latitude and longitude coordinates via wireless communication links (such as BeiDou short message service and 4G / 5G dual backup). The target's latitude and longitude are sent to the slave ship. After receiving the target's latitude and longitude, the slave ship uses the known coordinates of the reference ship's stern origin. Through reverse calculation (i.e. Then through and Finally, the target location information is obtained. This process, by establishing a local Cartesian coordinate system parallel to the working plane and based on the reference ship, fundamentally eliminates the significant errors caused by the curvature of the earth when directly using geographical latitude and longitude to calculate short-distance relative positions (for example, avoiding an error of 8-12 meters at a distance of 300 meters). It provides an accurate and unified mathematical reference framework for centimeter-level high-precision positioning and can accurately describe the relative orientation relationships between ships.

[0023] Step S120: Obtain the ship's own global navigation satellite system positioning data and obtain the relative distance data between the center point of the stern of the ship and the reference ship measured by a laser rangefinder.

[0024] The relative distance measurement data specifically includes straight-line distance. and the angle between the laser beam and the direction from the bow. Laser rangefinders have - The measurement range of meters and With an accuracy of meters, this constitutes a high-precision laser ranging observation source, used to compensate for the insufficient accuracy of single GNSS data.

[0025] Step S130: Based on the positioning data and relative ranging data, calculate the first estimated position and the second estimated position of the ship in the local Cartesian coordinate system, respectively.

[0026] The specific solution process is as follows: For the first estimated position First, obtain the ship's real-time latitude and longitude from the GNSS receiver. Calculate its position relative to the stern of the reference ship. latitude and longitude difference Then through the formula and Transform to the O-XY coordinate system; for the second estimated position Then, laser ranging data is used, combined with the bow angle between the ship and the reference ship. (Calculated using the GNSS heading angles of both sides) ,in (For reference ship heading angle), first set the laser beam angle. Transform to the angle relative to the X-axis of the coordinate system Then through the formula and Calculations are performed. Simultaneously, the initial positional deviations based on different data sources before fusion are also calculated: , as well as , This process combines the absolute position reference of GNSS with the high-precision relative geometric relationship of laser ranging, generating two position estimates with different error characteristics in a unified local coordinate system.

[0027] Step S140: Input the first estimated position and the second estimated position into the Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system.

[0028] The specific model of the Kalman filter is as follows: the state vector at time k is defined as... ,in, , To determine the position of the ship in the local Cartesian coordinate system, , The rate of change of position (velocity); the state transition equation of the Kalman filter is Among them, state transition matrix , The sampling period can be taken as... Second, It is the process noise vector. It follows a pattern with a mean of 0 and a covariance matrix of . Gaussian distribution, covariance matrix Set as Its observation equation is: , where the observation vector Observation matrix , It is observation noise Vector, whose covariance matrix Based on the different accuracy settings of GNSS and laser ranging, the following settings are used. GNSS observation noise variance (Approximately 5 meters error) and laser observation noise variance (Approximately 0.05 meters error); The iterative calculation of the Kalman filter includes a prediction step: state prediction. and prediction error covariance update ; and update step: calculate Kalman gain This leads to an update of the state estimate. and error covariance Ultimately from Extract the fused position This data fusion process effectively suppresses noise fluctuations and random errors in GNSS signals through the optimal estimation characteristics of the Kalman filter, and assigns greater weight to high-precision laser ranging data. This improves the relative positioning accuracy from ±5-10 meters (reliant on AIS) to within ±0.3 meters, meeting the high-precision operational requirements of salvage and rescue (within ±0.5 meters) and marine engineering construction (within ±0.3 meters). Simultaneously, it significantly improves the stability of positioning data, reducing the positioning standard deviation from 2-5 meters to within 0.1 meters, thus reducing the frequency of ineffective adjustments and energy consumption of the power system. Specifically, when updated information from the reference ship cannot be obtained from the ship (e.g., communication interruption) or the GNSS signal fails, the Kalman filter makes predictions based on relative ranging data and historical states to maintain the validity of the fused position. The specific mechanism is to stop calculating observations based on GNSS positioning data (i.e.,...). In Input, relying solely on laser ranging observations And use the state transition matrix to predict the state, that is, execute At this time, the Kalman gain The calculation and state update process is paused, and the filtering mainly operates in prediction mode. At the same time, the process noise covariance matrix is ​​dynamically corrected based on the rate of change of the laser ranging data. It adaptively reflects the increase in prediction uncertainty, thereby ensuring that the prediction error of the fused position can be constrained to within 0.5 meters for at least 5 minutes after communication or GNSS signal interruption. This overcomes the problem that the positioning fails immediately after the link failure of traditional technology, and ensures the communication-free fault tolerance and operational continuity required for critical operation stages such as salvage and rescue.

[0029] Step S150: Based on the positional deviation between the fused position and the target point information, generate control commands to adjust the power system of the slave ship.

[0030] The specific control logic is as follows: First, calculate the position deviation. and ,like or Then, control commands are generated to adjust the speed of the ship's lateral and longitudinal thrusters to gradually reduce the positional deviation; simultaneously, the method also includes obtaining the ship's current heading angle. With the target heading angle ( Compared with the reference ship's bow direction Consistent), calculate orientation deviation ,like The system then generates control commands to adjust the ship's rudder to correct its course. The entire adjustment process is continuously performed at a sampling frequency of 10Hz, ensuring real-time control and achieving high accuracy in ship heading control. Ultimately, this achieves precise and stable maintenance of both the ship's position and orientation relative to the target point in the local coordinate system, thereby improving the efficiency and safety of collaborative operations such as hoisting and docking.

[0031] The following describes the ship relative positioning adjustment device based on multi-source fusion provided by the present invention. The ship relative positioning adjustment device based on multi-source fusion described below and the ship relative positioning adjustment method based on multi-source fusion described above can be referred to in correspondence.

[0032] like Figure 2 As shown, in one embodiment, a ship relative positioning adjustment device based on multi-source fusion includes a communication module 210, a data acquisition module 220, a data processing module 230, a data fusion module 240, and a control module 250.

[0033] The communication module 210 is used to acquire target point information, which is the coordinates of the target operation point from the ship in a preset local Cartesian coordinate system. The local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the heading of the reference ship as the positive X-axis direction.

[0034] The data acquisition module 220 is used to acquire the ship's own global navigation satellite system positioning data and to acquire the relative distance data between the center point of the stern of the ship and the reference ship, measured by a laser rangefinder.

[0035] The data processing module 230 is used to calculate the first estimated position and the second estimated position of the ship in the local Cartesian coordinate system based on the positioning data and the relative ranging data.

[0036] The data fusion module 240 has a built-in Kalman filter for fusing the first estimated position and the second estimated position to obtain the fused position of the ship in the local Cartesian coordinate system.

[0037] The control module 250 is used to generate control commands to adjust the power system of the slave ship based on the positional deviation between the fused position and the target point information. The data fusion module is configured to control the Kalman filter to make predictions based on relative ranging data and historical states when the communication module cannot obtain updated information provided by the reference ship, so as to maintain the validity of the fused position.

[0038] Figure 3 This example illustrates a schematic diagram of the physical structure of an electronic device, which can be a smart terminal. Its internal structure diagram can be as follows: Figure 3 As shown. The electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a multi-source fusion-based ship relative positioning adjustment method, which includes: Obtain target point information, which is the coordinates of the target operation point from the ship in a preset local Cartesian coordinate system. The local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the bow direction of the reference ship as the positive X-axis. Acquire the ship's own global navigation satellite system positioning data, and acquire the relative distance data between the center point of the stern of the ship and the reference ship measured by a laser rangefinder; Based on the positioning data and the relative ranging data, the first estimated position and the second estimated position of the ship in the local Cartesian coordinate system are calculated respectively. The first and second estimated positions are input into a Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system. Based on the positional deviation between the fused position and the target point information, control commands are generated to adjust the ship's power system. When the ship cannot obtain updated information from the reference ship, the Kalman filter makes predictions based on relative ranging data and historical states to maintain the validity of the fused position.

[0039] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the electronic device to which the present invention is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0040] On the other hand, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements a ship relative positioning adjustment method based on multi-source fusion, the method comprising: Obtain target point information, which is the coordinates of the target operation point from the ship in a preset local Cartesian coordinate system. The local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the bow direction of the reference ship as the positive X-axis. Acquire the ship's own global navigation satellite system positioning data, and acquire the relative distance data between the center point of the stern of the ship and the reference ship measured by a laser rangefinder; Based on the positioning data and the relative ranging data, the first estimated position and the second estimated position of the ship in the local Cartesian coordinate system are calculated respectively. The first and second estimated positions are input into a Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system. Based on the positional deviation between the fused position and the target point information, control commands are generated to adjust the ship's power system. When the ship cannot obtain updated information from the reference ship, the Kalman filter makes predictions based on relative ranging data and historical states to maintain the validity of the fused position.

[0041] In another aspect, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, it implements a multi-source fusion-based method for ship relative positioning adjustment, the method comprising: Obtain target point information, which is the coordinates of the target operation point from the ship in a preset local Cartesian coordinate system. The local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the bow direction of the reference ship as the positive X-axis. Acquire the ship's own global navigation satellite system positioning data, and acquire the relative distance data between the center point of the stern of the ship and the reference ship measured by a laser rangefinder; Based on the positioning data and the relative ranging data, the first estimated position and the second estimated position of the ship in the local Cartesian coordinate system are calculated respectively. The first and second estimated positions are input into a Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system. Based on the positional deviation between the fused position and the target point information, control commands are generated to adjust the ship's power system. When the ship cannot obtain updated information from the reference ship, the Kalman filter makes predictions based on relative ranging data and historical states to maintain the validity of the fused position.

[0042] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0043] By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0044] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0045] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for adjusting the relative positioning of a ship based on multi-source fusion, characterized in that, The method includes: Obtain target point information, which is the coordinates of the target operation point of the ship in a preset local Cartesian coordinate system, wherein the local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the heading of the reference ship as the positive X-axis. The system acquires the ship's own global navigation satellite system positioning data and the relative distance data between the center point of the stern of the reference ship and the reference ship, measured by a laser rangefinder. Based on the positioning data and the relative ranging data, the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system are calculated respectively. The first estimated position and the second estimated position are input into a Kalman filter for data fusion to obtain the fused position of the ship in the local Cartesian coordinate system. Based on the positional deviation between the fused position and the target point information, control commands are generated to adjust the power system of the slave ship. When the slave ship cannot obtain the updated information provided by the reference ship, the Kalman filter makes a prediction based on the relative ranging data and historical status to maintain the validity of the fused position. The state vector of the Kalman filter is defined as follows: ,in, , Let k be the position of the ship in the local Cartesian coordinate system at time k. , The rate of change of position; The state transition equation of the Kalman filter is: , where the state transition matrix , The sampling period is This is the process noise vector; The Kalman filter makes predictions based on the relative ranging data and historical states, including: Stop inputting observations calculated based on the location data; State prediction is performed based on the state transition matrix and the state estimate from the previous time step: ; The process noise vector is corrected based on the rate of change of the relative ranging data. covariance matrix To maintain positioning accuracy for a preset period of time after network outage.

2. The ship relative positioning adjustment method based on multi-source fusion according to claim 1, characterized in that, The relative distance measurement data includes the straight-line distance between the center point of the stern of the slave ship and the reference ship, measured by the laser rangefinder. and the angle between the laser beam and the direction from the bow. ; The step of calculating the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system based on the positioning data and the relative ranging data includes: Based on the positioning data, the real-time latitude and longitude coordinates of the ship will be... Converted to coordinates relative to the center point of the stern of the reference ship. latitude and longitude difference The first estimated position is calculated using the following formula. : ， ， In the formula, The average radius of the Earth; Based on the straight-line distance Angle and the bow angle between the ship and the reference ship. The second estimated position is calculated using the following formula. : 。 3. The ship relative positioning adjustment method based on multi-source fusion according to claim 1, characterized in that, The observation equation of the Kalman filter is as follows: , where the observation vector Observation matrix , For the observed noise vector; The observed noise vector covariance matrix The settings are as follows: the observation noise variance corresponding to the first estimated position is 0.5, and the observation noise variance corresponding to the second estimated position is 0.0025, i.e. .

4. The ship relative positioning adjustment method based on multi-source fusion according to claim 1, characterized in that, The step of generating control commands to adjust the power system of the slave ship based on the positional deviation between the fused position and the target point information includes: Calculate the fused position Information on target locations Position deviation in the local Cartesian coordinate system: , ; like or Then, control commands are generated to adjust the speed of the ship's propellers.

5. The ship relative positioning adjustment method based on multi-source fusion according to claim 4, characterized in that, The method further includes: Obtain the current heading angle of the ship. With the target heading angle And calculate the orientation deviation. Wherein, the target heading angle relative to the bow of the reference ship Consistent; if Then, control commands are generated to adjust the rudder heading of the slave ship.

6. The ship relative positioning adjustment method based on multi-source fusion according to claim 1, characterized in that, The acquisition of target location information includes: Receive target latitude and longitude coordinates sent by the reference ship ; Based on the coordinates of the center point of the stern of the reference ship and the target latitude and longitude coordinates The target point information is obtained by conversion using the following formula. : ， ， , ,in, This is the average radius of the Earth.

7. The ship relative positioning adjustment method based on multi-source fusion according to claim 1, characterized in that, The XY plane of the preset local Cartesian coordinate system is parallel to the deck plane of the reference ship.

8. A ship relative positioning adjustment device based on multi-source fusion, characterized in that, The device includes: The communication module is used to acquire target location information, which is the coordinates of the target operation point of the ship in a preset local Cartesian coordinate system, wherein the local Cartesian coordinate system takes the center point of the stern of the reference ship for collaborative operation as the origin and the bow direction of the reference ship as the positive X-axis. The data acquisition module is used to acquire the ship's own global navigation satellite system positioning data and to acquire the relative distance data between the center point of the stern of the ship and the reference ship, measured by a laser rangefinder. The data processing module is used to calculate the first estimated position and the second estimated position of the vessel in the local Cartesian coordinate system based on the positioning data and the relative ranging data. The data fusion module, with a built-in Kalman filter, is used to fuse the first estimated position and the second estimated position to obtain the fused position of the ship in the local Cartesian coordinate system. The control module is used to generate control commands to adjust the power system of the slave ship based on the positional deviation between the fused position and the target point information. The data fusion module is configured to: when the communication module cannot obtain the updated information provided by the reference ship, control the Kalman filter to make predictions based on the relative ranging data and historical status, so as to maintain the validity of the fused position; The state vector of the Kalman filter is defined as follows: ,in, , Let k be the position of the ship in the local Cartesian coordinate system at time k. , The rate of change of position; The state transition equation of the Kalman filter is: , where the state transition matrix , The sampling period is This is the process noise vector; The Kalman filter makes predictions based on the relative ranging data and historical states, including: Stop inputting observations calculated based on the location data; State prediction is performed based on the state transition matrix and the state estimate from the previous time step: ; The process noise vector is corrected based on the rate of change of the relative ranging data. covariance matrix To maintain positioning accuracy for a preset period of time after network outage.

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