An intelligent amphibious ship navigation and positioning method, system and storage medium

Abstract

The present invention relates to the technical field of ship radio positioning, and particularly relates to an intelligent amphibious ship navigation and positioning method, system and storage medium. The method includes the following steps: analyzing the inertial position of the amphibious ship to obtain the inertial position data of the amphibious ship; compensating the navigation speed of the amphibious ship by using a Doppler log to generate ship Doppler compensation speed data; performing radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; dynamically correcting navigation parameters according to the inertial position data of the amphibious ship, the ship Doppler compensation speed data and the amphibious ship radio positioning data to obtain intelligent ship position positioning data; and displaying the intelligent ship position positioning data on a navigation display terminal to obtain amphibious ship navigation display information. The present invention realizes high-precision and high-reliability amphibious ship navigation and positioning through dynamic correction of navigation parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of ship radio positioning, and particularly to an intelligent amphibious ship navigation and positioning method, system and storage medium. Background Art

[0002] Amphibious ships, which have the ability to navigate on water and travel on land, have more special navigation and positioning requirements and need to adapt to two completely different environments, namely water surface and land. Traditional ship navigation and positioning methods mainly rely on global navigation satellite systems (GNSS) such as GPS and Beidou. GNSS calculates the position and speed information of the ship by receiving signals from multiple satellites. However, GNSS signals are easily blocked by obstacles such as buildings and trees. Especially in areas near the shore, ports, and inland rivers, the accuracy and reliability of the signals will decrease significantly. In addition, the positioning accuracy of GNSS in the land environment is also affected by factors such as terrain and vegetation, making it difficult to meet the high-precision navigation and positioning requirements of amphibious ships. However, traditional navigation and positioning methods are prone to position lag when dealing with rapid ship course changes, resulting in navigation delay problems. These methods usually calculate based on the current position and speed of the ship without fully considering dynamic information such as the ship's acceleration and turning rate. When the ship makes a rapid course change, its acceleration and turning rate will change violently, leading to navigation delay, which is particularly obvious during the water-land conversion process of amphibious ships. Summary of the Invention

[0003] Based on this, the present invention provides an intelligent amphibious ship navigation and positioning method, system and storage medium to solve at least one of the above technical problems.

[0004] To achieve the above object, an intelligent amphibious ship navigation and positioning method includes the following steps:

[0005] Step S1: Perform real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation based on the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data;

[0006] Step S2: Obtain the data of the navigation environment type of the amphibious ship; perform Doppler effect navigation speed compensation on the amphibious ship using a Doppler log based on the data of the navigation environment type of the amphibious ship to generate ship Doppler compensation speed data;

[0007] Step S3: Perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform spatio-temporal reference alignment processing based on the amphibious ship inertial position data, ship Doppler compensation speed data, and amphibious ship radio positioning data to generate spatio-temporal synchronized positioning and monitoring data; perform dynamic correction of navigation parameters based on the spatio-temporal synchronized positioning and monitoring data to obtain intelligent ship position positioning data;

[0008] Step S4: Perform navigation map matching on the intelligent ship position positioning data and display it on the navigation display terminal to obtain amphibious ship navigation display information.

[0009] Through real-time ship inertial measurement and attitude mode annotation, the present invention obtains accurate ship attitude angle data, and conducts inertial position analysis based on this to obtain amphibious ship inertial position data. Compared with the traditional method that simply relies on GNSS, by taking advantage of the strong autonomy of INS and its immunity to external environmental interference, it effectively compensates for the defect of the decline in the accuracy of GNSS in case of signal occlusion or interference. Especially in areas where GNSS signals are vulnerable to influence, such as near shore, ports, inland rivers, and land environments, it can provide more reliable position information to ensure the continuous navigation ability of amphibious ships in various complex environments. According to different types of navigation environment data, a Doppler log is used for navigation speed compensation (Step S2). Due to the huge differences in the characteristics of resistance, friction, etc. between water and land environments, the speed of the ship changes violently during the water-land conversion process. Traditional navigation methods based on constant speed or simple speed models are difficult to accurately estimate the real-time speed of the ship, resulting in positioning errors. However, this method can correct the ship speed in real time through Doppler effect navigation speed compensation, improving the accuracy of navigation positioning. Especially in the dynamic environment of water-land conversion, it effectively solves the problem of inaccurate speed estimation by traditional methods and ensures the accuracy of navigation information. Through spatio-temporal reference alignment, the time difference and space difference between different data sources are eliminated, ensuring the consistency and reliability of the data. Based on the spatio-temporal synchronized positioning and monitoring data, this method can correct navigation parameters such as position, speed, and attitude in real time, further improving the accuracy and real-time performance of navigation positioning, and effectively solving the problems of position lag and navigation delay in traditional methods when the ship quickly changes direction. Especially when the amphibious ship performs complex operations such as water-land conversion, quick turning, or acceleration and deceleration, it can more accurately capture the motion state of the ship and provide more timely navigation information, thereby enhancing the reliability and safety of navigation. Therefore, an intelligent amphibious ship navigation positioning method of the present invention effectively solves the problems of low positioning accuracy and large delay in traditional navigation methods in amphibious environments through integrating multi-source navigation information, dynamically correcting navigation parameters, and electronic map matching, realizing high-precision, high-reliability, and high-real-time amphibious ship navigation positioning, and significantly improving the navigation safety and operation efficiency of amphibious ships.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: Fix and install an inertial measurement unit on the hull of the amphibious ship, and start the inertial measurement unit to perform real-time ship inertial measurement, generating original ship inertial measurement data;

[0012] Step S12: Perform data preprocessing on the original ship inertial measurement data to obtain preprocessed ship inertial measurement data;

[0013] Step S13: Extract angular velocity based on the preprocessed ship inertial measurement data to generate ship angular velocity;

[0014] Step S14: Perform time integration based on the ship angular velocity and perform real-time ship attitude mode annotation through a preset ship attitude mode library to obtain real-time ship attitude angle data;

[0015] Step S15: Calculate attitude angle increment based on the real-time ship attitude angle data and perform linear velocity integration to generate preliminary ship linear velocity data;

[0016] Step S16: Perform amphibious ship inertial position analysis based on the real-time ship attitude angle data and the preliminary ship linear velocity data to obtain amphibious ship inertial position data.

[0017] In the present invention, by fixedly installing an inertial measurement unit on the hull and starting real-time measurement, original ship inertial measurement data is obtained, laying the foundation for subsequent high-precision inertial navigation. Preprocessing the original data can effectively remove noise and interference, improve data quality, and provide more reliable input for subsequent attitude solution and position analysis. Through angular velocity extraction and time integration, and combining with a preset ship attitude mode library for real-time attitude mode annotation, the attitude angle data of the ship can be accurately obtained, which is a key link in inertial navigation. The introduction of the attitude mode library can effectively identify the motion modes of the ship, such as straight-line navigation, turning, water-land conversion, etc., thereby improving the accuracy and robustness of attitude solution. Especially in the case of complex maneuvers of amphibious ships, it can more accurately reflect the attitude changes of the ship. Calculating attitude angle increment and linear velocity integration based on real-time attitude angle data can obtain more accurate ship linear velocity data, avoiding positioning errors caused by inaccurate speed estimation in traditional methods. Finally, combining real-time attitude angle data and accurate linear velocity data for amphibious ship inertial position analysis can obtain high-precision amphibious ship inertial position data.

[0018] Preferably, step S16 includes the following steps:

[0019] Step S161: Use the GNSS navigation system to obtain the real-time rough position of the amphibious ship to obtain amphibious ship rough position data;

[0020] Step S162: Use the rough position data of the amphibious ship as the calibrated positioning position, and calculate the inertial movement position of the ship based on the real-time ship attitude angle data and the preliminary ship linear velocity data to generate ship inertial movement node data;

[0021] Step S163: Perform navigation coordinate conversion on the ship inertial movement node data, and draw a ship movement curve based on the rough position data of the amphibious ship to obtain ship inertial drift curve data;

[0022] Step S164: Identify the ship stationary state for the ship inertial drift curve data based on the real-time ship attitude angle data and the preliminary ship linear velocity data to obtain ship stationary state data;

[0023] Step S165: Make a zero-speed judgment according to the ship stationary state data, and perform node zero-speed correction marking on the ship inertial drift curve data to obtain a node zero-speed correction flag;

[0024] Step S166: Set the speed of the ship inertial drift curve data to zero through the node zero-speed correction flag, and perform zero-speed position error correction to generate amphibious ship inertial position data.

[0025] The present invention uses GNSS to obtain the rough position data of the amphibious ship, providing an initial reference point for subsequent inertial position calculation. Using the rough position data as the calibrated positioning position and combining the real-time attitude angle data and the preliminary linear velocity data to calculate the inertial movement position, a series of ship inertial movement node data can be obtained, and these node data constitute the movement trajectory of the ship. Through navigation coordinate conversion and ship movement curve drawing, the inertial drift of the ship can be intuitively displayed. Identifying the ship stationary state for the inertial drift curve data and making a zero-speed judgment according to the stationary state data are the keys to realizing zero-speed correction. When the ship is in a stationary state, its speed is theoretically zero, but due to the errors and drifts of the inertial measurement unit, the actually measured speed is often not zero. By identifying the stationary state of the ship, node zero-speed correction marking can be performed on the inertial drift curve, and the speed can be set to zero at the marked nodes, thereby correcting the cumulative error of inertial navigation.

[0026] Preferably, step S2 includes the following steps:

[0027] Step S21: Use a Doppler log to monitor the real-time navigation speed to obtain the initial navigation speed of the amphibious ship;

[0028] Step S22: Obtain the data of the navigation environment type of the amphibious ship;

[0029] Step S23: Select the Doppler log speed measurement mode according to the data of the navigation environment type of the amphibious ship to obtain the Doppler log speed measurement mode;

[0030] Step S24: Perform Doppler effect compensation on the initial amphibious ship navigation speed through the Doppler log speed measurement mode to obtain ship Doppler compensation speed data.

[0031] Due to the huge differences in the physical characteristics of the water and land environments in the present invention, the speed measurement modes and accuracies of the Doppler log also vary in different environments. Selecting a suitable speed measurement mode according to the navigation environment type data can maximize the performance of the Doppler log and improve the accuracy of speed measurement. For example, when sailing in water, the bottom tracking mode can be selected; when driving on land, the land mode can be selected. This method of adaptively selecting the speed measurement mode according to the environment effectively improves the adaptability and robustness of speed measurement, ensuring accurate speed information can be obtained in different environments. Finally, perform Doppler effect compensation on the initial navigation speed through the selected Doppler log speed measurement mode to obtain ship Doppler compensation speed data. The Doppler effect compensation takes into account the influence of the relative motion between the ship's movement and the medium (water or land) on speed measurement, thereby eliminating the error caused by the Doppler effect and further improving the accuracy of speed measurement.

[0032] Preferably, step S3 includes the following steps:

[0033] Step S31: Use the amphibious ship to receive radio positioning signals to obtain radio frequency signals;

[0034] Step S32: Perform radio positioning processing according to the radio frequency signals to generate amphibious ship radio positioning data;

[0035] Step S33: Perform spatio-temporal reference alignment processing on the amphibious ship inertial position data, ship Doppler compensation speed data, and amphibious ship radio positioning data to generate spatio-temporally synchronized positioning and monitoring data;

[0036] Step S34: Establish an inertial navigation error model based on the amphibious ship inertial position data in the spatio-temporally synchronized positioning and monitoring data;

[0037] Step S35: Use the ship Doppler compensation speed data in the spatio-temporally synchronized positioning and monitoring data to calculate the speed vector difference of the inertial navigation error model and perform navigation axial coordinate projection to generate inertial navigation speed data;

[0038] Step S36: Establish position constraint conditions based on the amphibious ship radio positioning data in the spatio-temporally synchronized positioning and monitoring data, and use the inertial navigation speed data to perform dynamic correction of navigation parameters to obtain intelligent ship position positioning data.

[0039] The spatio-temporal synchronization of the present invention ensures the time and space consistency between different data sources, improving the accuracy and reliability of data fusion. Based on the spatio-temporal synchronized inertial position data, an inertial navigation error model is established, which can effectively analyze and quantify the errors of the inertial navigation system, providing a basis for subsequent error correction. By using Doppler compensated velocity data to calculate the velocity vector difference and project the navigation axial coordinates of the inertial navigation error model, more accurate inertial navigation velocity data can be generated. The Doppler velocity data provides correction information for the inertial navigation velocity, thereby reducing the error of the inertial navigation velocity and improving the navigation accuracy. By establishing position constraint conditions using radio positioning data and dynamically correcting navigation parameters in combination with accurate inertial navigation velocity data, more accurate and reliable intelligent ship position positioning data can be obtained.

[0040] Preferably, step S32 includes the following steps:

[0041] Step S321: Enhance the signal-to-noise ratio of the radio frequency signal and perform satellite signal acquisition to obtain acquisition result data; the satellite signal acquisition searches for the pseudo-code phase and carrier frequency of the radio frequency signal and determines whether there is a valid positioning signal.

[0042] Step S322: When there is a valid signal in the acquisition result data, track the satellite signal to obtain tracking loop signal data.

[0043] Step S323: Demodulate the pseudo-code based on the tracking loop signal data to obtain pseudo-range data.

[0044] Step S324: Smooth the pseudo-range data by carrier phase to obtain smoothed pseudo-range data.

[0045] Step S325: Suppress the multipath error of the smoothed pseudo-range data through the amphibious ship navigation environment type data to obtain multipath suppressed pseudo-range data.

[0046] Step S326: Use the multipath suppressed pseudo-range data to perform position calculation on the amphibious ship to generate amphibious ship radio positioning data.

[0047] By enhancing the signal-to-noise ratio of radio frequency signals and capturing satellite signals, the present invention can improve the signal quality, identify effective positioning signals, and lay a foundation for subsequent signal tracking and demodulation. Tracking the captured satellite signals can obtain more accurate signal parameters, such as pseudo-code phase and carrier frequency, providing more reliable data for pseudo-range measurement. Based on the signal data of the tracking loop, pseudo-code demodulation can be performed to obtain pseudo-range data, which is a key step in radio positioning. Carrier phase smoothing of the pseudo-range data can effectively reduce the influence of noise and multipath errors in pseudo-range measurement and improve the accuracy of pseudo-range measurement. Using the data of the navigation environment type of amphibious ships to suppress multipath errors in the smoothed pseudo-range data further improves the reliability of the pseudo-range data. Since the navigation environment of amphibious ships is complex and changeable, the influence of multipath effects is particularly significant. According to different navigation environment types, corresponding error suppression strategies can be adopted to effectively reduce the influence of multipath errors and improve the positioning accuracy. For example, in the near-shore or densely built-up areas, stronger multipath suppression algorithms can be used. Finally, using the pseudo-range data with multipath error suppression to perform position calculation on amphibious ships can obtain more accurate and reliable radio positioning data of amphibious ships.

[0048] Preferably, step S325 includes the following steps:

[0049] Query the occurrence probability of multipath effects according to the data of the navigation environment type of amphibious ships to obtain multipath occurrence probability data;

[0050] Conduct multipath effect analysis based on the multipath occurrence probability data and establish a multipath signal model using the smoothed pseudo-range data to obtain a multipath signal model;

[0051] Identify multipath signals in the radio frequency signals through the multipath signal model and estimate the multipath signal errors using the antenna array fixedly installed on the amphibious ship to obtain multipath signal error data;

[0052] Compensate the multipath errors in the smoothed pseudo-range data using the multipath signal error data to obtain compensated pseudo-range data;

[0053] Perform narrowband filtering suppression on the compensated pseudo-range data to generate pseudo-range data with multipath suppression for ships.

[0054] According to the present invention, by querying the multipath effect occurrence probability based on the navigation environment type data of an amphibious ship and conducting multipath effect analysis, the risk of multipath error can be effectively evaluated, providing guidance for subsequent multipath error suppression. Establishing a multipath signal model based on the multipath occurrence probability data and the smoothed pseudorange data can more accurately describe the characteristics of multipath signals, providing a basis for multipath signal identification and error estimation. Using the established multipath signal model to identify multipath signals in radio frequency signals and combining with an antenna array for multipath signal error estimation can more precisely quantify the magnitude and direction of multipath error. The introduction of the antenna array can effectively distinguish direct signals from multipath signals and improve the accuracy of multipath error estimation. Using the estimated multipath signal error data to compensate the smoothed pseudorange data for multipath error can effectively reduce the influence of multipath error and improve the accuracy of pseudorange measurement. Conducting narrowband filtering suppression on the compensated pseudorange data can further remove residual multipath error and noise, improve the signal-to-noise ratio of the pseudorange data, and thus generate purer and more reliable pseudorange data for ship multipath suppression.

[0055] Preferably, step S4 includes the following steps:

[0056] Step S41: Perform geographic coordinate conversion on the intelligent ship position positioning data to obtain geographic coordinate data;

[0057] Step S42: Process the navigation coordinates according to the geographic coordinate data and perform navigation map matching through preset electronic chart data to obtain matched navigation data;

[0058] Step S43: Display the matched navigation data on a navigation display terminal to obtain amphibious ship navigation display information.

[0059] The present invention converts the intelligent ship position positioning data into geographic coordinate data, making the position information easier to understand and use and facilitating integration with other geographic information systems. Processing the navigation coordinates based on the geographic coordinate data and performing navigation map matching through preset electronic chart data can associate the ship's positioning information with the geographic information on the electronic chart, thereby providing richer navigation information. The map matching technology can effectively correct positioning errors, improve navigation accuracy, and provide a more intuitive navigation display. For example, the position of the ship can be accurately displayed on the electronic chart, and information such as the surrounding terrain, waterways, and obstacles can be shown. Displaying the matched navigation data on the navigation display terminal can provide users with clear and intuitive navigation information, such as the ship's current position, heading, speed, destination, etc., as well as auxiliary information such as electronic charts, route planning, and obstacle alerts.

[0060] Preferably, the present invention further provides an intelligent amphibious ship navigation and positioning system, which executes the intelligent amphibious ship navigation and positioning method as described above. The intelligent amphibious ship navigation and positioning system includes:

[0061] A ship inertial measurement module, which is used to perform real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation based on the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data;

[0062] A Doppler log compensation module, which is used to obtain the data of the navigation environment type of the amphibious ship; perform Doppler effect navigation speed compensation on the amphibious ship using a Doppler log based on the data of the navigation environment type of the amphibious ship to generate ship Doppler compensation speed data;

[0063] A spatio-temporal navigation and positioning correction module, which is used to perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform spatio-temporal reference alignment processing based on the amphibious ship inertial position data, ship Doppler compensation speed data, and amphibious ship radio positioning data to generate spatio-temporal synchronous positioning monitoring data; perform dynamic correction of navigation parameters based on the spatio-temporal synchronous positioning monitoring data to obtain intelligent ship position positioning data;

[0064] An intelligent navigation display module, which is used to perform navigation map matching on the intelligent ship position positioning data and perform display on a navigation display terminal to obtain amphibious ship navigation display information.

[0065] Preferably, the present invention further provides a computer-readable storage medium storing a computer program, and when the computer program is executed, it implements the intelligent amphibious ship navigation and positioning method as described in any one of the above. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a schematic flow chart of the steps of the intelligent amphibious ship navigation and positioning method of the present invention;

[0067] Figure 2 is Figure 1 a schematic detailed implementation step flow chart of step S1 in

[0068] Figure 3 is Figure 1 a schematic detailed implementation step flow chart of step S3 in

[0069] The realization, functional features, and advantages of the object of the present invention will be further described in conjunction with embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0070] The technical method of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present invention.

[0071] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus the repeated description thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0072] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0073] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides an intelligent amphibious ship navigation and positioning method, including the following steps:

[0074] Step S1: Perform real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation according to the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data;

[0075] Step S2: Obtain the data of the type of the navigation environment of the amphibious ship; use the Doppler log to perform Doppler effect navigation speed compensation on the amphibious ship based on the data of the type of the navigation environment of the amphibious ship to generate ship Doppler compensation speed data;

[0076] Step S3: Perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform space-time reference alignment processing according to the amphibious ship inertial position data, the ship Doppler compensation speed data, and the amphibious ship radio positioning data to generate space-time synchronous positioning and monitoring data; perform dynamic correction of navigation parameters based on the space-time synchronous positioning and monitoring data to obtain intelligent ship position positioning data;

[0077] Step S4: Perform navigation map matching on the intelligent ship position positioning data and display it on the navigation display terminal to obtain the amphibious ship navigation display information.

[0078] In the embodiment of the present invention, the intelligent amphibious ship navigation and positioning method includes the following steps:

[0079] Step S1: Perform real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation according to the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data;

[0080] In the embodiment of the present invention, an inertial measurement unit (IMU) of model Xsens MTi-G-710 is fixedly installed at the center of the hull of the amphibious ship to ensure that the measurement axes of the IMU are aligned with the hull coordinate system. The three-axis acceleration and three-axis angular velocity data are collected at a frequency of 200 Hz to generate the original ship inertial measurement data, which is transmitted to the navigation computer through the data bus in the IEEE 754 floating-point data format. In the navigation computer, temperature compensation is performed using the pre-determined IMU temperature coefficient, and the zero bias value obtained from the static measurement is subtracted to preprocess the original data. The error state Kalman filter is used to perform attitude solution on the preprocessed inertial data. The state vector includes attitude error, gyroscope zero bias, and accelerometer zero bias, and the measurement vector is the measurement values of the accelerometer and gyroscope. The state equation of the Kalman filter is based on the IMU kinematic model, and the measurement equation is based on the IMU measurement model. The attitude error is estimated through Kalman filtering, and the initial attitude is corrected to obtain the real-time roll angle, pitch angle, and heading angle (in Euler angle form) with an update frequency of 200 Hz, which constitutes the real-time ship attitude angle data. The attitude angle data is combined with the initial position information provided by the GNSS, and the linear velocity and position are integrated using the fourth-order Runge-Kutta method to obtain the inertial position data (longitude, latitude, and altitude) of the amphibious ship with an update frequency of 200 Hz.

[0081] Step S2: Obtain the data of the amphibious ship navigation environment type; perform Doppler effect navigation speed compensation on the amphibious ship using the Doppler log based on the data of the amphibious ship navigation environment type to generate the ship Doppler compensation speed data;

[0082] In the embodiments of the present invention, environmental data is collected in real time through a water level sensor (e.g., an ultrasonic water level sensor with a measurement range of 0 - 5 meters and an accuracy of 1 cm), a GPS positioning module (e.g., u-blox ZED-F9P with a positioning accuracy of 1 meter), and an attitude sensor (e.g., Xsens MTi-G-710) installed on an amphibious ship. The data transmission frequency is 10 Hz for all. The navigation computer determines whether the ship is in a water surface navigation state according to the water level height threshold (e.g., 0.5 meters), determines whether the ship is in a land navigation state according to the GPS position information, and determines the rest of the situations as the intertidal zone navigation state, generating data on the navigation environment type of the amphibious ship. A Teledyne Workhorse Navigator DVL Doppler log is installed at the bottom of the amphibious ship to measure the speed of the ship relative to the water bottom or the ground, and the data update frequency is 10 Hz. When navigating on the water surface, the "water bottom tracking mode" of the DVL is activated, and a water flow sensor installed on the ship (e.g., Valeport Midas ECM with a measurement range of 0 - 5 m / s and an accuracy of 1 cm / s) is used to measure the water flow speed and direction. The water flow velocity vector is subtracted from the velocity vector measured by the DVL for Doppler effect navigation speed compensation. When navigating in the intertidal zone and on land, the "bottom tracking mode" and "ground tracking mode" of the DVL are activated respectively, and no Doppler effect compensation is required. The processed speed data is used as the ship's Doppler compensation speed data.

[0083] Step S3: Perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform space-time reference alignment processing according to the amphibious ship inertial position data, the ship Doppler compensation speed data, and the amphibious ship radio positioning data to generate space-time synchronized positioning and monitoring data; perform dynamic correction of navigation parameters based on the space-time synchronized positioning and monitoring data to obtain intelligent ship position positioning data;

[0084] In an embodiment of the present invention, a Trimble MB-Two multibeam receiver is installed on an amphibious ship to receive radio signals from a shore-based ultra-short baseline (USBL) positioning system, and the data update frequency is 1 Hz. The USBL system consists of a main base station and three auxiliary base stations, and the positions of the base stations are known and fixed. The navigation computer receives the radio frequency signals and calculates the distances between the ship and each base station by measuring the time differences of the signals arriving at the shipborne receiver and each auxiliary base station. Using this distance information and the known positions of the base stations, three-dimensional spatial positioning is performed by the least squares method to generate amphibious ship radio positioning data (longitude, latitude, and altitude). The navigation computer receives the inertial position data (200 Hz), ship Doppler compensation speed data (10 Hz), and amphibious ship radio positioning data (1 Hz) of the amphibious ship. The linear interpolation method is used to unify the three types of data to 10 Hz, and the Precision Time Protocol (PTP) is used for time synchronization to generate spatio-temporally synchronized positioning and monitoring data. Based on this data, an error state Kalman filter is used to dynamically correct the navigation parameters. The state vector of the Kalman filter includes position error, speed error, attitude error, IMU zero bias, and clock error, and the measurement vector is the USBL position and DVL speed. The state error is estimated through Kalman filtering, and the inertial navigation solution result is corrected to obtain intelligent ship position positioning data (longitude, latitude, altitude, speed, and attitude), with an update frequency of 10 Hz.

[0085] Step S4: Perform navigation map matching on the intelligent ship position positioning data and display it on a navigation display terminal to obtain amphibious ship navigation display information.

[0086] In an embodiment of the present invention, the intelligent ship position positioning data is converted from the WGS84 coordinate system to the UTM coordinate system to obtain geographic coordinate data. The moving average filter is used to smooth the geographic coordinate data, and the window size is set to 5. The smoothed geographic coordinate data is matched with the preset S-57 standard electronic chart data. The point-to-segment distance matching algorithm is adopted, and the search radius is set to 10 meters to find the nearest channel or coastline to obtain the matching navigation data, including the position, heading, and speed of the ship on the electronic chart. The matching navigation data is displayed on the navigation display terminal (for example, MaxSeaTimeZero ECDIS). Information such as the real-time position, heading, speed, surrounding environment (such as water depth, obstacles, channels, etc.), and preset route of the amphibious ship is displayed on the electronic chart.

[0087] Preferably, step S1 includes the following steps:

[0088] Step S11: Fix an inertial measurement unit on the hull of the amphibious ship and start the inertial measurement unit to perform real-time ship inertial measurement to generate original ship inertial measurement data;

[0089] Step S12: Perform data preprocessing on the original ship inertial measurement data to obtain preprocessed ship inertial measurement data;

[0090] Step S13: Extract angular velocity based on the preprocessed ship inertial measurement data to generate ship angular velocity;

[0091] Step S14: Perform time integration based on the ship angular velocity and perform real-time ship attitude mode annotation through a preset ship attitude mode library to obtain real-time ship attitude angle data;

[0092] Step S15: Calculate attitude angle increments based on the real-time ship attitude angle data and perform linear velocity integration to generate preliminary ship linear velocity data;

[0093] Step S16: Perform amphibious ship inertial position analysis based on the real-time ship attitude angle data and the preliminary ship linear velocity data to obtain amphibious ship inertial position data.

[0094] As an example of the present invention, refer to Figure 2 shown in Figure 1 is a schematic diagram of the detailed implementation steps of step S1 in

[0095] Step S11: Fix and install an inertial measurement unit on the hull of the amphibious ship, and start the inertial measurement unit to perform real-time ship inertial measurement to generate original ship inertial measurement data;

[0096] In the embodiment of the present invention, a rigid, flat and horizontal installation base is selected. Use high-strength bolts to firmly fix the IMU on the base to ensure that the IMU will not have relative displacement or vibration during ship navigation. The X-axis, Y-axis and Z-axis of the IMU need to be aligned with the longitudinal, transverse and vertical directions of the ship respectively, and the allowable deviation angle is less than 0.1 degree. Use a precision level and an angle gauge for measurement and adjustment. After the installation is completed, perform the electrical connection of the IMU. Connect the power supply line of the IMU to the ship's power supply system (such as a 24V DC power supply) and ensure that the power supply is stable and reliable. Connect the data output line of the IMU (such as RS422 or CAN bus) to the data processing unit. Then, start the IMU. The IMU usually has a self-check function and will automatically perform internal circuit inspection and sensor preheating after startup. The preheating time usually takes 30 minutes to 1 hour to ensure that the sensor reaches a stable operating temperature. After the preheating is completed, the IMU starts to output the original ship inertial measurement data at a set sampling frequency (such as 200Hz), including the linear acceleration measured by the three-axis accelerometer (unit: m / s²) and the angular velocity measured by the three-axis gyroscope (unit: ° / s).

[0097] Step S12: Perform data preprocessing on the original ship inertial measurement data to obtain preprocessed ship inertial measurement data;

[0098] In the embodiment of the present invention, the original ship inertial measurement data is filtered. Due to factors such as ship vibration and wave impact, the original data usually contains a large amount of high-frequency noise. A low-pass filter is used to filter out this noise. For example, a Butterworth low-pass filter with a cut-off frequency of 20 Hz can be used. The specific implementation method is as follows: Pass the original data through a digital filter, and the transfer function of this filter is determined according to the design formula of the Butterworth filter. The order of the filter (such as 4th order or 8th order) needs to be adjusted according to the actual situation. The higher the order, the better the filtering effect, but the greater the delay. The filtered data will become smoother. Then, zero-bias correction is performed. The IMU sensor has an inherent zero-bias error, that is, it will output a non-zero value even in the stationary state. The zero-bias error will drift slowly over time. Estimate the zero-bias through static data acquisition. The specific operation is as follows: When the ship is in a stationary state, collect IMU data for a period of time (such as 10 minutes) and calculate the average value. Take this average value as the estimated value of the zero-bias error.

[0099] Step S13: Extract the angular velocity according to the preprocessed ship inertial measurement data to generate the ship angular velocity;

[0100] In the embodiment of the present invention, the angular velocity information of the ship is extracted from the preprocessed IMU data. The preprocessed ship inertial measurement data includes triaxial accelerometer data and triaxial gyroscope data. Directly extract the output values of the triaxial gyroscopes from the preprocessed data, which are the angular velocities of the ship. These angular velocity data respectively correspond to the rotation rates of the ship around its own three axes (longitudinal axis, transverse axis, and vertical axis). For example, if the output of the gyroscope X-axis is 0.5° / s, it means that the ship is rotating around its longitudinal axis (i.e., rolling) at a speed of 0.5 degrees per second. The triaxial angular velocity data is output in digital form. For example, it is transmitted through the RS422 interface in a specific data format (such as including a frame header, data type identifier, data value, checksum, etc.). After the data processing unit receives these data, it parses them according to the data format and extracts the angular velocity values in three directions to generate ship angular velocity data. The unit is degrees per second (° / s).

[0101] Step S14: Perform time integration according to the ship angular velocity and perform real-time ship attitude mode annotation through a preset ship attitude mode library to obtain real-time ship attitude angle data;

[0102] In the embodiments of the present invention, angular velocity data is integrated to obtain attitude angles and attitude mode annotation is performed. First, time integration is performed on the angular velocity data of the ship. The quaternion method is used for integration, which can avoid the gimbal lock problem in Euler angle integration. Specific operation: Substitute the angular velocity data at the current moment and the quaternion at the previous moment into the quaternion differential equation to calculate the quaternion at the current moment. The quaternion represents the attitude of the ship relative to the reference coordinate system (for example, the navigation coordinate system). Then, the quaternion is converted into Euler angles (roll angle, pitch angle, and heading angle) to obtain the real-time attitude angle data of the ship. To improve the integration accuracy, a high-order integration algorithm such as the Runge-Kutta method can be used. Then, attitude mode annotation is performed. A ship attitude mode library is established, which contains predefined attitude modes and their corresponding attitude angle ranges.

[0103] Step S15: Calculate the attitude angle increment based on the real-time ship attitude angle data, and perform linear velocity integration to generate preliminary ship linear velocity data;

[0104] In the embodiments of the present invention, the attitude angle increment is calculated according to the attitude angles. The attitude angle increment refers to the change in attitude angles between two adjacent sampling moments. Subtract the attitude angle at the previous moment from the attitude angle at the current moment to obtain the attitude angle increment. For example, if the roll angle at the current moment is 15.2 degrees and the roll angle at the previous moment is 15.0 degrees, the roll angle increment is 0.2 degrees. Then, integrate the linear acceleration. Before integration, the linear acceleration measured by the accelerometer needs to be converted from the body coordinate system to the navigation coordinate system. A rotation matrix is constructed using the attitude angle data to convert the acceleration vector in the body coordinate system to the navigation coordinate system. Then, integrate the acceleration in the navigation coordinate system to obtain preliminary linear velocity data. The trapezoidal integration method or the Simpson integration method is used. For example, if the X-axis acceleration in the navigation coordinate system at the current moment is 0.1 m / s², the X-axis velocity at the previous moment is 0 m / s, and the sampling time interval is 0.01 seconds, the X-axis velocity at the current moment calculated using the trapezoidal integration method is . Due to the errors of the accelerometer, the linear velocity obtained by integration will drift over time.

[0105] Step S16: Perform amphibious ship inertial position analysis based on the real-time ship attitude angle data and the preliminary ship linear velocity data to obtain amphibious ship inertial position data.

[0106] In the embodiments of the present invention, the preliminary linear velocity data is integrated twice to obtain the position increment. The trapezoidal integration method or the Simpson integration method is also used. For example, if the X-axis velocity in the navigation coordinate system at the current moment is 0.001 m / s, the X-axis position at the previous moment is 0 m, and the sampling time interval is 0.01 seconds, the X-axis position increment at the current moment calculated using the trapezoidal integration method is Then, the position increment is accumulated to the position at the previous moment to obtain the position at the current moment. To obtain the absolute position, an initial position needs to be input as a reference. For example, when the ship starts the navigation system, an initial position (longitude, latitude, and altitude) is obtained through GPS or other positioning methods as the starting point of inertial navigation.

[0107] Preferably, step S16 includes the following steps:

[0108] Step S161: Use the GNSS navigation system to obtain the real-time rough position of the amphibious ship to obtain the rough position data of the amphibious ship;

[0109] Step S162: Take the rough position data of the amphibious ship as the calibrated positioning position, and calculate the inertial moving position of the ship according to the real-time ship attitude angle data and the preliminary ship linear velocity data to generate the ship inertial moving node data;

[0110] Step S163: Perform navigation coordinate conversion on the ship inertial moving node data, and draw the ship moving curve according to the rough position data of the amphibious ship to obtain the ship inertial drift curve data;

[0111] Step S164: Based on the real-time ship attitude angle data and the preliminary ship linear velocity data, identify the stationary state of the ship for the ship inertial drift curve data to obtain the ship stationary state data;

[0112] Step S165: Make a zero-speed judgment according to the ship stationary state data, and mark the node zero-speed correction for the ship inertial drift curve data to obtain the node zero-speed correction flag;

[0113] Step S166: Set the speed of the ship inertial drift curve data to zero through the node zero-speed correction flag, and perform zero-speed position error correction to generate the inertial position data of the amphibious ship.

[0114] In the embodiments of the present invention, a GNSS (Global Navigation Satellite System, such as GPS, Beidou, GLONASS or Galileo) receiver is used to obtain the initial position and rough position information of the amphibious ship. A GNSS antenna is installed on the amphibious ship, and the antenna position should be as open as possible to avoid occlusion to ensure receiving a sufficient number of satellite signals (at least 4). The GNSS antenna is connected to the GNSS receiver. The GNSS receiver measures the propagation time of the signal by receiving satellite signals and calculates the distance between the ship and the satellite using the principle of trilateration. Through the distance information of at least four satellites, the three-dimensional position (longitude, latitude and altitude) and time information of the ship can be solved. The GNSS receiver outputs the rough position data of the amphibious ship at a set frequency (such as 1 Hz or 5 Hz). The format of the data usually follows the NMEA 0183 standard or the binary format defined by the receiver manufacturer. The data is transmitted to the data processing unit through a serial port (such as RS232) or a network interface (such as UDP). After receiving the data, the data processing unit parses it according to the data format and extracts the longitude, latitude and altitude information. Combining the GNSS rough position, attitude angle and preliminary linear velocity data, the inertial moving position is calculated. First, the GNSS rough position data is used as the initial position of inertial navigation. When the inertial navigation system is started, the first valid position data (longitude, latitude and altitude) output by the GNSS receiver is used as the starting position of inertial navigation. This position will be used as the reference point for subsequent inertial position calculation. Then, according to the real-time ship attitude angle data and preliminary ship linear velocity data obtained in step S15, the ship inertial moving position is calculated. The specific calculation method is as follows: According to the inertial position, attitude angle and linear velocity at the previous moment, the position increment at the current moment is calculated. The calculation of the position increment needs to consider the attitude change of the ship, convert the velocity in the body coordinate system to the navigation coordinate system, and then perform integration. For example, the following formula is used to calculate the position increment:

[0115] where ΔE, ΔN and ΔU represent the position increments in the eastward, northward and upward directions respectively; Vt is the preliminary linear velocity; φ, θ and ψ are the roll angle, pitch angle and heading angle respectively; and Δt is the sampling time interval. The calculated position increment is accumulated to the inertial position at the previous moment to obtain the ship inertial moving node data at the current moment. The ship inertial moving node data is usually represented in a relative coordinate system (for example, with the position at the start-up moment as the origin). In order to compare and fuse it with other navigation data (such as GNSS data), it needs to be converted to a unified navigation coordinate system, such as the WGS-84 geodetic coordinate system (longitude, latitude and altitude). This can be achieved through coordinate translation and rotation transformation. The translation amount is determined by the initial GNSS position, and the rotation matrix is determined by the initial attitude angle. Then, according to the converted inertial moving node data, the ship moving curve is drawn.

[0116] Connect the inertial position points at each moment in a two-dimensional plane (e.g., longitude-latitude plane) or three-dimensional space to form a continuous curve. Using the attitude angle and linear velocity data, identify the stationary state of the ship. The stationary state of the ship refers to the state where the ship remains stationary or moves at an extremely low speed for a period of time. In the stationary state, the speed error and position error of the inertial navigation system will decrease significantly. Therefore, accurately identifying the stationary state is crucial for subsequent zero-speed correction. The specific identification method is as follows: Set a time window (e.g., 10 seconds), a speed threshold (e.g., 0.1 m / s), and an attitude angle change rate threshold (e.g., 0.5 degrees / second). If within this time window, the absolute value of the preliminary ship linear velocity is always less than the speed threshold, and the absolute value of the change rate of the three attitude angles (roll, pitch, heading) is always less than the attitude angle change rate threshold, then it is considered that the ship is in a stationary state. Once it is detected that the ship enters the stationary state, ship stationary state data is generated, which includes the start time and end time of the stationary state. Perform zero-speed judgment and correction marking based on the stationary state data. First, perform zero-speed judgment. According to the ship stationary state data obtained in step S164, judge whether the ship is in a zero-speed state. If the ship is in a stationary state and the speed data output by the GNSS receiver is also close to zero (e.g., less than 0.05 m / s), then it is considered that the ship is in a zero-speed state. Then, perform node zero-speed correction marking on the ship inertial drift curve data. On the ship inertial drift curve, find the node corresponding to the start time of the zero-speed state and mark this node to generate a node zero-speed correction flag. Use the zero-speed correction flag to perform speed zeroing and position error correction. First, perform speed zeroing. On the ship inertial drift curve, find the node with the node zero-speed correction flag. Force the speed calculated by the inertial navigation system corresponding to this node to be zero. This can eliminate the speed drift error of the inertial navigation system in the stationary state. Then, perform zero-speed position error correction. Since the integration of the speed error will cause a position error, after performing speed zeroing, it is also necessary to correct the position error. A simple method is: Compare the inertial position corresponding to the zero-speed correction flag with the GNSS rough position, calculate the position error. Distribute this position error evenly within the entire zero-speed interval and correct the inertial position at each moment. A more complex method is: Use the Kalman filter, take zero speed as the observation information, and estimate and correct the state (position, speed, attitude, and sensor error) of the inertial navigation system. After speed zeroing and position error correction, the final inertial position data of the amphibious ship is obtained.

[0117] Preferably, step S2 includes the following steps:

[0118] Step S21: Use a Doppler log to monitor the real-time navigation speed and obtain the initial navigation speed of the amphibious ship.

[0119] Step S22: Obtain the data on the type of the navigation environment of the amphibious ship.

[0120] Step S23: Select the Doppler log speed measurement mode according to the data on the type of the navigation environment of the amphibious ship to obtain the Doppler log speed measurement mode.

[0121] Step S24: Perform Doppler effect compensation on the initial navigation speed of the amphibious ship through the Doppler log speed measurement mode to obtain the ship Doppler compensation speed data.

[0122] As an example of the present invention, refer to Figure 3 shown in Figure 1 which is a schematic diagram of the detailed implementation steps of step S2 in

[0123] Step S21: Use a Doppler log to monitor the real-time navigation speed and obtain the initial navigation speed of the amphibious ship.

[0124] In the embodiment of the present invention, the transducer of the Doppler log is installed at the bottom of the amphibious ship. The installation position of the transducer should be as far away as possible from the propeller and the protrusions on the hull surface to reduce the interference of bubbles and turbulence. The transducer usually includes multiple acoustic array elements (for example, four), which are respectively directed in different directions (for example, at an angle of 30 degrees or 45 degrees with the longitudinal axis of the hull). The transducer is connected to the main unit of the Doppler log through a cable. Then, the Doppler log is started. The main unit of the Doppler log controls the transducer to periodically emit acoustic wave pulses. The frequency of the acoustic wave pulses depends on different models of Doppler logs and application scenarios, and is usually between dozens of kHz and several MHz. For example, for shallow water applications, acoustic waves of 600 kHz or 1200 kHz can be used; for deep water applications, acoustic waves of 75 kHz or 150 kHz can be used. The transducer simultaneously receives the echo signals reflected by the bottom of the water or the suspended matter in the water. The main unit of the Doppler log processes the received echo signals and calculates the speed of the ship relative to the bottom of the water (bottom tracking mode) or the water layer (water tracking mode) using the Doppler effect. The Doppler effect means that when there is relative motion between the sound source (transducer) and the reflector (bottom of the water or suspended matter), the frequency of the received echo signal will change. The magnitude of the frequency change is proportional to the relative speed. The Doppler log calculates the speed components of the ship in each direction by measuring the frequency change of the echo signal. The Doppler log outputs the initial navigation speed data of the amphibious ship at a set frequency (for example, 1 Hz or 10 Hz), including the longitudinal speed, the lateral speed, and the vertical speed.

[0125] Step S22: Obtain the data on the type of the navigation environment of the amphibious ship.

[0126] In an embodiment of the present invention, the current position (longitude and latitude) of the ship is obtained through a GNSS receiver, and then the pre-loaded chart database is queried to determine the sea area type to which the position belongs. For example, the sea area type can be divided into "inland river", "offshore shallow water area", "deep sea area", "port area", etc. Another way is to measure the current water depth through an on-board sensor (such as a depth sounder) and judge the sea area type according to the water depth range. For example, an area with a water depth less than 50 meters can be divided into an "offshore shallow water area", and an area with a water depth greater than 2000 meters can be divided into a "deep sea area". The navigation environment type data can also be obtained by manual input. For example, the driver can manually select the corresponding environment type according to the current navigation sea area and sea conditions. The obtained navigation environment type data is transmitted to the data processing unit in a coded form (for example, using the number 1 to represent "inland river", using the number 2 to represent "offshore shallow water area", etc.).

[0127] Step S23: Select a Doppler log speed measurement mode according to the navigation environment type data of the amphibious ship to obtain a Doppler log speed measurement mode;

[0128] In an embodiment of the present invention, a suitable Doppler log speed measurement mode is selected. Different navigation environments have different effects on the speed measurement performance of the Doppler log. For example, in a shallow water area, the sound wave is easy to reach the bottom and reflect, and the bottom tracking mode can be selected; in a deep water area, the sound wave is difficult to reach the bottom, or the reflected signal is very weak, and the water tracking mode can be selected. In an area with strong water flow, the influence of the water flow on the speed measurement needs to be considered, and a suitable compensation algorithm is selected. The specific selection method is: establish a mapping table between the navigation environment type and the Doppler speed measurement mode. This mapping table is formulated in advance according to the Doppler speed measurement characteristics in different environments. According to the navigation environment type data obtained in step S22, query this mapping table and select the corresponding Doppler speed measurement mode, sound wave frequency and other parameters (such as pulse length, transmission power, etc.). The data processing unit sends the selected speed measurement mode and parameters to the host of the Doppler log.

[0129] Step S24: Perform Doppler effect compensation on the initial navigation speed of the amphibious ship through the Doppler log speed measurement mode to obtain ship Doppler compensation speed data.

[0130] In the embodiments of the present invention, Doppler effect compensation is performed on the initial navigation speed to obtain the final speed data. The speed measured by a Doppler log is the speed relative to the acoustic reflector, rather than the absolute speed relative to the ground. In the bottom tracking mode, the reflector is the seabed, and the speed measured is the speed relative to the bottom; in the water tracking mode, the reflector is the suspended matter in the water, and the speed measured is the speed relative to different water layers. For example, in the bottom tracking mode, mainly the sound speed error needs to be compensated. The sound speed in water changes with temperature, salinity, and pressure. Doppler logs are usually equipped with temperature sensors that can measure the water temperature. According to empirical formulas or by looking up tables, the sound speed at the current water temperature can be calculated. Using the calculated sound speed, the Doppler speed measurement result is corrected. In the water tracking mode, in addition to the sound speed error, the influence of water flow also needs to be considered. The Doppler log can measure the speeds of multiple water layers to form a water flow profile. According to the water flow profile, the average flow velocity of the entire water column can be estimated, and this average flow velocity is deducted from the Doppler speed measurement result to obtain the speed relative to the seabed. If the heading of the ship is known, the water flow velocity can also be decomposed into the longitudinal and lateral directions of the ship and compensated separately. After Doppler effect compensation, the ship's Doppler compensation speed data, including the ground speeds in the longitudinal, lateral, and vertical directions, is obtained.

[0131] Preferably, step S3 includes the following steps:

[0132] Step S31: Use an amphibious ship to receive radio positioning signals to obtain radio frequency signals;

[0133] Step S32: Perform radio positioning processing based on the radio frequency signals to generate amphibious ship radio positioning data;

[0134] Step S33: Perform spatio-temporal reference alignment processing on the amphibious ship inertial position data, the ship Doppler compensation speed data, and the amphibious ship radio positioning data to generate spatio-temporally synchronized positioning and monitoring data;

[0135] Step S34: Establish an inertial navigation error model based on the amphibious ship inertial position data in the spatio-temporally synchronized positioning and monitoring data;

[0136] Step S35: Use the ship Doppler compensation speed data in the spatio-temporally synchronized positioning and monitoring data to calculate the speed vector difference of the inertial navigation error model and perform navigation axis coordinate projection to generate inertial navigation speed data;

[0137] Step S36: Establish position constraint conditions based on the amphibious ship radio positioning data in the spatio-temporally synchronized positioning and monitoring data, and use the inertial navigation speed data to perform dynamic correction of navigation parameters to obtain intelligent ship position positioning data.

[0138] In an embodiment of the present invention, a radio receiving antenna is installed on an amphibious ship. The type and installation location of the antenna are determined according to the radio positioning system used. For example, if a very high frequency (VHF) radio positioning system is used, a whip antenna or a loop antenna can be used and installed at a higher position on the hull to obtain better reception. If a Loran-C system is used, a long wire antenna can be used. If a satellite positioning system (such as Beidou short message) is used, a helical antenna or a planar antenna can be used. The antenna is connected to a radio receiver through a feeder. The radio receiver receives radio signals from radio positioning sources (such as shore-based base stations, navigation satellites, or differential GPS base stations) according to pre-set frequencies and modulation methods. The received radio signals usually contain ranging information for positioning (such as time of arrival of the signal, time difference of arrival, or pseudorange) or angle measurement information (such as angle of arrival of the signal). The radio receiver amplifies, filters, demodulates, and digitizes the received signals to generate radio frequency signals. The signals are output in digital form and transmitted to a data processing unit, for example, through a serial port (RS232 or RS422) or a network interface (UDP or TCP). By measuring the propagation time or phase difference of the signals, the distance between the ship and the base station is calculated. Then, using this distance information and the known position of the base station, the three-dimensional position coordinates (longitude, latitude, and altitude) of the amphibious ship are calculated through a three-dimensional space positioning algorithm (such as the least squares method). The calculated position coordinates and timestamp information are recorded to generate amphibious ship radio positioning data. The navigation computer receives the inertial position data of the amphibious ship, the ship Doppler compensation speed data, and the amphibious ship radio positioning data. The three types of data have different sampling frequencies. For example, the inertial position data is 100 Hz, the Doppler speed data is 10 Hz, and the radio positioning data is 1 Hz. A time interpolation method, such as linear interpolation, is used to unify the three types of data to the same sampling frequency, such as 10 Hz. Then, using the Precision Time Protocol (PTP) or other time synchronization methods, the timestamps of the three types of data are aligned to ensure that the data is processed under the same time reference. The three types of time-synchronized data are integrated together to generate spatio-temporal synchronized positioning and monitoring data. According to the inertial position data in the spatio-temporal synchronized positioning and monitoring data, an inertial navigation error model is established. The inertial navigation errors mainly include sensor errors (zero bias, scale factor errors, and random noise of gyroscopes and accelerometers) and initial alignment errors (initial attitude errors and initial position errors). The error model describes the variation law of these errors over time. A commonly used inertial navigation error model is a state-space-based model, which takes the error terms as state variables and establishes state equations and observation equations. For example, the following state equation can be used: ; where, δX is the state vector, including position error, velocity error, attitude error, gyroscope bias, accelerometer bias, etc.; F is the state transition matrix, describing the variation relationship of the error over time; G is the noise drive matrix, and W is the process noise vector. The state transition matrix F is determined according to the propagation law of inertial navigation error, and the process noise W is usually assumed to be Gaussian white noise. Compare the Doppler compensated velocity data (in the navigation coordinate system) in the spatio-temporal synchronous positioning and monitoring data with the velocity data calculated by the inertial navigation system (in the navigation coordinate system), and calculate the velocity differences in three directions (east, north, and up). These velocity differences reflect the velocity error of the inertial navigation system. Then, perform navigation axis coordinate projection. Project the calculated velocity differences onto the three axes of the navigation coordinate system. This can be achieved through simple coordinate transformation. For example, if the velocity difference is ΔV, the eastward velocity error is the eastward component of ΔV, the northward velocity error is the northward component of ΔV, and the upward velocity error is the upward component of ΔV. After calculating the velocity vector difference and performing navigation axis coordinate projection, the inertial navigation velocity data is obtained, which contains the velocity error information of the inertial navigation system in three directions. Use the amphibious ship radio positioning data (longitude, latitude, and altitude) in the spatio-temporal synchronous positioning and monitoring data as the position constraint. Since the radio positioning system (such as GPS) provides absolute position information, it can be used as the true value or reference value to constrain the position error of the inertial navigation system. Then, use the inertial navigation velocity data and the position constraint conditions to dynamically correct the navigation parameters. The Kalman filter algorithm is used for data fusion. Take the inertial navigation error model established in step S34 as the state equation of the Kalman filter, and take the inertial navigation velocity data obtained in step S35 and the position constraint conditions established in this step as the observation equation of the Kalman filter. The Kalman filter estimates the state vector of the inertial navigation system (including position error, velocity error, attitude error, gyroscope bias, accelerometer bias, etc.) according to the state equation and the observation equation, and the corrected output is the intelligent ship position positioning data.

[0139] Preferably, step S32 includes the following steps:

[0140] Step S321: Enhance the signal-to-noise ratio of the radio frequency signal and perform satellite signal acquisition to obtain acquisition result data; the satellite signal acquisition searches for the pseudo-code phase and carrier frequency of the radio frequency signal and determines whether there is a valid positioning signal;

[0141] Step S322: When there is a valid signal in the acquisition result data, track the satellite signal to obtain tracking loop signal data;

[0142] Step S323: Demodulate the pseudo-code based on the tracking loop signal data to obtain pseudo-range data;

[0143] Step S324: Perform carrier phase smoothing on the pseudorange data to obtain smoothed pseudorange data;

[0144] Step S325: Suppress the multipath error of the smoothed pseudorange data through the amphibious ship navigation environment type data to obtain multipath-suppressed pseudorange data;

[0145] Step S326: Use the multipath-suppressed pseudorange data to perform position calculation on the amphibious ship and generate amphibious ship radio positioning data.

[0146] In an embodiment of the present invention, the received radio frequency signal is enhanced in signal-to-noise ratio. For example, narrowband filtering technology is used to filter out out-of-band noise and improve the signal-to-noise ratio of the signal. A capture algorithm is used to capture satellite signals from the enhanced signal. Specifically, a two-dimensional search is performed on the pseudo-code phase and carrier frequency of the radio frequency signal and compared with known satellite pseudo-codes and carrier frequencies to determine whether there is a valid positioning signal. The search range is set to a pseudo-code phase of 0 - 1023 chips, a carrier frequency of -5 kHz to +5 kHz, and a step size of 100 Hz. The search results, including information such as satellite PRN code, pseudo-code phase, carrier frequency, and signal-to-noise ratio, are recorded as capture result data. If the detected pseudo-code and carrier frequency match those corresponding to a certain satellite, it is considered that the satellite signal has been successfully captured. If there is a valid signal in the capture result data, that is, at least one satellite signal has been captured, a tracking loop is started to track the captured satellite signal. The tracking loop includes a pseudo-code tracking loop and a carrier tracking loop. The pseudo-code tracking loop adjusts the phase of the local pseudo-code to keep it synchronized with the pseudo-code phase of the received satellite signal; the carrier tracking loop adjusts the frequency of the local carrier to keep it synchronized with the carrier frequency of the received satellite signal. The signal data output by the tracking loop, including information such as pseudo-code phase, carrier phase, and signal-to-noise ratio, are recorded as tracking loop signal data. Using the code phase information output by the code tracking loop in step S322, the local pseudo-code generator is controlled to generate a pseudo-code synchronized with the received signal. The received signal is correlated with the locally generated pseudo-code to remove the pseudo-code modulation in the signal. Then, by measuring the delay time of the bit transition edge of the received signal relative to the local clock, the propagation time of the signal can be calculated. Multiplying the propagation time by the speed of light gives the pseudo-range data. The pseudo-range data includes the geometric distance from the satellite to the receiver, satellite clock error, receiver clock error, ionospheric delay, tropospheric delay, and multipath error, etc. Using the carrier phase information output by the carrier tracking loop in step S322, the change in carrier phase between adjacent epochs is calculated. The carrier phase measurement value is much more accurate than the pseudo-range measurement value. The change in carrier phase is converted into a change in distance (multiplied by the carrier wavelength). The change in pseudo-range is corrected using the change in carrier phase. For example, a Hatch filter can be used to smooth the pseudo-range. The Hatch filter is a recursive filter that calculates the smoothed pseudo-range data at the current moment using the pseudo-range measurement value and the change in carrier phase at the current moment, as well as the smoothed pseudo-range value at the previous moment. According to the data on the type of the navigation environment of the amphibious ship, multipath error suppression is performed on the smoothed pseudo-range data. Multipath error refers to the error caused by the signal arriving at the receiver through multiple paths. In a water surface or tidal flat environment, the multipath error is relatively serious. Multipath suppression techniques, such as narrow correlation technology or Multipath Estimation Delay Locked Loop (MEDLL) technology, are used to correct the smoothed pseudo-range data and reduce the influence of multipath error.Record the corrected pseudorange data as multipath suppression pseudorange data. Use the multipath suppression pseudorange data to perform position solution for the amphibious ship. Specifically, input the multipath suppression pseudorange data, satellite position information, and receiver clock error information into a positioning solution algorithm, such as the least squares method or the Kalman filter algorithm. Calculate the three-dimensional position coordinates (longitude, latitude, and altitude) of the amphibious ship by solving the positioning equation. Record the calculated position coordinates and timestamp information to generate the radio positioning data of the amphibious ship.

[0147] Preferably, step S325 includes the following steps:

[0148] Query the multipath effect occurrence probability according to the amphibious ship navigation environment type data to obtain the multipath occurrence probability data;

[0149] Perform multipath effect analysis based on the multipath occurrence probability data and establish a multipath signal model using the smoothed pseudorange data to obtain the multipath signal model;

[0150] Identify multipath signals for the radio frequency signal through the multipath signal model and estimate the multipath signal error using the antenna array fixedly installed on the amphibious ship to obtain the multipath signal error data;

[0151] Compensate the multipath error for the smoothed pseudorange data using the multipath signal error data to obtain the compensated pseudorange data;

[0152] Perform narrowband filtering suppression on the compensated pseudorange data to generate the ship's multipath suppression pseudorange data.

[0153] In an embodiment of the present invention, the navigation computer stores a pre-established multipath effect occurrence probability database. This database is established based on a large amount of experimental data and statistical analysis, associating different types of navigation environments (water surface, tidal flat, land) with the multipath effect occurrence probability. For example, in a water surface navigation environment, due to the influence of water surface reflection, the multipath effect occurrence probability is relatively high, set to 0.8; in a tidal flat navigation environment, due to the complexity of the tidal flat terrain, the multipath effect occurrence probability is set to 0.6; in a land navigation environment, the multipath effect occurrence probability is relatively low, set to 0.2. The navigation computer queries the corresponding multipath effect occurrence probability from the database according to the amphibious ship navigation environment type data obtained in step S22 to obtain the multipath occurrence probability data. When the multipath occurrence probability data is greater than a preset threshold (e.g., 0.5), it is considered that the multipath effect is significant and multipath signal modeling is required. Using the smoothed pseudorange data and the known satellite position information, a multipath signal model is established. Specifically, it is assumed that the multipath signal consists of a direct signal and several reflected signals, and the amplitude, phase, and delay of each reflected signal are unknown. A multipath signal parameter estimation method, such as the MUSIC algorithm or the ESPRIT algorithm, is used to estimate the various parameters of the multipath signal and establish a multipath signal model. In this example, a two-path model is adopted. The received signal y(t) can be expressed as: ; where s(t) is the direct signal, α is the ratio of the amplitude of the multipath signal to the amplitude of the direct signal (0 < α < 1), τ is the delay of the multipath signal relative to the direct signal, and φ is the phase difference of the multipath signal relative to the direct signal. This model describes the composition and characteristics of the multipath signal, such as the number of reflected signals, the amplitude, phase, and delay of each reflected signal, etc. An antenna array is fixedly installed on the amphibious ship. For example, a uniform circular array composed of 4 antenna elements. The received radio frequency signal is identified for multipath signals using the multipath signal model. Specifically, the received signal is matched with the multipath signal model to identify the direct signal and each reflected signal. Using the spatial characteristics of the antenna array, the multipath signal error is estimated. Specifically, beamforming technology or spatial smoothing technology is adopted to process the signals received by each antenna element to estimate the pseudorange error caused by the multipath signal. The estimated pseudorange error is recorded as multipath signal error data. The multipath signal error data is subtracted from the smoothed pseudorange data to obtain compensated pseudorange data. The purpose of multipath error compensation is to eliminate the influence of the multipath effect on pseudorange measurement and improve the accuracy of pseudorange measurement. Narrowband filtering suppression is performed on the compensated pseudorange data to further reduce the influence of multipath error and noise. Specifically, a narrowband filter, such as a Butterworth filter, is used to filter the compensated pseudorange data, and the bandwidth of the filter is adjusted according to the characteristics of the signal and the noise level. The filtered pseudorange data is used as the final ship multipath suppression pseudorange data.

[0154] Preferably, step S4 includes the following steps:

[0155] Step S41: Perform geographic coordinate conversion on the intelligent ship position positioning data to obtain geographic coordinate data;

[0156] Step S42: Process the navigation coordinates according to the geographic coordinate data and perform navigation map matching through the preset electronic chart data to obtain matched navigation data;

[0157] Step S43: Display the matched navigation data on the navigation display terminal to obtain the navigation display information of the amphibious ship.

[0158] In the embodiments of the present invention, the intelligent ship position positioning data is converted from a computational coordinate system (for example, longitude and latitude in the WGS-84 coordinate system) to a geographic coordinate system. The intelligent ship position positioning data is usually represented in the form of longitude and latitude (and altitude), which is a spherical coordinate and is not convenient for direct display on a plane map or for distance and azimuth calculations. It is necessary to convert it into a plane rectangular coordinate system, such as the Universal Transverse Mercator (UTM) coordinate system or the Gauss-Krüger projection coordinate system. The specific conversion method is as follows: According to the selected map projection type (such as UTM or Gauss-Krüger), select the corresponding projection parameters (such as the central meridian, scale factor, etc.). Then, use the projection formula to convert the longitude and latitude coordinates into plane rectangular coordinates (such as the eastward coordinate and northward coordinate of the UTM coordinate system). Match the geographic coordinate data with the electronic chart data and display the ship position on the electronic chart. First, perform navigation coordinate processing. According to the geographic coordinate data (plane rectangular coordinates), calculate the heading and speed of the ship. The heading can be obtained by calculating the azimuth angle between two adjacent position points, and the speed can be obtained by calculating the distance between two adjacent position points divided by the time interval. Then, perform navigation map matching. Overlay the geographic coordinate data and the electronic chart data. The electronic chart data is usually stored in a vector format and contains the geometric information and attribute information of various elements on the chart (such as shorelines, waterways, lighthouses, depth points, etc.). Use a point-to-line or point-to-plane matching algorithm to project the ship position point onto the nearest waterway line or shoreline on the electronic chart. To avoid incorrect matching, it is necessary to consider the ship's heading, speed, and historical trajectory information. For example, a search radius can be set to find the matching line or plane only within the search radius. It is also possible to predict the next moment position of the ship based on the ship's heading and speed and preferentially match the line or plane close to the predicted position. After successful matching, draw the ship position symbol (such as a triangle or a ship-shaped icon) at the corresponding position on the electronic chart to generate the matching navigation data. Display the matching navigation data on the navigation display terminal. The navigation display terminal can be a liquid crystal display screen, an Electronic Chart Display and Information System (ECDIS), or an augmented reality navigation system. On the navigation display terminal, display the electronic chart and superimpose the real-time position, heading, speed, etc. of the amphibious ship on the map in a graphical manner. For example, use an icon to represent the current position of the amphibious ship, the direction of the icon represents the ship's heading, and the color of the icon represents the ship's navigation status (for example, green represents normal navigation, and red represents a dangerous state). At the same time, display other navigation information on the screen, such as the distance to the target point, the estimated arrival time, the route plan, etc.

[0159] Preferably, the present invention also provides an intelligent amphibious ship navigation and positioning system that executes the intelligent amphibious ship navigation and positioning method as described above. The intelligent amphibious ship navigation and positioning system includes:

[0160] A ship inertial measurement module, which is used to perform real-time ship inertial measurement on an amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation according to the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data;

[0161] A Doppler log compensation module, which is used to obtain the data of the navigation environment type of the amphibious ship; perform Doppler effect navigation speed compensation on the amphibious ship by using a Doppler log based on the data of the navigation environment type of the amphibious ship to generate ship Doppler compensation speed data;

[0162] A space-time navigation positioning correction module, which is used to perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform space-time reference alignment processing according to the amphibious ship inertial position data, the ship Doppler compensation speed data and the amphibious ship radio positioning data to generate space-time synchronous positioning monitoring data; perform dynamic correction of navigation parameters based on the space-time synchronous positioning monitoring data to obtain intelligent ship position positioning data;

[0163] An intelligent navigation display module, which is used to perform navigation map matching on the intelligent ship position positioning data and perform display on a navigation display terminal to obtain amphibious ship navigation display information.

[0164] Preferably, the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed, the intelligent amphibious ship navigation positioning method described in any one of the above is implemented.

[0165] This application aims to obtain accurate ship attitude angle data through real-time ship inertial measurement and attitude mode annotation, and conduct inertial position analysis based on this data to obtain the inertial position data of the amphibious ship. Compared with the traditional method that solely relies on GNSS, by taking advantage of the strong autonomy and immunity to external environmental interference of the inertial navigation system (INS), it effectively compensates for the defect of the GNSS in terms of accuracy degradation under signal occlusion or interference. Especially in areas where GNSS signals are vulnerable to influence, such as near the shore, in ports, inland rivers, and land environments, it can provide more reliable position information to ensure the continuous navigation ability of the amphibious ship in various complex environments. According to the data of different types of navigation environments, due to the huge differences in characteristics such as resistance and friction between water and land environments, the ship's speed changes drastically during the water-land conversion process. Traditional navigation methods based on constant speed or simple speed models are difficult to accurately estimate the ship's real-time speed, resulting in positioning errors. However, through Doppler effect navigation speed compensation, this application can correct the ship's speed in real time, improving the accuracy of navigation positioning. Especially in the dynamic environment of water-land conversion, it effectively solves the problem of inaccurate speed estimation by traditional methods and ensures the accuracy of navigation information. By fusing multi-source navigation information, dynamically correcting navigation parameters, and matching with electronic maps, it effectively solves the problems of low positioning accuracy and large latency of traditional navigation methods in amphibious environments, realizing high-precision, high-reliability, and high-real-time navigation positioning for amphibious ships. Specifically, through the multi-source data fusion of the inertial navigation system, GNSS, Doppler log, and radio positioning system, it can provide continuous and stable navigation services in different environments, significantly enhancing the navigation safety and operation efficiency of amphibious ships.

[0166] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Thus, it is intended to encompass all changes within the meaning and scope of the equivalent elements of the application document in the present invention.

[0167] The above are only the specific implementation manners of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. An intelligent amphibious ship navigation and positioning method, characterized in that, Including the following steps: Step S1: Conduct real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation based on the original ship inertial measurement data to obtain real-time ship attitude angle data; conduct amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data; specifically, step S1 is as follows: Step S11: Fix and install an inertial measurement unit on the hull of the amphibious ship, and start the inertial measurement unit to conduct real-time ship inertial measurement to generate original ship inertial measurement data; Step S12: Perform data preprocessing on the original ship inertial measurement data to obtain preprocessed ship inertial measurement data; Step S13: Extract the angular velocity according to the preprocessed ship inertial measurement data to generate the ship angular velocity; Step S14: Perform time integration according to the ship angular velocity, and conduct real-time ship attitude mode annotation through a preset ship attitude mode library to obtain real-time ship attitude angle data; Step S15: Calculate the attitude angle increment based on the real-time ship attitude angle data, and perform linear velocity integration to generate preliminary ship linear velocity data; Step S16: Conduct amphibious ship inertial position analysis according to the real-time ship attitude angle data and the preliminary ship linear velocity data to obtain amphibious ship inertial position data; specifically, step S16 is as follows: Step S161: Use the GNSS navigation system to obtain the real-time rough position of the amphibious ship to obtain the amphibious ship rough position data; Step S162: Take the amphibious ship rough position data as the calibrated positioning position, and calculate the ship inertial movement position according to the real-time ship attitude angle data and the preliminary ship linear velocity data to generate ship inertial movement node data; Step S163: Perform navigation coordinate conversion on the ship inertial movement node data, and draw the ship movement curve according to the amphibious ship rough position data to obtain the ship inertial drift curve data; Step S164: Identify the ship stationary state based on the real-time ship attitude angle data and the preliminary ship linear velocity data for the ship inertial drift curve data to obtain the ship stationary state data; Step S165: Conduct zero-speed judgment according to the ship stationary state data, and perform node zero-speed correction marking on the ship inertial drift curve data to obtain the node zero-speed correction flag; Step S166: Set the speed of the ship inertial drift curve data to zero through the node zero-speed correction flag, and perform zero-speed position error correction to generate the amphibious ship inertial position data; Step S2: Obtain the amphibious ship navigation environment type data; use the Doppler log to perform Doppler effect navigation speed compensation on the amphibious ship based on the amphibious ship navigation environment type data to generate ship Doppler compensation speed data; Step S3: Perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform spatio-temporal reference alignment processing based on the amphibious ship inertial position data, ship Doppler compensated speed data, and amphibious ship radio positioning data to generate spatio-temporal synchronous positioning and monitoring data; perform dynamic correction of navigation parameters based on the spatio-temporal synchronous positioning and monitoring data to obtain intelligent ship position positioning data; specifically, Step S3 is as follows: Step S31: Use the amphibious ship to receive radio positioning signals to obtain radio frequency signals; Step S32: Perform radio positioning processing based on the radio frequency signals to generate amphibious ship radio positioning data; Step S33: Perform spatio-temporal reference alignment processing on the amphibious ship inertial position data, ship Doppler compensated speed data, and amphibious ship radio positioning data to generate spatio-temporal synchronous positioning and monitoring data; Step S34: Establish an inertial navigation error model based on the amphibious ship inertial position data in the spatio-temporal synchronous positioning and monitoring data; Step S35: Use the ship Doppler compensated speed data in the spatio-temporal synchronous positioning and monitoring data to calculate the speed vector difference of the inertial navigation error model, and perform navigation axial coordinate projection to generate inertial navigation speed data; Step S36: Establish position constraint conditions based on the amphibious ship radio positioning data in the spatio-temporal synchronous positioning and monitoring data, and perform dynamic correction of navigation parameters using the inertial navigation speed data to obtain intelligent ship position positioning data; Step S4: Perform navigation map matching on the intelligent ship position positioning data and display it on the navigation display terminal to obtain amphibious ship navigation display information.

2. The intelligent amphibious ship navigation and positioning method according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Use a Doppler log to monitor the real-time navigation speed to obtain the initial amphibious ship navigation speed; Step S22: Obtain the amphibious ship navigation environment type data; Step S23: Select the Doppler log speed measurement mode according to the amphibious ship navigation environment type data to obtain the Doppler log speed measurement mode; Step S24: Perform Doppler effect compensation on the initial amphibious ship navigation speed through the Doppler log speed measurement mode to obtain ship Doppler compensated speed data.

3. The intelligent amphibious ship navigation and positioning method according to claim 1, wherein Step S32 includes the following steps: Step S321: Enhance the signal-to-noise ratio of the radio frequency signals and perform satellite signal acquisition to obtain acquisition result data; the satellite signal acquisition searches for the pseudo-code phase and carrier frequency of the radio frequency signals and determines whether there is an effective positioning signal; Step S322: When there is an effective signal in the acquisition result data, track the satellite signal to obtain tracking loop signal data; Step S323: Perform pseudo-code demodulation based on the tracking loop signal data to obtain pseudo-range data; Step S324: Smooth the pseudo-range data by carrier phase to obtain smoothed pseudo-range data; Step S325: Suppress the multipath error of the smoothed pseudo-range data through the amphibious ship navigation environment type data to obtain multipath suppressed pseudo-range data; Step S326: Use the multipath suppressed pseudo-range data to perform position calculation on the amphibious ship to generate amphibious ship radio positioning data.

4. The intelligent amphibious ship navigation and positioning method according to claim 1, characterized in that, Step S325 includes the following steps: Query the occurrence probability of multipath effect according to the data of the navigation environment type of the amphibious ship to obtain the multipath occurrence probability data; Conduct multipath effect analysis based on the multipath occurrence probability data, and establish a multipath signal model using smoothed pseudorange data to obtain the multipath signal model; Identify multipath signals for radio frequency signals through the multipath signal model, and estimate the multipath signal error using the antenna array fixedly installed on the amphibious ship to obtain the multipath signal error data; Perform multipath error compensation on the smoothed pseudorange data using the multipath signal error data to obtain the compensated pseudorange data; Perform narrowband filtering suppression on the compensated pseudorange data to generate the pseudorange data with multipath suppression for the ship.

5. The intelligent amphibious ship navigation and positioning method according to claim 1, wherein, Step S4 includes the following steps: Step S41: Perform geographic coordinate conversion on the intelligent ship position positioning data to obtain geographic coordinate data; Step S42: Process the navigation coordinates according to the geographic coordinate data, and perform navigation map matching through the preset electronic chart data to obtain the matched navigation data; Step S43: Display the matched navigation data on the navigation display terminal to obtain the navigation display information of the amphibious ship.

6. An intelligent amphibious ship navigation and positioning system, characterized in that, For implementing the intelligent amphibious ship navigation and positioning method as described in claim 1, the intelligent amphibious ship navigation and positioning system includes: A ship inertial measurement module, which is used to perform real-time ship inertial measurement on the amphibious ship to generate original ship inertial measurement data; perform real-time ship attitude mode annotation according to the original ship inertial measurement data to obtain real-time ship attitude angle data; perform amphibious ship inertial position analysis based on the real-time ship attitude angle data to obtain amphibious ship inertial position data; A Doppler log compensation module, which is used to obtain the data of the navigation environment type of the amphibious ship; perform Doppler effect navigation speed compensation on the amphibious ship using the Doppler log based on the data of the navigation environment type of the amphibious ship to generate the ship Doppler compensated speed data; A space-time navigation and positioning correction module, which is used to perform radio positioning processing on the amphibious ship to generate amphibious ship radio positioning data; perform space-time reference alignment processing according to the amphibious ship inertial position data, the ship Doppler compensated speed data, and the amphibious ship radio positioning data to generate space-time synchronous positioning monitoring data; perform dynamic correction of navigation parameters based on the space-time synchronous positioning monitoring data to obtain the intelligent ship position positioning data; An intelligent navigation display module, which is used to perform navigation map matching on the intelligent ship position positioning data and perform display on the navigation display terminal to obtain the navigation display information of the amphibious ship.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed, it implements the intelligent amphibious ship navigation and positioning method as described in any one of claims 1 to 5.

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