Underwater positioning system and method based on mobile baseline

Abstract

The invention provides an underwater positioning system and method based on a mobile base line, and belongs to the technical field of underwater positioning, the scheme adopts a positioning strategy of a mobile base station, and breaks through the limitation that a traditional underwater sound positioning system depends on the layout of a fixed base station; according to the scheme, real-time time synchronization between the water surface base station and the underwater to-be-positioned target is realized through a Beidou signal and an internet access module, the synchronization method provides an effective solution for the problem that a traditional GNSS and an inertial navigation system fail underwater, the ultrasonic distance measurement calculation process is simplified, and the positioning accuracy is improved. The demand on computing resources and the dependence on complex environment monitoring are reduced, so that the accuracy and practicability of positioning are improved; finally, according to the scheme, multiple measurement data and relative pose changes are integrated by introducing a pose map optimization method, and higher-precision positioning is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater positioning, and in particular relates to an underwater positioning system and method based on a moving baseline. Background Art

[0002] Current underwater positioning technologies primarily rely on long baseline (LBL) and short baseline (SBL) systems. These two technologies are widely used in various underwater operations, but they have significant inherent flaws that restrict their performance and operational efficiency in complex environments. Specifically, they are:

[0003] Long baseline systems are known for their high precision, however, their limitations are primarily reflected in the layout of fixed base stations. Long baseline systems require the pre-deployment of multiple base stations on the surface or underwater. This fixed base station deployment not only requires a long preparation time and high initial investment, but also, once the base stations are deployed, the system's adaptability is extremely limited. In dynamic water environments, such as changes in water flow, fluctuations in lighting conditions, or rapid adjustments in mission requirements, fixed base stations cannot effectively respond to these changes, resulting in a possible decrease in positioning accuracy. In addition, this method of relying on fixed base stations is greatly limited in operational flexibility and cannot meet the needs of rapid deployment and emergency response. For example, when conducting marine scientific research or military diving missions, flowing water or sudden environmental changes may cause the information provided by fixed base stations to no longer be reliable, thereby affecting the safety and effectiveness of the overall operation.

[0004] While short-baseline positioning systems can achieve rapid response through rapid deployment in small-scale scenarios (such as enclosed space operations like industrial equipment inspection), their inherent technical shortcomings still pose significant limitations in complex operating conditions. Short-baseline systems typically use a small number of acoustic sensors. While this allows for quick system startup, the close proximity of the base stations and the relatively simple overall structure significantly limit their positioning accuracy and operating range. This is particularly true when targets are operating simultaneously, where the system struggles to overcome signal interference. Due to the large fluctuations in the target's position relative to the base station, dynamic real-time positioning can result in significant errors. This is particularly true in the presence of water flow or relative motion of underwater objects, where the baseline system's positioning algorithm often struggles to accurately track the target's actual position. To address complex aquatic environments, some traditional solutions may incorporate an inertial navigation system (INS) to improve positioning accuracy through inertial sensors. However, this approach still has numerous drawbacks. Inertial navigation systems are susceptible to accumulated sensor errors, resulting in reduced positioning accuracy after a period of operation. Furthermore, without real-time external calibration, errors can increase, impacting the overall stability and reliability of the system. Summary of the Invention

[0005] The embodiments of the present invention provide an underwater positioning system and method based on a moving baseline, which effectively solves the problems of environmental interference and insufficient positioning accuracy of traditional underwater acoustic positioning systems in complex waters, as well as the problem that most existing underwater acoustic positioning systems rely on a fixed base station layout, lack flexibility, and have difficulty in quickly adapting to complex underwater operating environments and different operating requirements. In addition, traditional GNSS positioning systems and inertial navigation positioning systems fail underwater, and time synchronization cannot be achieved when multiple devices work together.

[0006] According to a first aspect of an embodiment of the present invention, there is provided an underwater positioning system based on a moving baseline, comprising:

[0007] A central base station, wherein the central base station is connected to the underwater target to be located by wired communication; the central base station is used to aggregate data of the movable buoy base station and send data packets to the underwater target to be located during the positioning process, and the central base station specifically performs the following processing: when the underwater target to be located serves as a signal sender and the movable buoy base station serves as a signal receiver, the central base station receives the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located, and forwards them to the underwater target to be located for posture solution; when the movable buoy base station serves as a signal transmitter and the underwater target to be located serves as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for unpacking the ultrasonic signals of different movable buoy base stations and its own posture solution;

[0008] At least three movable buoy base stations, wherein the movable buoy base stations are used to obtain their own coordinates and ultrasonic ranging results to underwater targets to be located;

[0009] Among them, the posture solution of the underwater target to be positioned is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

[0010] Furthermore, the movable buoy base station includes a basic control board for communication functions and a core control board for signal and data processing; except that the core control board is set at the underwater target to be located, the rest of the composition and functions of the central base station are consistent with those of the movable buoy base station.

[0011] Furthermore, there is a wired communication connection between the basic control board and the core control board in the movable buoy base station, and a wired communication connection between the basic control board of the central base station and the core control board carried by the underwater target to be positioned, and the basic control board and the core control board of the movable buoy base station and the central base station realize time synchronization between the control boards based on the PTP precise time protocol.

[0012] Furthermore, the position coordinates of the underwater target to be located are obtained by the preset pose graph optimization method, specifically:

[0013] The position of the underwater target to be located, the orientation angle of the underwater target to be located, and the positions of each movable buoy base station are used as variable nodes; edges are constructed by combining the pre-constructed buoy distance constraint factor, IMU motion constraint factor, connection coordinate constraint factor, IMU orientation angle constraint factor, and sound speed smoothing constraint factor; and a factor graph is constructed based on the variable nodes and the constructed edges.

[0014] Based on the constructed factor graph, the loss function is constructed;

[0015] Based on the constructed loss function, the position coordinate estimation and orientation angle of the underwater target to be located are obtained through optimization solution.

[0016] Furthermore, the buoy distance constraint factor is specifically expressed as:

[0017] f range (X k ,M i ,s k )=||X k -M i || 2 -(s k ·t i ) 2

[0018] The IMU motion constraint factor is specifically expressed as:

[0019] f IMU (X k ,X k-1 ,v k ,Δt)=||X k -(X k-1 +v k Δt)|| 2 ;

[0020] The connected coordinate constraint factor is specifically expressed as:

[0021] f orientation (X k ,θ k , Xk-1 ,θ k-1 )=(θ k -atan2(y k -y k-1 , x k -x k-1 )) 2 ;

[0022] The IMU orientation angle constraint factor is specifically expressed as:

[0023] f IMU_orientation (θ k ,θ k-1 ,ω k ,Δt)=(θ k -(θ k-1 +ω k Δt)) 2 ;

[0024] The sonic smoothing constraint factor is specifically expressed as:

[0025] f velocity (s k ,s k-1 )=||s k -s k-1 || 2 ;

[0026] Among them, X k , M i They represent the position of the underwater target to be located at time k and the position of the i-th movable buoy base station, t i is the ultrasonic ranging transmission time between the underwater target to be located and the i-th movable buoy base station, X k ,X k-1 represents the three-dimensional position of the underwater target to be located at the current time k and the previous time k-1; x k ,y k , x k-1 ,y k-1 v represents the x-axis and y-axis coordinate values ​​of the underwater target to be located at the current moment k and the previous moment k-1 on the horizontal plane respectively; k represents the speed of the underwater target to be located at the kth moment, Δt represents the time step at the kth moment; θ k ,θ k-1 represents the heading angle of the underwater target to be located at the current time k and the previous time k-1; ω k represents the angular velocity of the underwater target to be located at the kth moment, s k Indicates the ultrasonic wave speed in the current water area at time k.

[0027] Furthermore, the loss function is specifically expressed as follows:

[0028]

[0029] Among them, J(X,θ,s) is the final loss function to be optimized, T is the time period, and M is the number of movable buoy base stations.

[0030] Furthermore, before the positioning task begins, any two movable buoy base stations are pre-selected, and an ultrasonic ranging process is performed between the two movable buoy base stations. The distance between the base stations and the ultrasonic transmission time are calculated based on the coordinates of the two movable buoy base stations; based on the distance between the base stations and the ultrasonic transmission time, the ultrasonic wave speed in the current water area is determined.

[0031] According to a second aspect of an embodiment of the present invention, a method for underwater positioning based on a moving baseline is provided, which is based on the above-mentioned underwater positioning system based on a moving baseline, and includes:

[0032] In response to the initialization instruction, controlling the movable buoy base station involved in positioning to perform initial deployment, and moving the movable buoy base station so that the underwater target to be positioned is located within the waters covered by the movable buoy base station;

[0033] When the underwater target to be located acts as a signal sender and the movable buoy base station acts as a signal receiver, the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located are received by the central base station, and forwarded to the underwater target to be located for posture solution. When the movable buoy base station acts as a signal sender and the underwater target to be located acts as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for distinguishing and parsing ultrasonic signals from different movable buoy base stations and its own posture solution.

[0034] Among them, the posture solution is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

[0035] According to a third aspect of an embodiment of the present invention, an electronic device is provided, comprising a memory, a processor, and a computer program stored and running on the memory, wherein when the processor executes the program, the underwater positioning method based on a moving baseline is implemented.

[0036] According to a fourth aspect of an embodiment of the present invention, a non-transitory computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the underwater positioning method based on a moving baseline is implemented.

[0037] One or more of the above technical solutions have the following beneficial effects:

[0038] The present invention provides an underwater positioning system and method based on a mobile baseline. By adopting a mobile base station, the solution breaks through the traditional underwater acoustic positioning system's dependence on fixed base stations, greatly improving the system's deployment flexibility. This innovation enables the positioning system to quickly adapt to dynamic water environments and rapidly changing operational requirements, avoiding the problems of long deployment and adjustment time and high costs faced by traditional positioning solutions.

[0039] The solution described in this invention achieves real-time time synchronization between a surface buoy base station and an underwater target to be located (i.e., the UUV (Unmanned Underwater Vehicle) in this embodiment) through a wired communication connection based on a network port module. This overcomes the limitations of traditional GNSS (Global Navigation Satellite System) and inertial navigation systems, which fail underwater. The solution described in this invention significantly simplifies the ultrasonic ranging calculation process, reduces reliance on complex environmental monitoring, and alleviates the burden on computing resources. This real-time synchronization not only improves positioning accuracy but also enables the system to maintain high positioning reliability even in harsh underwater conditions.

[0040] The proposed solution, through the introduction of a pose graph optimization method, provides a novel solution for integrating multiple measurement data and relative pose changes. This method effectively reduces errors introduced by dynamic factors such as water flow and target movement by dynamically updating and optimizing positioning data, ensuring that the system maintains high-precision positioning capabilities in complex waters. As the number of measurements increases, pose graph optimization continuously improves positioning accuracy, ensuring that the system consistently provides accurate position information during actual operations, which is crucial for performing precision operations and coordinating multi-tasking operations.

[0041] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0043] Figure 1 Schematic diagram of the structure of the underwater positioning system based on the moving baseline according to an embodiment of the present invention;

[0044] Figure 2Schematic diagram of the factor graph structure described in an embodiment of the present invention;

[0045] Figure 3 This is a workflow diagram of the underwater positioning method based on a moving baseline in the first signal transmission and reception mode described in an embodiment of the present invention;

[0046] Figure 4 This is a workflow diagram of the underwater positioning method based on a moving baseline under the second signal transmission and reception mode described in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0048] It should be noted that the terms used herein are for describing particular embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0049] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0050] To facilitate understanding of the innovation of this application, the following briefly describes traditional underwater positioning technology:

[0051] Traditional underwater positioning technology mainly relies on the hydroacoustic positioning system, which is widely used and mainly divided into long baseline (LBL) and short baseline (SBL) systems. The workflow and technical details of these two technical solutions are explained in detail below.

[0052] The workflow of a long baseline (LBL) positioning system begins with environmental preparation and base station deployment. First, multiple fixed base stations with known three-dimensional coordinates are pre-deployed in specific areas, either on the surface or underwater. In practice, these base stations are often composed of a combination of acoustic transmitters and receivers. Once deployed, the base stations communicate with underwater target devices by transmitting acoustic signals (pulsed or continuous). The underwater target device, equipped with both a receiver and a transmitter, determines its distance to each base station by receiving the acoustic signals from the base stations. During distance measurement, the underwater target device first records the time the acoustic signal is emitted and calculates the signal's arrival time. The device then uses the acoustic wave propagation speed (approximately 1500 m / s in water) to calculate the distance to each base station. Because the propagation speed of acoustic waves is affected by water temperature, salinity, and depth, in practical applications, the system requires real-time environmental monitoring to dynamically adjust the acoustic wave propagation speed. With the distance to the base stations known, the device determines its own position through triangulation. Specifically, the location of an underwater target is represented as a set of distances from multiple base stations. Using these known distances and the base station coordinates, the target's precise position can be determined by solving geometric equations. This process involves multi-lateration positioning algorithms, including the least squares method and nonlinear optimization. The system continuously updates position information to account for water currents and other dynamic changes.

[0053] Short baseline (SBL) positioning systems operate differently, primarily for use in small, dynamic environments. SBL systems typically employ a small number of acoustic sensors (usually two or three) mounted on an underwater device, which serve as base stations. Compared to LBL systems, SBL systems are characterized by relatively close base station locations, resulting in a simpler structure and faster deployment. During the process, the underwater device's acoustic sensors transmit acoustic signals into the water while simultaneously receiving return signals from other sensors, calculating the propagation time differences between the acoustic waves. By measuring these time differences and the known base station locations, the device can calculate its distance relative to these base stations. The underwater device's own processing unit uses this distance data, applying geometric theorems and triangulation principles, to calculate its precise position. This process typically occurs in real time, enabling the system to rapidly respond to environmental changes. To improve the positioning accuracy and adaptability of SBL systems, many modern approaches incorporate inertial navigation systems (INS). In addition to acoustic positioning, inertial sensors (such as accelerometers and gyroscopes) provide motion information for the device, mitigating positioning drift caused by water flow or external interference. Overall, underwater positioning technology, whether long-baseline or short-baseline systems, involves complex acoustic measurement and data processing to ensure efficient and accurate positioning services in a variety of underwater environmental conditions. These systems are widely used in fields such as ocean research, deep-sea exploration, marine engineering, and underwater robot navigation, providing critical technical support for underwater operations.

[0054] As shown in the background technology of this application, the problems existing in the above-mentioned traditional solutions are shown. Figure 1 As shown, this embodiment provides an underwater positioning system based on a moving baseline, including:

[0055] A central base station, wherein the central base station is connected to the underwater target to be located by wired communication; the central base station is used to aggregate data of the movable buoy base station and send data packets to the underwater target to be located during the positioning process, and the central base station specifically performs the following processing: when the underwater target to be located serves as a signal sender and the movable buoy base station serves as a signal receiver, the central base station receives the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located, and forwards them to the underwater target to be located for posture solution; when the movable buoy base station serves as a signal transmitter and the underwater target to be located serves as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for unpacking the ultrasonic signals of different movable buoy base stations and its own posture solution;

[0056] At least three movable buoy base stations, wherein the movable buoy base stations are used to obtain their own coordinates and ultrasonic ranging results to underwater targets to be located;

[0057] Among them, the posture solution of the underwater target to be positioned is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

[0058] In a specific implementation, the movable buoy base station includes a basic control board for communication functions and a core control board for signal and data processing; except that the core control board is set at the underwater target to be located, the rest of the composition and functions of the central base station are consistent with those of the movable buoy base station.

[0059] Specifically, taking three movable buoy base stations (understandably, there can also be four, five, six or more) as an example, the buoy base stations can be moved so that each base station is located as directly below the regular triangle as possible. This optimal layout can reduce the error caused by the array layout while covering the target water area. At the same time, the mobile buoy ensures that the underwater target is within the locatable water area, which can effectively solve the problem of limited positioning range of the traditional system. The underwater UUV (i.e., the underwater target to be located) serves as the mobile node of the coordinates to be measured, and completes the ultrasonic ranging process by sending and receiving ultrasonic signals with the movable buoy base station through the transducer module. The UUV needs to calculate the distance to three (or more) movable buoy base stations to obtain its own position and posture. The overall workflow is as follows:

[0060] Taking three mobile buoy base stations as an example, each one first initializes its modules and obtains its own coordinates through the Beidou module. Then, two control boards (the basic control board and the core control board) are connected internally via a network cable. Time synchronization between the two boards is achieved using PTP (Precision Time Protocol, IEEE 1588). Using a network card that supports PTP hardware timestamps, time synchronization accuracy can be achieved to sub-microsecond levels. The central base station uses the same method to synchronize time with the buoy base stations and the UUV. Beidou pulse signals are used to synchronize time between the three mobile buoy base stations. The ultrasonic transmission and reception frequency is set based on the Beidou pulse signal. This embodiment designs an adaptive ranging time interval, which is specifically implemented as follows: at the beginning, a larger time interval is first selected (to ensure that the next ultrasonic transmission and reception process is performed after the previous ultrasonic transmission and reception process is completed) as the ultrasonic signal transmission and reception frequency, and the distance from each buoy base station to the UUV is obtained by ultrasonic signal solution. Then, the ultrasonic transmission time from the farthest buoy to the UUV is calculated (which can be known from the sound wave transmission speed in the local waters). A time greater than or equal to this time and a multiple of the time base (the basic reference for system time measurement) is used as the ranging time interval. This time interval will be adaptively changed according to the movement of the UUV, ensuring that the next ranging signal transmission and reception is performed after the previous ultrasonic signal transmission and reception process between each buoy base station and the UUV is completed, so as to avoid the problem of inaccurate ranging results caused by sampling errors due to interference between multiple transmission and reception signals. After determining the ranging time interval, the mobile buoy base station and the central base station receive BeiDou pulse signals through their respective BeiDou modules. The microcomputer reads the pulse signals through the serial port, calculates the time interval based on these pulse signals, and issues an ultrasonic ranging command at each time interval. Because the core control board and the microcomputer board are time-synchronized, the core control board can control the transducer module to send and receive ultrasonic signals based on these time intervals. There are two specific options: one is for the mobile buoy base station to begin receiving ultrasonic signals at each time interval, and the underwater target to be located (i.e., the UUV) transmits ultrasonic signals at each time interval; the other is for the ultrasonic signal transmitter and receiver to exchange directions.If the first method is selected, after the three movable buoy base stations have successfully sampled and received the ultrasonic signal and performed distance calculation, the respective ranging results and coordinates are packaged into data packets through the communication module and transmitted to the basic control board of the central base station. The basic control board on the central base station transmits the aggregated data packets to the core control board deployed in the underwater target to be positioned (i.e., UUV) through the network port module using the network cable. After the core control board unpacks the data, it combines the coordinates of the three general buoys and the distance propagation time to itself with the IMU sensor data and brings them into the preset pose graph optimization algorithm for estimated pose solution. After the algorithm is iterated, the pose is estimated. The final estimated pose is obtained by generation, thus completing the entire positioning process; if the second method is selected, the three mobile base stations first send ultrasonic signals with their own ultrasonic ID numbers, and the central base station sends the ultrasonic ID number of each base station and its coordinates to the core control board deployed in the UUV through the network port module using the network cable. After the UUV receives the ultrasonic signals from the three base stations, it solves the ultrasonic signals based on the ID numbers, and obtains the coordinates of the three mobile buoy base stations and the distance propagation time to itself. Combined with the IMU sensor data, it is brought into the pose graph optimization algorithm for estimated pose solution, and the final estimated pose is obtained through algorithm iteration.

[0061] It should be noted here that the system described in this embodiment adopts a layered time synchronization architecture: first, a global unified microsecond time reference is established for all mobile base stations and central base stations through Beidou satellite pulse signal timing; on this basis, a precision synchronization system based on the IEEE 1588PTP protocol is deployed between each control board. Specifically: the basic control board and the core control board of the mobile buoy base station and the central base station are directly connected by a network cable and equipped with a dedicated network card that supports hardware timestamps, wherein: the basic control board serves as the PTP master clock, and the core control board serves as the PTP slave clock; the master clock periodically sends Sync synchronization messages and records the precise physical layer sending timestamp, and the slave clock captures the message arrival timestamp and then returns the Delay_Req delay request message. After receiving the message, the master clock records the timestamp and feedbacks the full-link timestamp data through the Delay_Resp response message; the slave clock calculates the master-slave clock offset and network path delay in real time based on the timestamp difference of the two-way message transmission, and adopts a closed-loop control algorithm to dynamically compensate for the clock phase error. This architecture effectively avoids the delay introduced by the operating system protocol stack through nanosecond-level hardware timestamp collection at the physical layer. Combined with direct network cable connection, it eliminates switch queue jitter. Field measurements have verified that the synchronization accuracy between control boards can be stably controlled in the range of 100 nanoseconds to 1 microsecond, providing a reliable technical foundation for high-precision measurement of ultrasonic propagation time (calculation of the difference between the receiving timestamp and the sending timestamp), meeting the extreme requirements of underwater acoustic positioning for timing accuracy.

[0062] In a specific implementation, there is a wired communication connection between the basic control board and the core control board in the movable buoy base station, there is a wired communication connection between the basic control board of the central base station and the core control board carried by the underwater target to be positioned, and the basic control board and the core control board of the movable buoy base station and the central base station realize time synchronization between the control boards based on the PTP protocol.

[0063] Specifically, the movable buoy base station includes a basic control board (i.e., a multi-serial port microcomputer board), a core control board, and other functional modules, such as a communication module, a Beidou satellite signal receiving chip (Beidou module), a transducer module, and a network port module. Since the movable buoy base station itself is an existing product, the connection relationship between its internal components will not be repeated here. In the movable buoy base station, the multi-serial port microcomputer board mainly undertakes the communication function. The multi-serial port microcomputer board is equipped with a Beidou module, a network port module, a control module, a communication module, and a multi-serial port microcomputer. Among them, the control module is responsible for receiving instructions from the multi-serial port microcomputer to realize the movement requirements of the buoy; the Beidou module is responsible for receiving Beidou pulse signals (pulse signals are used to unify subsequent multiple buoy base stations and UUV (Unmanned Underwater) Vehicle: ultrasonic signal receiving and transmitting frequency of unmanned underwater vehicle); the network port module is responsible for connecting to the network port module of the core control board through a network cable to achieve time synchronization and data transmission between the two control boards; the communication module is responsible for communication between buoy base stations to achieve data transmission between multiple buoy base stations, and the data includes the coordinates of each buoy base station and its respective ultrasonic ranging results; the multi-serial port microcomputer serves as the main control center and is responsible for multiple functions, including reading Beidou pulse signals through the serial port to control the receiving and transmitting frequency of ultrasonic signals, using the PTP protocol through the network port module to achieve time synchronization with the core control board, and realizing data transmission between multiple buoy base stations through the communication module. The core control board is mainly responsible for signal and data processing functions. The core control board is mainly equipped with a transducer module, a network port module, and a microcomputer. Among them, the network port module is used to connect to the network port module of the multi-serial port microcomputer board with a network cable to achieve time synchronization and data transmission. The transducer module is responsible for sending and receiving ultrasonic ranging signals. The microcomputer is responsible for signal and data processing, including achieving time synchronization and data transmission with the multi-serial port microcomputer board through the network port module, using the network cable to obtain the Beidou pulse signal to control the transducer module to send and receive ultrasonic signals, and processing the received ultrasonic signals to calculate the distance between the UUV and complete the ultrasonic ranging process and transmit the ranging results to the multi-serial port microcomputer board through the network port module.

[0064] Specifically, the central base station has roughly the same composition and functions as a mobile buoy base station, except for the core control board located on the underwater target to be located (using a UUV (Unmanned Underwater Vehicle) system as an example). In the central base station, the multi-serial port microcomputer board on the buoy serves as a data aggregation center. During the positioning process, if the buoy base station acts as an ultrasonic receiver, it will receive the ultrasonic ranging results and coordinates of multiple mobile buoy base stations and then send them to the UUV via the network port module to complete the subsequent position and posture solution. If the UUV acts as an ultrasonic receiver, the coordinates of each mobile buoy base station and its ultrasonic ID number will be sent to the UUV via the network port module to complete the subsequent position and posture solution. The core control board in the central base station system includes a control module, a sensor module, a transducer module, a network port module, and a microcomputer. The network port module and transducer module perform similar functions as those in the mobile buoy base station system. The network port module includes a multi-serial port microcomputer board located on the surface (buoy) and connected via a 1500-meter-long network umbilical cable. This provides time synchronization and data transmission. The transducer module transmits and receives ultrasonic signals. The control module receives control commands from the microcomputer to control the UUV's motion and attitude. The sensor module (including a pressure gauge, altimeter, camera, and IMU) acquires environmental and UUV motion information, providing the necessary data for control and final pose calculation. In addition to its functions in the mobile buoy base station system, the microcomputer also handles the UUV's motion and attitude control, receiving multiple buoy coordinates and ranging information from the multi-serial port microcomputer board via the network port module. The microcomputer then integrates the sensor module data (primarily IMU data) into the pose graph optimization algorithm for pose estimation.

[0065] In a specific implementation, the position coordinates of the underwater target to be located are obtained by the preset pose graph optimization method, specifically:

[0066] The position of the underwater target to be located, the orientation angle of the underwater target to be located, and the positions of each movable buoy base station are used as variable nodes; edges are constructed by combining the pre-constructed buoy distance constraint factor, IMU motion constraint factor, connection coordinate constraint factor, IMU orientation angle constraint factor, and sound speed constraint factor; and a factor graph is constructed based on the variable nodes and the constructed edges.

[0067] Based on the constructed factor graph, the loss function is constructed;

[0068] Based on the constructed loss function, the position coordinate estimation and orientation angle of the underwater target to be located are obtained through optimization solution.

[0069] Specifically, the posture optimization method includes the following processing steps:

[0070] (1) Constructing factor graph:

[0071] First, taking three movable buoy base stations as an example, the positions of the movable buoy base stations are known: M1 (x1, y1, z1), M2 (x2, y2, z2) and M3 (x3, y3, z3).

[0072] Variable node definition:

[0073] Position Node X k and X k-1 : They represent the three-dimensional position of the underwater target to be located at the current time k and the previous time k-1 respectively. For convenience, the following uses X node Indicates the three-dimensional position of the underwater target to be located.

[0074] Towards the corner node θ k and θ k-1 : They represent the orientation angles at the current moment and the previous moment respectively.

[0075] Position nodes M1, M2, M3 of the mobile buoy base station: These nodes represent the positions of the three buoys.

[0076] Constraint factor definition:

[0077] 1) Buoy distance constraint factor: connection position node X k and buoy position node M i , indicating the measurement distance constraint:

[0078] f range(i) =||X k -M i || 2 -(s k ·t i ) 2

[0079] Among them, X k Indicates the three-dimensional position of the underwater target to be located, M i represents the three-dimensional coordinates of the i-th movable buoy base station, s k represents the ultrasonic wave velocity in the current water area at time k, ti ​​represents the ultrasonic ranging transmission time between the underwater target to be located and the i-th movable buoy base station, specifically, t i is the ultrasonic propagation time directly measured by the PTP precision synchronization system, which is determined by the buoy emission time t send and the UUV receiving time t recv The precise calculation is as follows: i =t recv-t send .

[0080] Specifically, taking the first movable buoy base station as an example, its buoy distance constraint factor is expressed as:

[0081] f range(1) =||X k -M1|| 2 -(s k t1) 2 =0

[0082] Specifically expanded as follows:

[0083] (x k -x1) 2 +(x k -y1) 2 +(x k -z1) 2 -(s k t1) 2 =0

[0084] This can be used to obtain the distance constraint between each buoy and the underwater target to be located:

[0085] f range(1) =||X k -M1|| 2 -(s k t1) 2 =0

[0086] f range(2) =||X k -M2|| 2 -(s k t2) 2 =0

[0087] f range(3) =||X k -M3|| 2 -(s k t3) 2 =0

[0088] 2) IMU motion constraint factor: connects the connected position nodes and IMU data, indicating the displacement relationship caused by velocity:

[0089] The constraints provided by the IMU are established through position and velocity. The IMU data gives the velocity measurement, from which we get the displacement constraint:

[0090] X node (k) = X node (k-1)+v node (k-1)·Δt

[0091] Among them, v node is the speed of the underwater target to be located at the current moment.

[0092] This constraint indicates how the position of the underwater target to be located changes between two time points based on the previous time pose and velocity. Then the IMU motion constraint factor can be obtained as:

[0093] f IMU (X k ,X k-1 ,v k ,Δt)=||X k -(X k-1 +v k Δt)|| 2

[0094] Among them, v k is the speed of the underwater target to be located at the current moment.

[0095] 3) Connected coordinate constraint factor: connects the orientation angle node and the position node to ensure that the orientation and position changes are consistent.

[0096] First, calculate from X k-1 to X k The direction vector:

[0097] ΔX k =X k -X k-1 =(x k -x k-1 ,y k -y k-1 , z k -z k-1 )

[0098] Usually, we only calculate the heading angle in the horizontal plane (XY plane), so the z coordinate can be ignored. That is:

[0099]

[0100] Next, we can use the inverse tangent function to calculate the heading angle. The heading angle calculation formula is as follows:

[0101]

[0102] This formula gives the value from position X k-1 Point to position X k The angle of , usually, this angle refers to the angle with the x-axis. It can also be written as:

[0103] θ k =atan2(y k -yk-1 ,x k -x k-1 )

[0104] Next, we can obtain the corresponding constraint factors. Based on the previous heading angle estimate, we create factors to ensure that the heading angle is consistent with the buoy measurement and the dynamic model:

[0105] f orientation (X k ,θ k ,X k-1 ,θ k-1 )=(θ k -atan2(y k -y k-1 ,x k -x k-1 )) 2

[0106] 4) IMU heading angle constraint factor: This connects the connected heading angle nodes and IMU data to represent the heading angle relationship calculated by the IMU (the IMU heading angle constraint factor relates the heading angles at adjacent moments by integrating the angular velocity to suppress errors caused by gyroscope drift):

[0107] When we have two moments of orientation angle θ k-1 and θ k When, IMU can provide the angular velocity ω between two moments k =(ω x,k ,ω y,k ,ω z,k In this case, we can use the Euler integration method (or other angular velocity integration methods) to get the change in orientation.

[0108] Assume that our angular velocity ω at time k is k is known, then the change in orientation within a small time step Δt can be approximately expressed as:

[0109] θ k ≈θ k-1 +ω k Δt

[0110] This equation shows the effect of angular velocity on the current angle. k and θ k-1 is the orientation angle of the connected nodes.

[0111] Next, we can construct a factor to represent the constraint between these two heading angles. The heading constraint factor (measured by IMU) is defined as:

[0112] f IMU_orientation (θ k ,θk-1 ,ω k ,Δt)=(θ k -(θ k-1 +ω k Δt)) 2

[0113] 5) Sound velocity smoothing constraint factor, which specifically introduces a sound velocity change continuity constraint to suppress estimation jitter caused by sudden changes in the environment. This factor connects the sound velocity nodes at adjacent moments and is defined as:

[0114] f velocity (s k ,s k-1 )=||s k -s k-1 || 2

[0115] Among them, s k Indicates the ultrasonic wave speed in the current water area at time k.

[0116] This results in three variable nodes and five constraint factors, forming a factor graph as shown below: Figure 2 shown.

[0117] (2) Constructing the loss function

[0118] Based on the construction of the above factor graph, a total of four parts of the loss function can be obtained. The first is the loss function of the buoy distance constraint part:

[0119]

[0120] Wherein, M is the number of movable buoy base stations, which is set to 3 in this embodiment. It can be understood that the number of movable buoy base stations can also be an integer greater than 3. Xk represents the three-dimensional position of the underwater target to be located at time k, Mi is the position of the i-th movable buoy base station, and f range(i) (X k ,M i ) is the buoy distance constraint factor of the i-th movable buoy base station.

[0121] The loss functions of the remaining four parts are the constraint functions of the four parts listed above. The integration can be obtained as follows:

[0122]

[0123] Among them, J(X,θ,s) is the final loss function to be optimized, T is the time period, and M is the number of movable buoy base stations.

[0124] After obtaining the loss function, the final estimated pose can be solved using Newton's method. Newton's method is an iterative optimization algorithm suitable for solving nonlinear equations or optimization problems. The following example illustrates the core steps of pose graph optimization, using the optimization of state variables at two adjacent time steps (k-1 and k). In practical systems, the loss function J(X, θ, s) is the total cost function for the state at all time steps (k = 1 to T). Global optimization can be performed iteratively using incremental or batch optimizers (such as the Gauss-Newton method and the Levenberg-Marquardt algorithm). Incremental optimization typically maintains a sliding window (covering the state at the current time step and several previous time steps). Each time time step k is added, the state at time k-1 is considered (partially) known, and the relevant state variables within the window (e.g., k-1, k) or a longer time range are jointly optimized. Batch optimization optimizes the state at all time steps at once after sufficient data has been collected. This step description focuses on revealing how to use the measurement at the current moment k (acoustic ranging, IMU) and its constraint relationship with the state at the previous moment k-1 to construct an optimization problem and perform a single iterative solution. This process is the core computational unit of the global optimization solver.

[0125] The specific steps are as follows:

[0126] 1) Initialization:

[0127] First, we need to initialize the coordinates X and the initial estimate of the heading angle θ (0) and θ( 0) and initial sound speed s (0) These parameters constitute the state variable Θ within the current optimization window, and the initialization results are as follows:

[0128]

[0129] 2) Calculate the residual:

[0130] Residual vector r (l) , which represents the set of error terms (residuals) between the measured values ​​of all constraint factors and the model predicted values ​​in the current optimization window at the lth iteration (or current estimation). The structure of r is as follows.

[0131]

[0132] in:

[0133]

[0134]

[0135] r imu-heading =θ k -θ k-1 -ω k Δt

[0136]

[0137] r sound-smooth =s k -s k-1

[0138] The residual vector r is the core component of nonlinear least squares optimization. Each of its terms corresponds to a specific physical constraint or sensor measurement error. By minimizing the sum of squares of these residuals (i.e., the cost function J(Θ)), the state estimate (position, orientation, speed of sound) can be gradually adjusted to bring it closer to the true value.

[0139] 3) Calculate the Jacobian matrix:

[0140]

[0141] Among them, the Jacobian matrix J (l) , represents the matrix of partial derivatives of the residual vector r with respect to the state variable Θ in the lth optimization iteration. Its function is to guide the optimization algorithm on how to adjust the state variables (position, orientation, speed of sound) to minimize the cost function J(Θ).

[0142] 4) Hessian matrix and gradient calculation

[0143] Approximate Hessian matrix:

[0144] H (l) =J (l)T J (l)

[0145] In the lth iteration, the Jacobian matrix J (l) The transpose of is multiplied by itself to obtain an approximate Hessian matrix H (l) .

[0146] Gradient vector:

[0147] g (l) =J (l)T r (l)

[0148] In the lth iteration, the Jacobian matrix J (l) The transpose of the current residual vector r (l) Multiply them together to get the gradient vector g (l) .

[0149] 5) Solving linear systems

[0150] H (l) ΔΘ=-g (l)

[0151] In the lth iteration, by approximating the Hessian matrix H (l) and the gradient vector g (l) , construct a system of linear equations to solve the parameter update ΔΘ.

[0152] ΔΘ=-(J (l) TJ (l) ) -1 J (l)T r (l)

[0153] This is an explicit solution to the linear increment equation, and the parameter update ΔΘ is obtained directly through matrix inversion and multiplication.

[0154] 6) Status Update:

[0155] Θ (l+1) =Θ (l) +αΔΘ

[0156] In the lth iteration, the current state is used to estimate Θ (l) Add the product of the search direction ΔΘ and the step size α to get the new state estimate Θ (l+1) .

[0157]

[0158] The step size α is chosen by the Armijo condition (sufficient descent condition) to ensure that the movement in the search direction sufficiently reduces the objective function J(Θ).

[0159] 7) Convergence judgment:

[0160] ||ΔΘ||<10 -6 or |J (l+1) -J (l) |<10 -8

[0161] Repeat the above process. When this condition is met, it can be judged that the iteration has converged to a sufficiently accurate solution, and the estimated pose at this time can be obtained.

[0162] Furthermore, before the positioning task begins, any two movable buoy base stations are pre-selected, and an ultrasonic ranging process is performed between the two movable buoy base stations. The distance between the base stations and the ultrasonic transmission time are calculated based on the coordinates of the two movable buoy base stations; based on the distance between the base stations and the ultrasonic transmission time, the ultrasonic wave velocity in the current water area is determined, and this can be used as the initial value of the ultrasonic wave velocity.

[0163] Specifically, for ease of understanding, the positioning workflow of the solution described in this embodiment is described below from the perspective of specific implementation. Figure 3 and Figure 4As shown, the specific processing process includes the following:

[0164] Step 1: First, initialize the various modules of the movable buoy base stations (three are used as an example here) and the central base station, and deploy the general surface movable buoy base station positions.

[0165] Step 2: The mobile buoy base station connects the two control boards (multi-serial port microcomputer board and core control board) via Ethernet cables through their respective network port modules. Time synchronization between the two boards is achieved using the PTP protocol. The central base station uses the same method to achieve time synchronization between the two boards, but the core control board is located on the UUV and connected by a long Ethernet umbilical cable.

[0166] Step 3: After achieving time synchronization between the two control boards, each mobile buoy base station uses the BeiDou module to obtain its own coordinates. Before the underwater target positioning process begins, two mobile buoy base stations are selected and an ultrasonic ranging process is performed between the two base stations. Based on the coordinates of the two base stations, the distance d and the ultrasonic transmission time t are calculated. The ultrasonic wave speed s in the current water area (s = d / t) is used as the initial wave speed, and then the process proceeds to Step 4.

[0167] Step 4: After obtaining the initial wave velocity v in the current water area, positioning officially begins. The mobile buoy base station and the central base station both activate the Beidou module to begin receiving Beidou satellite pulse signals. After receiving the pulse signal, the multi-serial port microcomputer reads the signal through the serial port and processes the signal. After the pulse signal rises after the adaptive time interval (the initial time interval is large enough), an ultrasonic ranging command is issued. The core control board, which has achieved time synchronization, receives the command at the corresponding time interval through the network port module and then proceeds to step 5.

[0168] Step 5: After the core control board receives the ultrasonic ranging command, if the first method (UUV sends ultrasonic waves) is selected, the underwater target to be located (i.e., the UUV) starts sending ultrasonic signals by controlling the transducer module through the core control board. After the core computer board receives the ranging command, it drives the transducer to send ultrasonic signals. The movable buoy base station starts monitoring and receiving ultrasonic signals by controlling the corresponding transducer module through the core control board, and then proceeds to step 6.

[0169] Step 6: After the transducer module of the movable buoy base station starts to receive the ultrasonic signal transmitted by the underwater target to be located, the propagation time is calculated after receiving the signal.

[0170] Step 7: This solves the ultrasonic transmission times t1, t2, and t3 from the three mobile buoy base stations to the UUV node (these three data points will be later incorporated into the constraint equations for buoy and position coordinate estimation in the factor graph). Each base station transmits the distance calculated by the core control board to the multi-serial port microcomputer board via the network port module for subsequent data packaging and aggregation.

[0171] Step 8: After the movable buoy base station obtains the distance propagation time to the UUV through ultrasonic ranging, it combines the distance and its own coordinates obtained in step 3 to package the distance and its own coordinates into a data packet, and sends the data packet to the multi-serial port microcomputer board on the central base station buoy through the communication module on the multi-serial port microcomputer board, and then proceeds to step 9.

[0172] Step 9: After the multi-serial port microcomputer board at the central base station buoy obtains the three distances from the mobile buoy base station to the UUV and its own coordinates, it calculates the maximum value of the three propagation times t max , take a time base multiple greater than or equal to the time as the ultrasonic ranging time interval and transmit the calculated time interval to the microcomputer board of each movable buoy base station through the communication module using the same method as in step 8 for application in the subsequent ultrasonic ranging process, thereby realizing adaptive ultrasonic ranging time interval.

[0173] Step 10: While calculating the time interval, the multi-serial port microcomputer board of the central base station obtains the three distance propagation times from the three movable buoy base stations to the UUV and its own coordinates, and then uses the network port module to send the summarized data packet to the UUV node through the network cable, and then enters step 11.

[0174] Step 11: After the core control board on the UUV receives the data packet from the buoy on the central base station through the network port module, it unpacks the data packet to obtain the coordinates of each of the three movable buoy base stations and the distance from itself. Then, it uses the three distances, the coordinates of the three movable buoy base stations (buoys), and the data of the IMU sensor to calculate its own position coordinates through the pose graph optimization method.

[0175] It should be noted that if the second method is selected, that is, the buoy base station sends an ultrasonic signal and the UUV receives it, the three movable base stations will first send an ultrasonic signal with their own ultrasonic ID number. The central base station will send the ultrasonic ID number of each base station and its coordinates to the core control board deployed in the UUV through the network port module using a network cable. After the UUV receives the ultrasonic signals from the three base stations, it will calculate the ultrasonic signal based on the ID number, and obtain the coordinates of the three movable buoy base stations and the distance propagation time to itself for subsequent calculation.

[0176] The innovative design of the solution described in this embodiment in the field of underwater positioning effectively solves many problems existing in the background technology, thereby achieving a significant improvement in flexibility, accuracy and efficiency. First of all, by adopting a combination of mobile base stations and underwater unmanned underwater vehicles (UUVs), the solution described in this embodiment breaks through the dependence of traditional hydroacoustic positioning systems on fixed base stations, greatly improving the deployment flexibility of the system. This innovation enables the system to adapt quickly when faced with dynamic water environments and rapidly changing operational requirements, avoiding the problems of long deployment and adjustment time and high costs faced by traditional positioning solutions. In complex underwater operations, such as marine scientific research, rescue missions or military operations, rapid response capabilities are particularly important, and the design of the present invention is precisely for this purpose, ensuring efficient operations in different environments.

[0177] Secondly, the solution described in this embodiment uses the Beidou module and the network port module to achieve real-time time synchronization between the surface buoy and the underwater UUV node based on the PTP protocol, solving the limitation of traditional GNSS and inertial navigation systems failing underwater. Traditional underwater acoustic positioning methods are easily affected by environmental variables such as water depth, temperature, and salinity, which lead to changes in the speed of sound wave propagation, thereby affecting the accuracy of positioning. However, through real-time time synchronization, the present invention significantly simplifies the ultrasonic ranging calculation process, reduces dependence on complex environmental monitoring, and reduces the burden on computing resources. This real-time synchronization not only improves the accuracy of positioning, but also enables the system to maintain a high level of positioning reliability even in the face of harsh underwater conditions.

[0178] Finally, the pose graph optimization method introduced in this embodiment provides a novel solution for integrating multiple measurement data and relative pose changes. By dynamically updating and optimizing positioning data, this method effectively reduces errors introduced by dynamic factors such as water flow and target movement, ensuring that the system maintains high-precision positioning capabilities in complex waters. As the number of measurements increases, pose graph optimization continuously improves positioning accuracy, ensuring that the system consistently provides accurate position information during actual operations, which is crucial for performing precision operations and coordinating multi-task operations.

[0179] In summary, the solution described in this embodiment significantly improves the flexibility and adaptability of underwater positioning through innovative design ideas and technical solutions, solving a series of serious problems faced by traditional technologies, such as the lack of flexibility, lack of real-time performance, and reduced precision of fixed base stations. By introducing mobile base stations, time synchronization methods based on Beidou signals and network cables, and pose graph optimization, not only does it improve the stability and reliability of the positioning system, but it also lays a solid foundation for the efficient implementation of future underwater operations, achieving accurate and efficient positioning tasks in complex water environments, thereby promoting the development of underwater positioning technology and opening up new application prospects.

[0180] In one or more embodiments, Figure 3 and Figure 4 As shown, based on the above-mentioned underwater positioning system based on a moving baseline, this embodiment provides an underwater positioning method based on a moving baseline, including:

[0181] In response to the initialization instruction, controlling the movable buoy base station involved in positioning to perform initial deployment, and moving the movable buoy base station so that the underwater target to be positioned is located within the waters covered by the movable buoy base station;

[0182] When the underwater target to be located acts as a signal sender and the movable buoy base station acts as a signal receiver, the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located are received by the central base station, and forwarded to the underwater target to be located for posture solution. When the movable buoy base station acts as a signal sender and the underwater target to be located acts as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for distinguishing and parsing ultrasonic signals from different movable buoy base stations and its own posture solution.

[0183] Among them, the posture solution is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

[0184] In further embodiments, there is also provided:

[0185] An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the above embodiment. For the sake of brevity, no further details are given here.

[0186] It should be understood that in this embodiment, the processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), off-the-shelf field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0187] The memory may include a read-only memory and a random access memory, and provides instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0188] A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the method described in the above embodiment is completed.

[0189] The methods in the above embodiments can be directly implemented and executed by a hardware processor, or by a combination of hardware and software modules within the processor. The software modules can be located in a storage medium well-established in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. The storage medium is located in a memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods. To avoid repetition, a detailed description is not given here.

[0190] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in this embodiment can be implemented using electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0191] The foregoing description is merely a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present disclosure shall be included within the scope of protection of the present disclosure.

Claims

1. An underwater positioning system based on a moving baseline, characterized in that: include: A central base station, wherein the central base station is connected to the underwater target to be located by wired communication; the central base station is used to aggregate data of the movable buoy base station and send data packets to the underwater target to be located during the positioning process, and the central base station specifically performs the following processing: when the underwater target to be located serves as a signal sender and the movable buoy base station serves as a signal receiver, the central base station receives the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located, and forwards them to the underwater target to be located for posture solution; when the movable buoy base station serves as a signal transmitter and the underwater target to be located serves as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for unpacking the ultrasonic signals of different movable buoy base stations and its own posture solution; At least three movable buoy base stations, wherein the movable buoy base stations are used to obtain their own coordinates and ultrasonic ranging results to underwater targets to be located; Among them, the posture solution of the underwater target to be positioned is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

2. The underwater positioning system based on a moving baseline according to claim 1, wherein: The movable buoy base station includes a basic control board for communication functions and a core control board for signal and data processing; except that the core control board is set at the underwater target to be located, the rest of the composition and functions of the central base station are consistent with those of the movable buoy base station.

3. The underwater positioning system based on a moving baseline according to claim 2, wherein: There is a wired communication connection between the basic control board and the core control board in the movable buoy base station, and there is a wired communication connection between the basic control board of the central base station and the core control board carried by the underwater target to be positioned, and the basic control board and the core control board of the movable buoy base station and the central base station achieve time synchronization between the control boards based on the precise time protocol.

4. The underwater positioning system based on a moving baseline according to claim 1, wherein: The position coordinates of the underwater target to be located are obtained by the preset pose graph optimization method, specifically: The position of the underwater target to be located, the orientation angle of the underwater target to be located, and the positions of each movable buoy base station are used as variable nodes; edges are constructed by combining the pre-constructed buoy distance constraint factor, IMU motion constraint factor, connection coordinate constraint factor, IMU orientation angle constraint factor, and sound speed smoothing constraint factor; and a factor graph is constructed based on the variable nodes and the constructed edges. Based on the constructed factor graph, the loss function is constructed; Based on the constructed loss function, the position coordinate estimation and orientation angle of the underwater target to be located are obtained through optimization solution.

5. The underwater positioning system based on a moving baseline according to claim 4, characterized in that: The buoy distance constraint factor is specifically expressed as: f range (X k ,M i ,s k )=||x k -M i || 2 -(s k ·t i ) 2 The IMU motion constraint factor is specifically expressed as: f IMU (X k ,X k-1 ,v k ,Δt)=||X k -(X k-1 +v k Δt)|| 2 ; The connected coordinate constraint factor is specifically expressed as: f orientaion (X k ,the k ,X k-1 ,the k-1 )=(θ k -atan2(y k -y k-1 ,x k -x k-1 )) 2 ; The IMU orientation angle constraint factor is specifically expressed as: f IMU_orientation (i k ,i k-1 ,oh k ,Δt)=(θ k -(θ k-1 +oh k Δt)) 2 ; The sonic smoothing constraint factor is specifically expressed as: f velocity (s k ,s k-1 )=||s k -s k-1 || 2 ; Among them, X k , M i They represent the position of the underwater target to be located at time k and the position of the i-th movable buoy base station, t i is the ultrasonic ranging transmission time between the underwater target to be located and the i-th movable buoy base station, X k ,X k-1 represents the three-dimensional position of the underwater target to be located at the current time k and the previous time k-1; x k ,y k , x k-1 ,y k-1 v represents the x-axis and y-axis coordinate values ​​of the underwater target to be located at the current moment k and the previous moment k-1 on the horizontal plane respectively; k represents the speed of the underwater target to be located at the kth moment, Δt represents the time step at the kth moment; θ k ,θ k-1 represents the heading angle of the underwater target to be located at the current time k and the previous time k-1; ω k represents the angular velocity of the underwater target to be located at the kth moment, s k Indicates the ultrasonic wave speed in the current water area at time k.

6. The underwater positioning system based on a moving baseline according to claim 5, characterized in that: The loss function is specifically expressed as follows: Among them, J(X,θ,s) is the final loss function to be optimized, T is the time period, and M is the number of movable buoy base stations.

7. The underwater positioning system based on a moving baseline according to claim 1, wherein: Before the positioning task begins, any two movable buoy base stations are pre-selected, and an ultrasonic ranging process is performed between the two movable buoy base stations. The distance between the base stations and the ultrasonic transmission time are calculated based on the coordinates of the two movable buoy base stations; based on the distance between the base stations and the ultrasonic transmission time, the ultrasonic wave speed in the current water area is determined.

8. The underwater positioning method based on a moving baseline is characterized by: The underwater positioning system based on a moving baseline according to any one of claims 1 to 7 comprises: In response to the initialization instruction, controlling the movable buoy base station involved in positioning to perform initial deployment, and moving the movable buoy base station so that the underwater target to be positioned is located within the waters covered by the movable buoy base station; When the underwater target to be located acts as a signal sender and the movable buoy base station acts as a signal receiver, the coordinates of the movable buoy base station and the ultrasonic ranging result from the movable buoy base station to the underwater target to be located are received by the central base station, and forwarded to the underwater target to be located for posture solution. When the movable buoy base station acts as a signal sender and the underwater target to be located acts as a receiver, the central base station sends the coordinates of each movable buoy base station and its ultrasonic signal ID to the underwater target to be located for distinguishing and parsing ultrasonic signals from different movable buoy base stations and its own posture solution. Among them, the posture solution is specifically as follows: based on the obtained coordinates of each movable buoy base station and the ultrasonic ranging results to the underwater target to be positioned, combined with the measurement data of the inertial measurement unit carried by the underwater target to be positioned, the position coordinates of the underwater target to be positioned are obtained through a preset posture graph optimization method.

9. An electronic device comprising a memory, a processor, and a computer program stored and running on the memory, characterized in that: When the processor executes the program, the underwater positioning method based on moving baseline as described in claim 8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the underwater positioning method based on a moving baseline as claimed in claim 8 is implemented.

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