A ship, a ship multi-sensor positioning information synchronization method, a storage medium and a program product

Abstract

The application discloses a ship, a ship multi-sensor positioning information synchronization method, a storage medium and a program product, structured clock signals are uniformly sent to each sensor through a reference clock device, the problem of different time references of multiple sensors caused by independent clock sources is solved from the hardware level, it is ensured that all measurement data have consistent and accurate traceable time labels, and the probability of misusing historical data due to time misalignment is reduced. In view of the inherent difference that the data update frequencies of the sensors are different, the high-frequency IMU and DVL data are intelligently matched to the low-frequency GNSS data time, fusion data with time synchronization and accurate covariance estimation are generated, and therefore the probability of interpolation error and information loss caused by inconsistent frequencies is reduced.

Description

Technical Field

[0001] This invention relates to the field of marine technology, and in particular to a ship, a method for synchronizing positioning information of multiple sensors on a ship, a storage medium, and a program product. Background Technology

[0002] With increasing demands for accuracy and reliability in ship navigation systems, multi-sensor fusion positioning has become an important technological direction. However, sensors typically originate from different manufacturers, possessing independent clock references and varying data output frequencies, making it difficult to directly align the acquired positioning information in terms of time and frequency. This time asynchrony and frequency inconsistency directly impacts the accuracy of subsequent data fusion, thereby reducing the precision and reliability of the final ship positioning information. How to effectively achieve time synchronization and frequency registration among multiple sensors is a key issue that needs to be addressed in the practical application of multi-sensor fusion positioning systems. Summary of the Invention

[0003] This application provides a ship, a method for synchronizing ship multi-sensor positioning information, a storage medium, and a program product. It solves the technical problem in the prior art where positioning information from multiple sensors is difficult to directly align and fuse due to inconsistencies between the clock reference and the acquisition frequency. It achieves the technical effect of effectively improving the data consistency and final positioning output accuracy of the multi-sensor fusion positioning system through hardware clock synchronization and software frequency registration.

[0004] In a first aspect, this application provides a ship equipped with an industrial control computer, a reference clock device, an inertial measurement unit, a first Doppler log, a second Doppler log, and a signal receiver for a global navigation satellite system.

[0005] The reference clock device, the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver are respectively connected to the industrial control computer; The inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver are respectively connected to the reference clock device; The first Doppler log and the second Doppler log are arranged in a mirror-symmetric manner with respect to the longitudinal midsection of the ship and are located in the same transverse section of the ship.

[0006] Secondly, this application provides a method for synchronizing multi-sensor positioning information of a ship, applied to an industrial control computer of a ship as provided in the first aspect, the method comprising: The reference clock device is controlled to send reference clock signals to the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver at preset frequencies respectively; The inertial measurement unit is controlled to generate first measurement data according to a first measurement cycle, the first Doppler logger is controlled to generate second measurement data according to a second measurement cycle, the second Doppler logger is controlled to generate third measurement data according to a second measurement cycle, and the signal receiver is controlled to receive fourth measurement data sent by the global navigation satellite system according to a fourth measurement cycle; the first measurement data, the second measurement data, the third measurement data, and the fourth measurement data each carry clock information matching the reference clock signal; the first measurement cycle is η times the fourth measurement cycle, the second measurement cycle is τ times the fourth measurement cycle, and both η and τ are greater than 1; Based on the first measurement data, first initial data related to attitude is determined; based on the second measurement data and the third measurement data with clock matching, second initial data related to displacement increment is determined; and based on the fourth measurement data, fourth initial data related to position is determined. For each fourth measurement cycle, the η first initial data points obtained in the current fourth measurement cycle are fused to obtain first fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle; the τ second initial data points obtained in the current fourth measurement cycle are fused to obtain second fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle; based on the first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle, the target positioning information of the ship in the current fourth measurement cycle is determined.

[0007] Thirdly, this application provides a non-transitory computer-readable storage medium that, when the instructions in the storage medium are executed by the ship's industrial control computer, enables the ship to implement a ship multi-sensor positioning information synchronization method as provided in the second aspect.

[0008] Fourthly, this application provides a computer program product, including computer instructions, which are executed by an industrial control computer to implement a method for synchronizing multi-sensor positioning information of a ship as provided in the second aspect.

[0009] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: This application embodiment uses a reference clock device to uniformly send structured clock signals to all sensors, completely solving the time reference asynchrony problem caused by independent clock sources for multiple sensors at the hardware level. This ensures that all measurement data have consistent and accurately traceable time tags, avoiding the misuse of historical data due to time misalignment. Secondly, addressing the inherent differences in the update frequencies of data from various sensors, high-frequency IMU and DVL data are intelligently registered to the low-frequency GNSS data time, generating time-synchronized fused data with accurate covariance estimation. This fundamentally eliminates interpolation errors and information loss caused by frequency inconsistency. Finally, this spatiotemporally aligned multi-source data with clear uncertainty metrics is input into a Kalman filter controller. This fully leverages the absolute position accuracy of GNSS, the high-precision relative displacement measurement of DVL, and the continuous attitude update advantages of IMU. Through optimal estimation, it achieves a synergistic improvement in positioning information accuracy, continuity, and overall robustness, providing stable, reliable, and high-precision fused navigation and positioning capabilities for ocean-going vessels in complex sea conditions. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A schematic diagram of the structure of a ship provided for an embodiment of this application; Figure 2 A schematic diagram illustrating the distribution of various sensors in a ship, provided as an embodiment of this application; Figure 3 A schematic diagram of the distribution of a Doppler log in a ship, provided for an embodiment of this application; Figure 4 A flowchart illustrating a method for synchronizing positioning information of multiple sensors on a ship, provided as an embodiment of this application; Figure 5 A schematic diagram illustrating the timing and delay characteristics of multi-sensor data output; Figure 6 A time-series comparison diagram of multi-sensor data output; Figure 7 This is a schematic diagram illustrating the calculation of the Doppler log measurement model provided in the embodiments of this application.

[0012] Figure label: 1-Global navigation satellite, 2-Signal receiver, 3-Ship, 4-Inertial measurement unit, 5-First Doppler log, 6-Second Doppler log. Detailed Implementation

[0013] This application provides a ship, a method for synchronizing positioning information from multiple ship sensors, a storage medium, and a program product, which solves the technical problem in the prior art where positioning information from multiple sensors is difficult to directly align and fuse due to inconsistencies between the clock reference and the acquisition frequency.

[0014] The technical solution of this application embodiment is to solve the above-mentioned technical problems, and the general idea is as follows: This application embodiment uses a reference clock device to uniformly send structured clock signals to all sensors, completely solving the time reference asynchrony problem caused by independent clock sources for multiple sensors at the hardware level. This ensures that all measurement data have consistent and accurately traceable time tags, avoiding the misuse of historical data due to time misalignment. Secondly, addressing the inherent differences in the update frequencies of data from various sensors, high-frequency IMU and DVL data are intelligently registered to the low-frequency GNSS data time, generating time-synchronized fused data with accurate covariance estimation. This fundamentally eliminates interpolation errors and information loss caused by frequency inconsistency. Finally, this spatiotemporally aligned multi-source data with clear uncertainty metrics is input into a Kalman filter controller. This fully leverages the absolute position accuracy of GNSS, the high-precision relative displacement measurement of DVL, and the continuous attitude update advantages of IMU. Through optimal estimation, it achieves a synergistic improvement in positioning information accuracy, continuity, and overall robustness, providing stable, reliable, and high-precision fused navigation and positioning capabilities for ocean-going vessels in complex sea conditions.

[0015] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0016] First, it should be clarified that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0017] This application provides an embodiment of a ship, which can be referred to in detail. Figure 1 , Figure 2 and Figure 3As shown, the ship 3 is equipped with an industrial control computer, a reference clock device, an inertial measurement unit 4 (such as a gyroscope), a first Doppler log 5, a second Doppler log 6, and a signal receiver 2 for a global navigation satellite system; the reference clock device, the inertial measurement unit 4, the first Doppler log 5, the second Doppler log 6, and the signal receiver 2 are respectively connected to the industrial control computer; the inertial measurement unit 4, the first Doppler log 5, the second Doppler log 6, and the signal receiver 2 are respectively connected to the reference clock device.

[0018] refer to Figure 2 The locations of the inertial measurement unit 4 and the signal receiver 2 on the ship 3 are known. On the ship 3, the inertial measurement unit 4 is typically positioned near the ship's center of gravity or in a location with a stable hull structure to reduce vibration interference caused by the ship's movement and ensure stable and reliable attitude angle data. The signal receiver 2 (i.e., the antenna for the Global Navigation Satellite System (GNSS)) is positioned on the top of the ship 3's superstructure or other high locations with unobstructed views to ensure stable reception of GNSS signals.

[0019] refer to Figure 3 It can be seen that the first Doppler log 5 and the second Doppler log 6 are positioned in a manner that is mirror-symmetrical with respect to the longitudinal midsection of the ship 3 and located on the same transverse section of the ship 3. Due to the port-to-port orientation of the first Doppler log 5 and the second Doppler log 6 on the ship 3, the first Doppler log 5 can also be referred to as the port-side Doppler log, and the second Doppler log 6 as the starboard-side Doppler log.

[0020] This arrangement means that the first Doppler log 5 and the second Doppler log 6 are installed on the port and starboard sides of the vessel 3, respectively. They are equidistant from the longitudinal centerline (midline section) of the vessel 3, and their installation directions are symmetrical with respect to the centerline. At the same time, they are located on the same transverse section (same transverse cross section) of the vessel 3, meaning that their installation positions are not misaligned in the bow-stern direction (longitudinal) of the vessel 3.

[0021] This symmetrical and coplanar arrangement is designed to ensure that when the vessel 3 is in motion, the logs on both the port and starboard sides can simultaneously and equally measure the lateral velocity component of the vessel 3 relative to the seabed. This allows for the accurate calculation of the vessel 3's turning rate or heading angle change through the velocity difference, and reduces the calculation error introduced by the different longitudinal installation positions.

[0022] Furthermore, during installation, the orientation (i.e., the central axis of signal transmission / reception) of the internal acoustic transducers (the core components for transmitting and receiving sound waves) of the Doppler logs on both port and starboard sides is also symmetrically calibrated. Typically, Doppler logs do not emit sound waves vertically downwards, but rather at a fixed angle to the vertical (called the "Janus angle"). Here, symmetry means both angular and directional symmetry. Angular symmetry refers to the angle between the port starboard log's transmission axis and the left side of the ship's longitudinal midsection, and the angle between the starboard log's transmission axis and the right side of the midsection, being equal in magnitude. Directional symmetry means that, in horizontal projection, these two axes are mirror-symmetrical with respect to the midsection.

[0023] The purpose of this symmetrical configuration of the signal transmission axis is threefold. First, it ensures a consistent measurement reference, a technical prerequisite for achieving the intended function of physical position symmetry (calculating steering through speed differences). If only the physical position is symmetrical, but the signal transmission axis is asymmetrical (e.g., different angles or non-mirror orientation), then the port and starboard odometers will no longer measure the speed components in strictly symmetrical directions. Second, it reduces systematic errors. The symmetrical transmission axis ensures that the responses of the port and starboard sensors to the same motion of the vessel 3 (especially lateral or rotational motion) are geometrically equivalent. This allows subsequent calculations of heading angle changes to purely reflect the true steering of the vessel 3, reducing the inclusion of fixed biases caused by differences in sensor orientation. Third, it ensures model validity, a crucial hardware condition for the subsequent mathematical model of "calculating heading angle increments based on the difference in port and starboard mileage" to hold true and maintain accuracy. An asymmetrical transmission axis would violate the geometric assumptions of this model, introducing systematic errors that are difficult to correct through software.

[0024] In other words, the embodiments of this application ensure that the left and right Doppler logs are not only symmetrical in installation position, but more importantly, symmetrical in the measurement direction of signal transmission, thereby providing a reliable and consistent geometric measurement benchmark for high-precision extraction of the ship's lateral speed and steering information.

[0025] Based on the aforementioned vessel, this application provides a method for synchronizing multi-sensor positioning information of a vessel, applied to the industrial control computer of the aforementioned vessel. The method includes steps S41-S44, which can be found in detail below. Figure 4 As shown.

[0026] Step S41: Control the reference clock device to send reference clock signals to the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver respectively at a preset frequency; Step S42: Control the inertial measurement unit to generate first measurement data according to a first measurement cycle, control the first Doppler logger to generate second measurement data according to a second measurement cycle, control the second Doppler logger to generate third measurement data according to a second measurement cycle, and control the signal receiver to receive fourth measurement data sent by the global navigation satellite system according to a fourth measurement cycle; the first measurement data, the second measurement data, the third measurement data, and the fourth measurement data each carry clock information matching the reference clock signal; the first measurement cycle is η times the fourth measurement cycle, the second measurement cycle is τ times the fourth measurement cycle, and both η and τ are greater than 1; Step S43: Determine first initial data related to attitude based on the first measurement data, determine second initial data related to displacement increment based on the second measurement data with clock matching and the third measurement data, and determine fourth initial data related to position based on the fourth measurement data; Step S44: For each fourth measurement cycle, fuse the η first initial data points obtained in the current fourth measurement cycle to obtain first fused data synchronized with the fourth initial data points in the current fourth measurement cycle; fuse the τ second initial data points obtained in the current fourth measurement cycle to obtain second fused data synchronized with the fourth initial data points in the current fourth measurement cycle; based on the first fused data points, the second fused data points, and the fourth initial data points in the current fourth measurement cycle, determine the target positioning information of the ship in the current fourth measurement cycle.

[0027] The method for synchronizing multi-sensor positioning information of a ship provided in this application embodiment can be executed by the ship's industrial control computer.

[0028] Regarding step S41, the reference clock device is controlled to send reference clock signals to the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver respectively at a preset frequency.

[0029] like Figure 5The diagram illustrates the timing and delay characteristics of multi-sensor data output. The horizontal axis represents time (from t0 to t1), and the vertical axis corresponds to different types of sensor data output. The diagram shows the signal output characteristics of three types of sensors: GNSS, Doppler Velocity Log (DVL), and Inertial Measurement Unit (IMU). The IMU has the highest data update frequency and the densest output waveform, with a data delay of only 1 μs; the DVL has a medium update frequency and a moderate waveform density, corresponding to a data delay of up to 5 μs; the GNSS has the lowest update frequency, the sparsest waveform, and the largest data delay, reaching 20 μs. Figure 5 As can be seen, there is a clock synchronization problem between different sensors during the time span from t0 to t1.

[0030] To address this issue, this embodiment of the application uses an industrial control computer to control the reference clock device to send reference clock signals to the inertial measurement unit, the first Doppler logger, the second Doppler logger, and the signal receiver at preset frequencies.

[0031] Specifically, the reference clock device is controlled to generate a first reference clock signal matching a first structure of the inertial measurement unit, and transmit the first reference clock signal to the inertial measurement unit at a preset frequency; the reference clock device is controlled to generate a second reference clock signal matching a second structure of the first Doppler log, and transmit the second reference clock signal to the first Doppler log at a preset frequency; the reference clock device is controlled to generate a third reference clock signal matching a second structure of the second Doppler log, and transmit the third reference clock signal to the second Doppler log at a preset frequency; the reference clock device is controlled to generate a fourth reference clock signal matching a fourth structure of the signal receiver, and transmit the fourth reference clock signal to the signal receiver at a preset frequency; the reference clock signals include the first reference clock signal, the second reference clock signal, the third reference clock signal, and the fourth reference clock signal.

[0032] For example, a reference clock device generates Global Navigation Satellite System (GNSS) architecture data transmission data:

[0033] The reference clock device generates and transmits Doppler log structure data:

[0034] The reference clock device generates gyroscope (IMU) structure data and transmits the data:

[0035] As can be seen, in this embodiment, the reference clock device does not broadcast the same simple clock pulse to all sensors. Instead, it generates and sends reference clock signals with a unified time scale that match the specific data structure and communication protocol of different types of sensors. Specifically, it generates a clock signal of the "first structure" for the gyroscope, a clock signal of the "second structure" for the left and right Doppler speedometers, and a clock signal of the "fourth structure" for the GNSS signal receiver. The purpose of this design is to ensure that each sensor can seamlessly integrate the synchronization signal into its own data frame or sampling period when it receives it, thereby binding the measurement time with a unified system time base (real_time) with high precision from the source of data generation (sensor end). All subsequent data (such as GNSS_data, DVL_data, IMU_data) carries this unified time scale, providing a basis for the industrial control computer to perform accurate time point matching and data association across sensors in subsequent steps. Sending "at a preset frequency" ensures the continuity and periodicity of the synchronization signal, maintaining the long-term stability and consistency of the entire system clock reference. This step is a key operation that solves the "clock reference asynchrony" problem at the hardware and driver levels, providing a clean data source with time alignment for subsequent fusion algorithms.

[0036] Regarding step S42, the inertial measurement unit is controlled to generate first measurement data according to a first measurement cycle, the first Doppler logger is controlled to generate second measurement data according to a second measurement cycle, the second Doppler logger is controlled to generate third measurement data according to a second measurement cycle, and the signal receiver is controlled to receive fourth measurement data sent by the global navigation satellite system according to a fourth measurement cycle; the first measurement data, the second measurement data, the third measurement data, and the fourth measurement data each carry clock information matching the reference clock signal; the first measurement cycle is η times the fourth measurement cycle, the second measurement cycle is τ times the fourth measurement cycle, and both η and τ are greater than 1.

[0037] like Figure 6The diagram shows a time-series comparison of multi-sensor data output, visually illustrating the asynchronous data update frequencies of the three navigation sensors: GNSS, DVL, and IMU. The horizontal axis represents the time axis, and the vertical axis corresponds to the data output channels of different sensors: the IMU's output waveform is the densest, indicating it has the highest data update frequency among the three, continuously outputting inertial measurement data at microsecond intervals; the DVL's waveform density is at a medium level, with the next highest data update frequency; the GNSS's waveform is the sparsest, with the lowest update frequency. The alignment of the dashed lines at time point t2 clearly shows that while the IMU has completed dozens of data outputs and the DVL has also output multiple sets of data, the GNSS has only output a few frames of data. This significant difference in frequency causes the data to be unable to be directly aligned in the time dimension.

[0038] To solve this problem, this application provides steps S42-S44. Step S42 will be explained below.

[0039] Step S42 first controls each sensor to operate independently according to its inherent or preset measurement cycle. The inertial measurement unit (IMU) generates first measurement data containing raw measurement values ​​such as angular velocity and acceleration at a higher frequency (first measurement cycle); the Doppler logs (DVLs) on the port and starboard sides generate second and third measurement data containing their respective measured ground velocity or displacement vectors at another higher frequency (second measurement cycle). The velocity measurement model of the Doppler log at time k can be expressed as:

[0040] in, The relative velocity components of the ship along the Doppler beam direction at time k. The frequency of sound wave emission. The echo reflection frequency difference (this is the difference between the frequency of the received seabed (or water layer) reflected wave and the original transmission frequency). (the difference between them) The cosine of the angle between the central axis of the sound wave beam emitted by the Doppler log transducer and the direction perpendicular to the sea surface (i.e., the direction of the local gravity line, which can be approximated as the direction perpendicular to the ship's deck plane in the ship's coordinate system (when the ship is upright)). The speed at which sound travels in seawater. Based on The relative instantaneous velocity components of ocean-going vessels along the Doppler beam direction at any given moment The unit time can be obtained by integration. The relative navigation distance components of ocean-going vessels along the Doppler beam direction: .

[0041] The GNSS signal receiver receives satellite signals at a relatively low frequency (fourth measurement cycle) and generates fourth measurement data containing latitude, longitude, or planar coordinates.

[0042] The key is that every frame of data generated or received by all sensors has a unified reference clock information provided by step S41 embedded at the data source, so that data from different physical devices and at different times have a consistent timestamp that is traceable and comparable.

[0043] Step S42 further clarifies that the IMU sampling frequency is η times that of GNSS, and the DVL sampling frequency is τ times that of GNSS (η, τ>1). This utilizes high-frequency IMU and DVL data to fill and refine the low-frequency GNSS data update interval, providing the possibility and data foundation for aligning and fusing data from multiple high-frequency sensors through a fusion algorithm at each GNSS data arrival time. This step essentially solidifies the results of hardware clock synchronization into a timestamped data stream and establishes the mathematical relationship between different frequency sampling data, which is a prerequisite for subsequently solving the frequency asynchrony problem and performing effective data fusion.

[0044] Regarding step S43, first initial data related to attitude is determined based on the first measurement data, second initial data related to displacement increment is determined based on the second measurement data with clock matching and the third measurement data, and fourth initial data related to position is determined based on the fourth measurement data.

[0045] The initial measurement data comes from the inertial measurement unit (IMU), typically containing raw voltage or digital readings of three-axis angular velocity and three-axis acceleration. Based on this data, the industrial control computer calculates the ship's attitude angles at the current moment—namely, roll, pitch, and heading angles—using built-in algorithms (such as attitude calculation, which involves integrating gyroscope data, combining accelerometer data for tilt estimation, and drift compensation). These calculated attitude angles constitute the initial data related to the ship's attitude.

[0046] For example, the first initial data may include:

[0047] in, This represents the ship's yaw angle calculated by the IMU. In the field of ship navigation, this angle is usually defined as the heading angle, which is the angle between the ship's heading line and the geographic north. This represents the ship's pitch angle calculated by the IMU. In the field of marine engineering, this angle usually corresponds to the roll angle, which is the angle at which the ship rotates about its transverse axis (port-starboard axis), with the bow pointing upwards as positive. This represents the ship's roll angle calculated by the IMU. In the maritime field, this angle usually corresponds to the roll angle, which is the angle at which the ship rotates about its longitudinal axis (bow-stern axis), with the starboard side rolling down (port side rising) being positive. , , , This is a unit quaternion with four components used to represent the rotational attitude of the IMU (and the carrier, i.e. the ship) relative to a reference coordinate system (usually the navigation coordinate system, such as "north-south sky") in a non-singular and compact manner. It is a scalar (real part) of a quaternion whose value is related to the cosine of half the rotation angle and contains the total rotation information. , , These are the vector (imaginary) components of the quaternion, which are respectively related to the rotation axis (x, y, z axis) and the sine of half the rotation angle.

[0048] This set of formulas uses mathematically superior attitude quaternions calculated by the IMU (Inertial Measurement Unit). , , , Through trigonometric relationships, it is converted into Euler angles (heading angles) that are more commonly used and easier to understand in fields such as navigation and control. , swaying Horizontal rocking Therefore, the initial data typically includes the three attitude angles calculated by the IMU.

[0049] The second and third measurement data come from Doppler logs (DVL) on the port and starboard sides, respectively, and are typically the velocity components along their beam directions or the ground velocity vectors measured by each. Since these two sets of data have been clock-matched through steps S41 and S42, the industrial control computer can process the port and starboard DVL data pairs based on the timestamp-aligned data. This primarily utilizes the geometric relationship between the port and starboard velocity information to calculate the overall velocity vector, displacement increment, and heading change of the ship within the current measurement period. These quantities, characterizing the changes in the ship's motion over a short time interval, collectively constitute the second initial data related to the displacement increment.

[0050] Specifically, based on the second measurement data and the third measurement data with clock matching, second initial data related to the displacement increment is determined, including steps S431-S432.

[0051] Step S431: For each consecutive two adjacent second measurement data and the next second measurement data obtained by the first Doppler log, and for each consecutive two adjacent third measurement data and the next third measurement data obtained by the second Doppler log, the clocks of the previous second measurement data and the next second measurement data are matched, and the clocks of the next second measurement data and the next third measurement data are matched, the first actual mileage of the first Doppler log in the current second measurement cycle is determined based on the previous second measurement data and the next second measurement data, and the second actual mileage of the second Doppler log in the current second measurement cycle is determined based on the previous third measurement data and the next third measurement data.

[0052] Step S431 describes the specific calculation process for extracting the actual navigation distance from the raw Doppler log (DVL) speed measurement. Its core lies in utilizing clock-synchronized, paired, and continuous port and starboard DVL data.

[0053] This step first clarifies the objects being processed, including: for the port DVL (first Doppler log), taking two consecutive frames of data (the previous second measurement data and the next second measurement data); similarly, for the starboard DVL (second Doppler log), taking two consecutive frames of data (the previous third measurement data and the next third measurement data). Crucially, these data pairs are not only continuous within their respective sensors, but the port and starboard data are also strictly matched in time; that is, the timestamps of the "previous" frame of port and starboard data are aligned, and the timestamps of the "next" frame of port and starboard data are also aligned.

[0054] Based on these two pairs of time-aligned continuous data, the industrial control computer performs calculations. It does not directly use a single speed reading, but rather processes two consecutive measurements within a time interval (i.e., a second measurement cycle, TDVL). This typically involves integrating the speeds measured within that cycle. Specifically, the industrial control computer uses the speed information corresponding to the previous and next frames of data (combined with the cycle length) to calculate the cumulative distance traveled along its measurement direction, as sensed by the port DVL itself, within that TDVL time interval; this is the first actual navigation distance (DVL). The exact same calculation process is applied independently to two adjacent frames of data synchronized with the starboard DVL, thus obtaining the second actual navigation distance ( ).

[0055] Step S432: Based on the first actual voyage mileage, the second actual voyage mileage, the installation distance between the first Doppler log and the second Doppler log, and the previous heading angle corresponding to the start time of the current second measurement cycle, determine the second initial data related to the displacement increment of the ship in the current second measurement cycle.

[0056] Step S432 is to calculate the independent navigation distance on the port and starboard sides in step S431. and Based on this, these local measurements are merged and transformed into displacement increment information describing the overall motion of the ship.

[0057] The core of this step is utilizing the geometric relationship inherent in the difference between the port and starboard mileages. The industrial control computer will receive the first actual navigation mileage ( ) and the second actual voyage distance ( ), along with known hardware installation parameters, namely the installation distance between the port and starboard Doppler logs ( ), and the ship's previous heading angle at the start of the current calculation period ( ), as input.

[0058] The industrial control computer processes these inputs using a specific kinematic model (whose mathematical essence is solving the circular motion of a rigid body in a two-dimensional plane). This model can determine the mileage difference between the port and starboard sides. The change in the ship's heading angle during this period is calculated. Simultaneously, the displacement of the ship's center of mass in the forward direction is calculated from the average mileage on both the port and starboard sides. Finally, combined with the initial heading angle ( These motions in the ship's body coordinate system are analyzed and converted into displacement increments along the X and Y axes in a unified global reference system (e.g., the northeast-central coordinate system). , ).

[0059] Specifically, step S432 can be broken down into steps S4321-S4324. Steps S4321 to S4324 detail the complete mathematical model and calculation process for progressively converting the independent mileage measured by the port and starboard Doppler logs (DVL) into the ship's displacement increment (second initial data) in the global coordinate system. For details, please refer to [link / reference needed]. Figure 7 The diagram shows a Doppler log measurement model.

[0060] Step S4321: Based on the first actual voyage mileage and the second actual voyage mileage, determine the actual voyage mileage of the ship in the current second measurement cycle.

[0061] The industrial control computer will measure the first actual voyage distance (DVL) on the port side. ) and the second actual navigation distance measured by starboard DVL ( Perform an arithmetic mean:

[0062] Its physical significance lies in the fact that, assuming the ship moves as a rigid body and the DVL (Direct Velocity Scale) is symmetrically installed on both sides, this average value represents the actual distance traveled by the ship's center of mass (or center of rotation) along the forward direction within the current DVL measurement period. It filters out the speed difference between the port and starboard sides caused by the ship's turning and extracts the pure forward motion component.

[0063] Step S4322: Based on the first actual voyage mileage, the second actual voyage mileage, and the installation distance between the first Doppler log and the second Doppler log, determine the ship's heading angle increment from the start time to the end time of the current second measurement cycle.

[0064] The industrial control computer calculates the difference in actual sailing distance between the port and starboard sides. ), and divide it by the fixed installation distance between the port and starboard DVLs ( ):

[0065] The geometric principle is as follows: when a ship turns, the arc length of the inner (turning center side) DVL trajectory is shorter than that of the outer DVL trajectory. The ratio of the difference in arc length to the installation distance is approximately equal to the angle (increment of heading angle, in radians) that the ship rotates around the instantaneous turning center during that time period. This formula is the core of this method, which allows the attitude to be calculated using only two DVLs.

[0066] Step S4323: Determine the turning radius of the ship in the current second measurement cycle based on the ship's actual voyage distance and the ship's heading angle increment.

[0067] The industrial control computer will process the actual voyage distance of the ship obtained in step S4321. Divide by the heading angle increment obtained in step S4322 ( ):

[0068] In a short period of time, the ship ( Under the model where the motion of () is approximated as circular motion, based on the formula that the length of a circular arc equals the radius multiplied by the central angle, this calculation result... This refers to the instantaneous turning radius of the ship during its circular motion within this period. This parameter serves as a bridge between linear displacement and angular displacement.

[0069] Similarly, in At any moment, assuming The Doppler log positioning model can be described as follows:

[0070] in, express The position and pose of an ocean-going vessel in the global coordinate system at any given time.

[0071] Figure 7 In express The position and pose of an ocean-going vessel in the global coordinate system at any given time.

[0072] Step S4324: Based on the turning radius, the ship's heading angle increment, and the previous heading angle corresponding to the start time of the current second measurement cycle, determine the second initial data related to the displacement increment of the ship in the current second measurement cycle.

[0073] The industrial computer will use the calculated turning radius ( ), heading angle increment ( ) and the previous heading angle known at the start of the period ( Substitute this into the circular arc kinematics model. This model, through geometric relationships, decomposes the tangential motion along the circular arc onto the X and Y axes of the global coordinate system. The specific calculations are typically as follows:

[0074] Calculated and That is, the ship from At any moment, the position and posture are in motion. The displacement increment in the global coordinate system during the pose transition. Combined with... Together, they constitute the complete second initial data { , , }

[0075] Therefore, the output of step S432, i.e. the second initial data, is a global displacement vector containing the displacement of the ship within a single DVL measurement cycle. , ) and heading angle increment ( This is a complete dataset. This data accurately describes the relative motion of ships over a short time interval and is a key input for subsequent fusion with absolute position information (GNSS data).

[0076] Furthermore, the fourth set of measurement data comes from the Global Navigation Satellite System (GNSS) signal receiver, typically in raw latitude and longitude coordinates or coordinates in a geocentric-fixed coordinate system. Based on this data, the industrial control computer performs necessary coordinate transformations (e.g., from WGS-84 geodetic coordinates to locally used planar projected coordinates, such as UTM coordinates) to obtain the ship's two-dimensional planar position coordinates (x, y) in a unified global reference system. This transformed absolute position information, which can be directly used for subsequent fusion calculations, is the fourth set of initial position-related data.

[0077] Regarding step S44, for each of the fourth measurement cycles, the η first initial data points obtained in the current fourth measurement cycle are fused to obtain first fused data synchronized with the fourth initial data points in the current fourth measurement cycle; the τ second initial data points obtained in the current fourth measurement cycle are fused to obtain second fused data synchronized with the fourth initial data points in the current fourth measurement cycle; based on the first fused data points, the second fused data points, and the fourth initial data points in the current fourth measurement cycle, the target positioning information of the ship in the current fourth measurement cycle is determined.

[0078] Step S44 aims to address the problem of data not being directly aligned and fused in time due to differences in sensor sampling frequencies (i.e., "frequency asynchrony"). This step describes a systematic frequency registration and data fusion process.

[0079] First, the lowest frequency GNSS data update time (i.e., the end time of each fourth measurement cycle) was defined as the reference point. At this reference point, the system does not directly use the single measurement values ​​of the IMU and DVL at that time, but instead fuses multiple sets of high-frequency data accumulated within the current GNSS cycle.

[0080] Specifically, the η IMU attitude data points (first initial data) collected within this period are fused to generate a more statistically representative first fused data point synchronized with the GNSS time. Similarly, the τ DVL displacement increment data points (second initial data) collected within this period are fused to generate a second fused data point synchronized with the GNSS time. The purpose of this fusion (e.g., using estimation algorithms such as least squares) is to estimate the optimal values ​​and uncertainties of the IMU attitude and DVL displacement increments at the GNSS sampling time by processing multiple data points within a time window, thereby unifying the information from all sensors to the same "virtual sampling time" in the time dimension.

[0081] After completing the frequency registration described above, the system obtains three sets of aligned data at the same time point: fourth initial data representing absolute position, first fused data representing the best estimated attitude, and second fused data representing the best estimated displacement increment. Finally, these time-synchronized and complementary data are input into a data fusion unit (such as a Kalman filter controller). The fusion unit performs optimal estimation based on their respective physical models and statistical characteristics, ultimately outputting a unified "target positioning information" with superior accuracy, reliability, and continuity compared to any single sensor. This information typically includes frequently updated ship position, velocity, and attitude. In short, step S44 achieves effective unification and coordination of multi-rate sensor data at both the temporal and informational levels by fusing high-frequency data windows based on low-frequency moments.

[0082] Specifically, the η first initial data points obtained in the current fourth measurement cycle are fused to obtain first fused data synchronized with the fourth initial data in the current fourth measurement cycle, including: The η initial data points obtained in the current fourth measurement cycle are fused using the least squares method to obtain a first virtual value and a first covariance matrix of the first virtual value; the first fused data includes the first virtual value and the first covariance matrix.

[0083] The input consists of η initial data points arranged chronologically (e.g., a heading angle sequence). These data timestamps are evenly distributed within the current GNSS cycle, but what is needed is the attitude value at the specific moment the GNSS data arrives. This target moment is typically located at the end or middle of the time series (depending on the definition). Directly using the last measurement may be inaccurate due to transient noise, while simple averaging ignores the temporal trend of the data. Therefore, a method is needed that can model the trend of data over time and perform optimal interpolation / extrapolation.

[0084] The least squares method establishes a simple linear variation model. It assumes that within a short GNSS cycle (η IMU cycles), the change in attitude angle can be approximated as a straight line. The algorithm uses the time offset (relative to the target GNSS time) of each IMU data point as the independent variable and the measured attitude angle as the dependent variable to perform a linear fit on all η data points.

[0085] The first virtual value is the function value corresponding to the fitted straight line at the target GNSS time. It represents the optimal estimate of the target's attitude angle at that time based on all observations within that time period. This is smoother and better suppresses random noise than any single-point measurement.

[0086] The first covariance matrix is ​​a quantitative indicator of the uncertainty (or accuracy) of this least squares estimation. It originates from the variance of the fitted model and the known (or estimated) measurement noise. The elements in the covariance matrix, especially the element representing the variance of the "first dummy value" estimation error, directly reflect the reliability of this fusion estimation. The greater the noise, the fewer the data points, or the shorter the time span, the larger this variance usually is, indicating that the estimate is more uncertain.

[0087] The output of the first fused data (containing the first dummy value and the first covariance matrix) provides an attitude estimate that is strictly aligned with the GNSS data time, resolving the issue of the IMU and GNSS sampling times not directly coinciding. In subsequent fusion stages such as Kalman filtering, the first covariance matrix is ​​crucial. The filter uses this covariance matrix to determine the weight of the first fused data in the final fusion result; the more uncertain the estimate (larger the covariance), the lower its weight; the more certain the estimate (smaller the covariance), the higher its weight. This achieves automatic weighting based on data quality.

[0088] In short, this step, through the least squares method, not only compresses and synchronizes multiple high-frequency IMU data to a low-frequency time point, but also quantitatively gives the reliability of this synchronization value, providing the necessary weighted synchronization input for subsequent optimal data fusion.

[0089] Further, the τ second initial data points obtained within the current fourth measurement cycle are fused to obtain second fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle, including: The τ initial data points corresponding to the current fourth measurement cycle are fused using the least squares method to obtain a second virtual value and a second covariance matrix of the second virtual value; the second fused data includes the second virtual value and the second covariance matrix.

[0090] The input consists of τ second initial data points arranged in chronological order, each data point containing the estimated displacement increment within a single DVL cycle (e.g., ...). , ) and heading angle increment ( The algorithm fuses each component that needs to be fused (e.g., the X-direction displacement increment). Establish a simple linear motion model independently, assuming that the cumulative rate of change of displacement increment (i.e. velocity) is approximately constant within a short GNSS cycle.

[0091] The least squares algorithm uses τ data points and their corresponding timestamps (relative to the target GNSS time) to perform linear fitting on each motion component.

[0092] The second virtual value is the value corresponding to the fitted straight line at the target GNSS time. It represents the optimal estimate of the displacement increment that the ship should have generated in the past DVL cycle at the GNSS time, based on observations over the past τ DVL cycles. This value smooths out the inherent random noise and possible instantaneous errors in DVL measurements.

[0093] The second covariance matrix is ​​a measure of the uncertainty of this least squares estimation. It is calculated from the noise characteristics of the fitted model and the DVL measurements. This matrix quantifies the estimation error of the second dummy value and reflects the reliability of the estimate.

[0094] The output second fused data (containing the second dummy value and the second covariance matrix) achieves frequency registration, generating a displacement increment estimate that is strictly aligned temporally with the low-frequency GNSS data points, thus resolving the issue of the DVL and GNSS data not directly corresponding on the time axis. It also provides fusion weights; the second covariance matrix is ​​a key input in the subsequent Kalman filter. The filter dynamically determines the confidence weight of the second fused data in the final state update based on this covariance. The more uncertain the estimate (larger covariance), the smaller its impact on the final result; the more accurate the estimate (smaller covariance), the greater its contribution.

[0095] In short, this step uses the least squares method to transform and condense a series of high-frequency relative motion measurements (DVL displacement increments) into an optimal estimate with a clear quality assessment that is time-synchronized with the absolute position measurement (GNSS), providing an accurate and reliable input for subsequent optimal information fusion.

[0096] For example, assuming the GNSS measurement period is The measurement cycle of DVL is And satisfy That is, the measurement frequency of DVL is the measurement frequency of GNSS. times.

[0097] If GNSS is If one frame of data is collected at a given time, the next frame of data should be collected at... Data is collected continuously.

[0098] DVL The detection data were fused using the least squares method to obtain a virtual value. This value was then used as... The estimated value of DVL at time point reduces the positioning data error caused by the frequency inconsistency between GNSS and DVL. The specific steps are as follows: DVL to Detected Each information record is ,Will The virtual values ​​and their derivatives after fusion processing using the least squares method are recorded as follows: ,but The The size of a data point can be expressed as:

[0099] in, To measure noise, the above formula can be further simplified to:

[0100] in, Its mean is 0 and its variance is .

[0101]

[0102] like And to make If the minimum is:

[0103] Therefore, we can conclude that:

[0104] The covariance matrix is:

[0105] In summary, the measured value of DVL and its noise at this time can be expressed as:

[0106]

[0107] in, , It is a constant.

[0108] Further, based on the first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle, the target positioning information of the vessel in the current fourth measurement cycle is determined, including: The first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle are input into the Kalman filter controller to obtain the target positioning information of the ship corresponding to the current fourth measurement cycle.

[0109] The input to the Kalman filter is three sets of data that are strictly synchronized in time and quantized in quality: The first fused data represents the ship's attitude information (heading, roll, pitch) at the current moment and its estimation uncertainty (first covariance matrix). It originates from the fusion of high-frequency IMU data and provides continuous, high-frequency attitude updates.

[0110] Second fusion data: representing the relative displacement increment and turning information of the ship within the previous GNSS cycle ( , , The second covariance matrix (DVL) is derived from the fusion of high-frequency DVL data and provides high-precision short-time trajectory extrapolation independent of external signals.

[0111] Fourth initial data: Represents the absolute position information (latitude, longitude, or planar coordinates) from GNSS at the current moment. It provides a global reference, but updates less frequently and may contain noise or jumps.

[0112] The Kalman filter is a recursive optimal estimation algorithm. In this scenario, using second fused data (displacement increment) and first fused data (attitude), based on the ship's kinematics model, it predicts the ship's current position, velocity, and attitude from the previous moment's "target positioning information." This prediction is primarily based on DVL and IMU, offering advantages of high frequency and continuity, but it accumulates errors (drift) over time. When new fourth initial data (GNSS absolute position) is received, the filter compares the predicted position with the GNSS measured position. Based on the covariance matrix (characterizing the reliability of IMU and DVL predictions) attached to the first and second fused data, and the known measurement noise characteristics of GNSS, the Kalman filter calculates the optimal fusion weights to correct the prediction value, minimizing the estimation variance. The absolute information from GNSS can effectively correct the accumulated drift of DVL / IMU predictions.

[0113] Through the aforementioned continuous prediction and correction loop, the Kalman filter controller outputs optimally fused target positioning information. This is typically a complete navigation state vector, including not only a higher frequency and smoother position (x, y) than a single GNSS output, but also potentially precise velocity (Vx, Vy), heading angle, and attitude angle.

[0114] The Kalman filter fully leverages the advantages of each of the carefully registered multi-source data (the absolute accuracy of GNSS, the high frequency and continuity of DVL / IMU), and dynamically adjusts the trust weights based on their quantization uncertainties, ultimately outputting a set of high-precision and high-complete ship integrated positioning information in a stable and real-time manner.

[0115] In summary, this application's embodiments solve the time reference asynchrony problem caused by independent clock sources for multiple sensors at the hardware level by uniformly sending structured clock signals to each sensor through a reference clock device. This ensures that all measurement data have consistent and accurately traceable time labels, reducing the probability of misusing historical data due to time misalignment. Secondly, addressing the inherent differences in the update frequencies of each sensor's data, high-frequency IMU and DVL data are intelligently registered to the low-frequency GNSS data time, generating time-synchronized fused data with accurate covariance estimation. This reduces the probability of interpolation errors and information loss caused by frequency inconsistency. Finally, this spatiotemporally aligned multi-source data with clear uncertainty metrics is input into a Kalman filter controller, fully leveraging the absolute position accuracy of GNSS, the high-precision relative displacement measurement of DVL, and the continuous attitude update advantages of IMU. Through optimal estimation, a synergistic improvement in positioning information accuracy, continuity, and overall robustness is achieved, providing stable, reliable, and high-precision fused navigation and positioning capabilities for ocean-going vessels in complex sea conditions.

[0116] This application's embodiments achieve multi-level technological breakthroughs and collaborative optimization through the construction of an integrated hardware system and a systematic data processing flow, resulting in significant comprehensive technical effects. First, by distributing structured clock signals to each sensor through a reference clock device controlled by an industrial control computer, the time stamps of all data are unified from the source, essentially eliminating the time reference asynchrony problem caused by independent clock sources for multiple sensors. This reduces the probability of misusing historical data due to time misalignment, laying a precise time alignment foundation for subsequent fusion. Second, addressing the inherent differences in the update frequencies of each sensor's data, periodic data fusion based on the least squares method is used to register high-frequency IMU attitude data and high-frequency DVL displacement increment data to low-frequency GNSS time, generating time-synchronized fused data with accurate covariance estimation. This reduces the probability of interpolation errors and information loss caused by inconsistent sampling frequencies, achieving high-fidelity synchronization of inter-frequency data. Of particular note is the model proposed in this application, which relies solely on two Doppler logs symmetrically deployed on the port and starboard sides to calculate ship position and attitude angle information in real time. This model provides continuous, high-precision relative motion information while significantly reducing the complexity and computational burden of attitude calculation. Finally, the aforementioned spatiotemporally precisely registered multi-source data (synchronized GNSS absolute position, fused IMU attitude, and fused DVL displacement increments) and their quantified uncertainties are input into a Kalman filter controller for optimal estimation. This fully leverages the complementary advantages of each sensor, greatly improving the output frequency, continuity, smoothness, and overall robustness of the positioning information. Ultimately, it yields comprehensive ship positioning information with significantly higher accuracy than any single sensor or a simple fusion method without synchronized processing, providing stable and reliable technical support for high-precision navigation of ocean-going vessels.

[0117] Based on the same inventive concept, embodiments of this application provide a non-transitory computer-readable storage medium that, when the instructions in the storage medium are executed by the ship's industrial control computer, enables the ship to implement a ship multi-sensor positioning information synchronization method as described above.

[0118] Based on the same inventive concept, embodiments of this application provide a computer program product, including computer instructions, which are executed by an industrial control computer to implement a method for synchronizing multi-sensor positioning information of a ship as described above.

[0119] Since the vessel described in this embodiment is the vessel used to implement the information processing method in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the vessel in this embodiment based on the information processing method described in the embodiments of this application. Therefore, how the vessel implements the method in the embodiments of this application will not be described in detail here. Any vessel used by those skilled in the art to implement the information processing method in the embodiments of this application falls within the scope of protection of this application.

[0120] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0122] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0123] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0124] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0125] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A ship, characterized in that, The ship is equipped with an industrial control computer, a reference clock device, an inertial measurement unit, a first Doppler log, a second Doppler log, and a signal receiver for a global navigation satellite system. The reference clock device, the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver are respectively connected to the industrial control computer; The inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver are respectively connected to the reference clock device; The first Doppler log and the second Doppler log are arranged in a mirror-symmetric manner with respect to the longitudinal midsection of the ship and are located in the same transverse section of the ship.

2. A method for synchronizing positioning information from multiple ship sensors, characterized in that, The method, applied to an industrial control computer for a ship as described in claim 1, comprises: The reference clock device is controlled to send reference clock signals to the inertial measurement unit, the first Doppler log, the second Doppler log, and the signal receiver at preset frequencies respectively; The inertial measurement unit is controlled to generate first measurement data according to a first measurement cycle, the first Doppler logger is controlled to generate second measurement data according to a second measurement cycle, the second Doppler logger is controlled to generate third measurement data according to a second measurement cycle, and the signal receiver is controlled to receive fourth measurement data sent by the global navigation satellite system according to a fourth measurement cycle; the first measurement data, the second measurement data, the third measurement data, and the fourth measurement data each carry clock information matching the reference clock signal; the first measurement cycle is η times the fourth measurement cycle, the second measurement cycle is τ times the fourth measurement cycle, and both η and τ are greater than 1; Based on the first measurement data, first initial data related to attitude is determined; based on the second measurement data and the third measurement data with clock matching, second initial data related to displacement increment is determined; and based on the fourth measurement data, fourth initial data related to position is determined. For each fourth measurement cycle, the η first initial data points obtained in the current fourth measurement cycle are fused to obtain first fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle; the τ second initial data points obtained in the current fourth measurement cycle are fused to obtain second fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle; based on the first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle, the target positioning information of the ship in the current fourth measurement cycle is determined.

3. The method for synchronizing multi-sensor positioning information of a ship as described in claim 2, characterized in that, Controlling the reference clock device to send reference clock signals to the inertial measurement unit, the first Doppler logger, the second Doppler logger, and the signal receiver at preset frequencies includes: The reference clock device is controlled to generate a first reference clock signal that matches the first structure of the inertial measurement unit, and the first reference clock signal is sent to the inertial measurement unit at a preset frequency. The reference clock device is controlled to generate a second reference clock signal that matches the second structure of the first Doppler log, and the second reference clock signal is sent to the first Doppler log at a preset frequency; The reference clock device is controlled to generate a third reference clock signal that matches the second structure of the second Doppler log, and the third reference clock signal is sent to the second Doppler log at a preset frequency; The reference clock device is controlled to generate a fourth reference clock signal that matches the fourth structure of the signal receiver, and the fourth reference clock signal is sent to the signal receiver at a preset frequency; The reference clock signal includes the first reference clock signal, the second reference clock signal, the third reference clock signal, and the fourth reference clock signal.

4. The method for synchronizing multi-sensor positioning information of a ship as described in claim 2, characterized in that, Based on the second and third measurement data with clock matching, second initial data related to the displacement increment is determined, including: For each consecutive second measurement data and the next second measurement data obtained by the first Doppler log, and for each consecutive third measurement data and the next third measurement data obtained by the second Doppler log, the clocks of the previous second measurement data and the next second measurement data are matched, and the clocks of the next second measurement data and the next third measurement data are matched. Based on the previous second measurement data and the next second measurement data, the first actual mileage of the first Doppler log in the current second measurement cycle is determined, and the second actual mileage of the second Doppler log in the current second measurement cycle is determined based on the previous third measurement data and the next third measurement data. Based on the first actual voyage mileage, the second actual voyage mileage, the installation distance between the first Doppler log and the second Doppler log, and the previous heading angle corresponding to the start time of the current second measurement cycle, the second initial data related to the displacement increment of the ship in the current second measurement cycle is determined.

5. The method for synchronizing multi-sensor positioning information of a ship as described in claim 4, characterized in that, Based on the first actual voyage mileage, the second actual voyage mileage, the installation distance between the first and second Doppler logs, and the previous heading angle corresponding to the start time of the current second measurement cycle, the second initial data related to the displacement increment of the ship in the current second measurement cycle is determined, including: Based on the first actual voyage mileage and the second actual voyage mileage, the actual voyage mileage of the ship in the current second measurement cycle is determined; Based on the first actual voyage mileage, the second actual voyage mileage, and the installation distance between the first Doppler log and the second Doppler log, the ship's heading angle increment from the start time to the end time of the current second measurement cycle is determined; The turning radius of the ship in the current second measurement cycle is determined based on the ship's actual voyage distance and the ship's heading angle increment. Based on the turning radius, the ship's heading angle increment, and the ship's previous heading angle at the start of the current second measurement cycle, the second initial data related to the displacement increment for the ship in the current second measurement cycle is determined.

6. The method for synchronizing multi-sensor positioning information of a ship as described in claim 2, characterized in that, The η first initial data points obtained in the current fourth measurement cycle are fused to obtain first fused data synchronized with the fourth initial data in the current fourth measurement cycle, including: The η initial data points obtained in the current fourth measurement cycle are fused using the least squares method to obtain a first virtual value and a first covariance matrix of the first virtual value; the first fused data includes the first virtual value and the first covariance matrix.

7. A method for synchronizing multi-sensor positioning information of a ship as described in claim 2, characterized in that, The τ second initial data points obtained within the current fourth measurement cycle are fused to obtain second fused data synchronized with the fourth initial data corresponding to the current fourth measurement cycle, including: The τ initial data points corresponding to the current fourth measurement cycle are fused using the least squares method to obtain a second virtual value and a second covariance matrix of the second virtual value; the second fused data includes the second virtual value and the second covariance matrix.

8. A method for synchronizing multi-sensor positioning information of a ship as described in claim 2, characterized in that, Based on the first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle, the target positioning information of the vessel in the current fourth measurement cycle is determined, including: The first fused data, the second fused data, and the fourth initial data corresponding to the current fourth measurement cycle are input into the Kalman filter controller to obtain the target positioning information of the ship corresponding to the current fourth measurement cycle.

9. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the ship's industrial control computer, the ship is able to implement a ship multi-sensor positioning information synchronization method as described in any one of claims 2 to 8.

10. A computer program product, characterized in that, It includes computer instructions, which are executed by an industrial control computer to implement a method for synchronizing multi-sensor positioning information of a ship as described in any one of claims 2 to 8.

Images