Real-time positioning system and positioning method of underwater glider and underwater glider

Abstract

The invention discloses a real-time positioning system and method of an underwater glider and the underwater glider, and belongs to the technical field of underwater detection equipment. The real-time positioning system comprises an acoustic positioning system, an inertial navigation unit, an electromagnetic ocean current meter and a control unit. The acoustic positioning system is composed of an ultra-short baseline range finder electronic cabin and an ultra-short baseline electroacoustic transducer and used for emitting acoustic signals and carrying out underwater position calculation through a tracking ship. The inertial navigation unit comprises a gyroscope, an accelerometer and a magnetometer; the electromagnetic ocean current meter is used for acquiring ocean current speed data; and the control unit is used for receiving and fusing data of the acoustic positioning system, the inertial navigation unit and the electromagnetic current meter, and optimizing real-time position estimation of the underwater glider through a fusion algorithm based on Kalman filtering. According to the system, the path and the track of the underwater glider for executing the observation task can be accurately obtained, and the ocean observation and detection accuracy is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater detection equipment, and particularly relates to a real-time positioning system, a positioning method and an autonomous underwater glider of an autonomous underwater glider. Background Art

[0002] As an important means of understanding the ocean, underwater mobile observation equipment is widely used in the observation of ocean resources and the identification of underwater targets. The autonomous underwater glider (AUG) has the advantages of strong mobility, high survival ability, no risk of casualties, low manufacturing and maintenance costs, etc., and is preferentially applied to long-term and large-scale observation tasks. AUG can be used to detect and track typical or sudden ocean events, and is suitable for the observation of "mesoscale" and "sub-mesoscale" ocean dynamic processes, and can provide high-resolution spatial and temporal observation data for research in the field of oceanography.

[0003] In order to complete the observation task, AUG needs to preset the task path, and knowing its accurate position information is an important part of completing the observation task. And accurate position information can provide more references for temperature, salinity and depth data. When AUG surfaces, it can use the Global Positioning System (GPS) to obtain the position. However, when underwater, it is difficult for the autonomous underwater glider to obtain accurate position information. For example, when operating under the ice in the polar region or in the anti-typhoon mode, the autonomous underwater glider needs to navigate underwater for a long time and cannot obtain accurate position information in time, which will affect the completion of the expected task objectives. Currently, the autonomous underwater glider mainly uses an electronic compass and a depth sensor to calculate the position during operation. However, since the position calculation error will increase with time accumulation, it is necessary to use the information of external sensors to correct these errors. However, the autonomous underwater glider has limitations in terms of the volume and energy consumption of the carried external sensors. Therefore, based on the carrying capacity of the autonomous underwater glider, how to improve the positioning accuracy of the autonomous underwater glider is a challenging problem. Summary of the Invention

[0004] Aiming at the problems that the existing autonomous underwater glider cannot obtain accurate position information during long-term underwater navigation, the position calculation error accumulates with time, and the external sensors are difficult to effectively correct the error due to volume and energy consumption limitations, the present invention provides a real-time positioning system, a positioning method and an autonomous underwater glider of an autonomous underwater glider.

[0005] The present invention is implemented as follows. A real-time positioning system for an underwater glider, characterized in that it comprises an acoustic positioning system, an inertial navigation unit, an electromagnetic current meter, and a control unit: The acoustic positioning system consists of an ultra-short baseline ranging instrument electronic cabin and an ultra-short baseline electro-acoustic transducer, and is used to transmit acoustic signals and perform underwater position calculation through a tracking ship; The inertial navigation unit includes a gyroscope, an accelerometer, and a magnetometer. The gyroscope is used to obtain the attitude angle data of the underwater glider; The accelerometer is used to obtain the specific force data of the fuselage; The magnetometer is used to detect the direction of the earth's magnetic field to provide heading angle reference data; The electromagnetic current meter is used to obtain ocean current speed data; The control unit is used to receive and fuse the data of the acoustic positioning system, the inertial navigation unit, and the electromagnetic current meter, and optimize the real-time position estimation of the underwater glider through a fusion algorithm based on Kalman filtering.

[0006] In the above technical solution, preferably, the ultra-short baseline electro-acoustic transducer is installed at the front end of the underwater glider and is used to directionally transmit acoustic signals; The ultra-short baseline ranging instrument electronic cabin is located on the central axis of the underwater glider and is connected to the ultra-short baseline electro-acoustic transducer. The ultra-short baseline ranging instrument electronic cabin is used to receive and process acoustic signals and calculate the relative distance between the underwater glider and the tracking ship.

[0007] In the above technical solution, preferably, the inertial navigation unit is installed on the central axis of the underwater glider with the Y-axis pointing in the forward direction and is connected to the control unit through a watertight cable.

[0008] In the above technical solution, preferably, the electromagnetic current meter is installed on the front-end central axis of the underwater glider and is connected to the control unit through a watertight cable.

[0009] The second object of the present invention is to propose a positioning method based on the above real-time positioning system for an underwater glider, characterized in that it includes the following steps:

[0010] S1. Data acquisition: Receive acoustic ranging data through the ultra-short baseline positioning system; Obtain the attitude angle, angular velocity, and acceleration data of the underwater glider in real time through the inertial navigation unit; Measure the current ocean current speed data through the electromagnetic current meter.

[0011] S2. Data fusion and optimization: Input the attitude angle, angular velocity, and acceleration data into the dynamics model to predict the motion state of the underwater glider; Based on the extended Kalman filter formula, perform attitude angle optimization, velocity optimization, and position optimization. During the attitude angle optimization, fuse the data from the gyroscope, accelerometer, and magnetometer, and compensate for the attitude angle error through complementary filtering; During the velocity optimization, introduce the ocean current velocity data into the dynamics model to correct the deviation between the accelerometer-integrated velocity and the model-simulated velocity; During the position optimization, use the ultra-short baseline ranging data as the observation value to filter and correct the position cumulative error of inertial navigation.

[0012] S3. Output the optimized real-time position, velocity, and attitude information.

[0013] In the above technical solution, preferably, the extended Kalman filter formula is:

[0014]

[0015] In the above technical solution, preferably, the parameters of the dynamics model are calibrated through the historical sea trial data of the underwater glider, and it includes compensating the ocean current velocity measured by the electromagnetic current meter to both the accelerometer-integrated velocity and the simulated velocity output by the dynamics model, and then fusing them through the Kalman filter.

[0016] In the above technical solution, preferably, it includes performing closed-loop feedback after step S2, and feeding back the optimized position error to the inertial navigation unit to suppress its error accumulation.

[0017] The third object of the present invention is to propose an underwater glider equipped with the above real-time positioning system.

[0018] Through the innovatively designed integrated navigation and positioning system and method, the present invention effectively solves the technical bottleneck in underwater positioning of traditional underwater gliders, and has the following advantages and effects:

[0019] By integrating an Inertial Navigation System (INS) with an Ultra-Short Baseline Acoustic Positioning System (USBL), and combining the real-time water flow velocity measurement of an electromagnetic current meter, a set of efficient multi-source data fusion frameworks is constructed. The inertial navigation unit uses gyroscopes, accelerometers, and magnetometers to obtain high-precision attitude angles, angular velocities, and specific force data in real time, providing autonomous and stable motion state prediction within a short time window; while the USBL system outputs absolute position reference values periodically through the collaborative communication of acoustic signals with the surface tracking vessel, significantly suppressing the long-term cumulative error of inertial navigation. The fusion algorithm based on Kalman filtering further optimizes the data processing flow. Through the progressive correction mechanism of attitude angles, velocities, and positions, it deeply integrates the dynamic response characteristics of gyroscopes, the instantaneous measurement accuracy of accelerometers, and the heading stability of magnetometers. At the same time, the dynamic correction of the ocean current velocity is introduced to correct the simulation output of the dynamic model, effectively offsetting the influence of environmental interference on the motion trajectory.

[0020] This system not only greatly improves the trajectory tracking ability of underwater gliders in long-time series and large-scale observation tasks, but also provides a high-precision position reference for the spatial correlation of temperature, salinity, and depth data. It is especially suitable for scenarios that are difficult to cover by traditional technologies such as sub-ice detection in polar regions and submersible navigation in typhoon patterns, promoting the refined leap of ocean dynamic process observation from "mesoscale" to "sub-mesoscale". Brief Description of the Drawings

[0021] Figure 1 It is the overall schematic diagram of an underwater glider for real-time underwater positioning of the present invention;

[0022] Figure 2 It is the connection diagram of the sensor hardware circuit of the present invention;

[0023] Figure 3 It is the flow chart of the integrated navigation algorithm of the present invention;

[0024] Figure 4 It is the block diagram of the optimized estimation of attitude angles of the present invention;

[0025] Figure 5 It is the block diagram of the optimized estimation of velocities of the present invention;

[0026] Figure 6 It is the block diagram of the optimized estimation of positions of the present invention. Detailed Description of the Invention

[0027] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0028] To solve the problems that existing underwater gliders cannot obtain accurate position information during long-term underwater navigation, the position calculation error accumulates over time, and external sensors are difficult to effectively correct errors due to volume and energy consumption limitations, the present invention particularly provides a real-time positioning system, a positioning method, and an underwater glider for an underwater glider. To further illustrate the structure of the present invention, the detailed description is as follows in conjunction with the accompanying drawings:

[0029] Embodiment 1

[0030] Please refer to Figure 1 , a real-time positioning system for an underwater glider, including an acoustic positioning system, an inertial navigation unit, an electromagnetic current meter 1, and a control unit.

[0031] The acoustic positioning system consists of an ultra-short baseline ranging instrument electronic cabin 2 and an ultra-short baseline electro-acoustic transducer 3, and is used to transmit acoustic signals and perform underwater position calculation through a tracking ship. The inertial navigation unit includes a gyroscope, an accelerometer, and a magnetometer. The gyroscope is used to output the angular velocity data of the underwater glider in real time. The accelerometer is used to obtain the body acceleration data; the magnetometer is used to detect the direction of the earth's magnetic field to provide heading angle reference data. The electromagnetic current meter is used to obtain the ocean current velocity data. The control unit is used to receive and fuse the data of the acoustic positioning system, the inertial navigation unit, and the electromagnetic current meter, and optimize the real-time position estimation of the underwater glider through a fusion algorithm based on Kalman filtering.

[0032] In this embodiment, specifically, this system is applicable to an underwater glider platform equipped with an acoustic positioning sensor to form an integrated navigation and positioning system. This integrated navigation and positioning system includes an acoustic positioning system, an inertial navigation unit, an electromagnetic current meter, and also includes components such as a power conversion module, a storage module, and communication cables.

[0033] As Figure 1 , the ultra-short baseline ranging instrument electronic cabin and the ultra-short baseline electro-acoustic transducer of the acoustic positioning system are used to transmit acoustic signals to assist the tracking ship in completing the positioning calculation of the position of the underwater glider. Among them, the ultra-short baseline ranging instrument electronic cabin is mainly used to measure the distance to the beacon and control the transducer connected to the outside. The ultra-short baseline electro-acoustic transducer is used to transmit acoustic signals underwater for the tracking ship to capture. The ultra-short baseline ranging instrument electronic cabin is subjected to anti-static treatment and placed on the central axis of the AUG. The ultra-short baseline transducer has a waterproof design and needs to meet the condition of the angle of its acoustic signal transmission. At the same time, in order to maintain the airtightness of the cabin, it is installed on the front fairing 4 of the AUG and connected to the ranging instrument in the cabin through a watertight cable. The power supply and serial port line of the ultra-short baseline transducer are connected to the front end of the AUG through a watertight cable and then connected to the control unit in the middle cabin of the AUG through a through-hull cable. The debugging port of the ultra-short baseline ranging instrument and the control unit is connected to the front end of the AUG through a watertight cable and then connected to the control unit in the middle cabin of the AUG through a through-hull cable. The connection of the sensor hardware circuit is asFigure 2 , the sensor layout takes into account watertightness, anti-interference and space efficiency. The ultra-short baseline transducer is placed at the front end of the fairing to optimize the acoustic signal emission angle. The inertial unit is installed along the central axis to ensure the alignment of the motion data with the vehicle coordinate system. The electromagnetic current meter is integrated on the front central axis to accurately capture the flow field disturbance.

[0034] The inertial navigation unit includes a three-axis gyroscope, a three-axis accelerometer and a three-axis magnetometer, and can output the changes in angular velocity and acceleration. Among them, the gyroscope can obtain the attitude angle of the body, and the collected value is the angular velocity of the body. The measured value of the accelerometer is the specific force received by the body. The magnetometer estimates the attitude information of the device based on the accurate measurement of the magnetic field intensity around the device. The inertial unit should be installed on the central axis of the AUG, and the Y-axis points in the forward direction. The power supply line of the inertial unit is connected to the control unit to convert to a 5V voltage conversion module, and the serial communication uses RS232.

[0035] The electromagnetic current meter is based on Faraday's law of electromagnetic induction and Lorentz force, and can calculate the ocean current velocity. The electromagnetic current meter is carried on the front central axis of the AUG and is connected to the control unit in the cabin through a watertight cable. That is, the power supply and serial port line of the electromagnetic current meter are connected to the front end of the AUG through a watertight cable, and then connected to the control unit in the middle cabin of the AUG through a through-hull cable. The power supply line of the electromagnetic current meter is connected to the control unit to convert to a 5V voltage conversion module, and the serial communication uses RS232.

[0036] The control unit is the core of the AUG, which processes and fuses the data from each sensor and analyzes the real-time state of the AUG.

[0037] Embodiment 2

[0038] A positioning method for a real-time positioning system of an underwater glider disclosed in Embodiment 1 includes the following steps:

[0039] S1. Data acquisition:

[0040] Receive acoustic ranging data through the ultra-short baseline positioning system; obtain the attitude angle, angular velocity and acceleration data of the underwater glider in real time through the inertial navigation unit; measure the current ocean current velocity data through the electromagnetic current meter.

[0041] S2. Data fusion and optimization:

[0042] Please refer to Figures 3 - 6 , input the attitude angle, angular velocity and acceleration data into the dynamic model to predict the motion state of the underwater glider; perform attitude angle optimization, velocity optimization and position optimization based on the extended Kalman filter formula.

[0043] In the execution of attitude angle optimization, gyroscope angular velocity is fused with accelerometer and magnetometer data, and attitude angle errors are compensated through complementary filtering.

[0044] In the execution of speed optimization, ocean current speed data is introduced into the dynamic model to correct the deviation between the integrated speed of the accelerometer and the simulated speed of the model. The parameters of the dynamic model are calibrated through the historical sea trial data of the underwater glider, and it includes compensating the ocean current speed measured by the electromagnetic current meter to both the integrated speed of the accelerometer and the simulated speed output by the dynamic model, and then fusing them through a Kalman filter.

[0045] In the execution of position optimization, ultra-short baseline ranging data is used as the observation value to filter and correct the cumulative position error of inertial navigation.

[0046] After the above optimizations, real-time position, speed, and attitude information are output.

[0047] Specifically, based on the new integrated navigation system, a fusion algorithm based on INS / USBL is adopted. The fusion algorithm is based on the theory of Kalman filtering, and combines the output information of the dynamic model of AUG, the output information of the inertial unit, the output information of the ultra-short baseline, etc., to complete the estimation and optimization of the position of AUG. The Kalman filter algorithm model is as follows:

[0048]

[0049] The estimation and optimization of the integrated navigation algorithm can be divided into three parts: the optimal estimation of the attitude angle, the optimal estimation of the speed, and the optimal estimation of the position:

[0050] The optimal estimation of the attitude angle is to utilize the complementary characteristics of the accelerometer and gyroscope in the frequency domain, use a complementary filter to fuse the two pieces of data, and compensate the attitude angle obtained by the gyroscope with the attitude angle obtained by the accelerometer and electronic compass, so as to optimize the attitude angle estimation;

[0051] The optimal estimation of the speed is to introduce the control variables of the AUG sea trial data into the dynamic model to obtain the motion speed of AUG, introduce the speed of the ocean current into the integrated speed of the accelerometer and the simulated speed of the dynamic model, and further introduce these two speed information into the Kalman filter to optimize the speed estimation;

[0052] The optimal estimation of the position is to perform error-state Kalman filtering based on the reference position information provided by the ultra-short baseline device and depth sensor, and finally substitute it back into the position information to cancel the generated error value, so as to optimize the position estimation.

[0053] The motion model of AUG is non - linear, and the traditional linear Kalman Filter (KF) cannot be directly applied. Therefore, the Extended Kalman Filter (EKF) is needed to handle the non - linear state equation. EKF can fuse the predicted values of the dynamic model with the sensor measurement values to optimize the position information of AUG.

[0054] 1. State variables of EKF

[0055] In AUG positioning, the state variables usually include:

[0056]

[0057] Among them, (x k y k z k ) are the position coordinates of AUG;

[0058] (v x v y v z ) are the velocity components;

[0059] (φ θ ψ) are the roll angle, pitch angle, and yaw angle.

[0060] 2. Prediction step

[0061]

[0062] Use the dynamic model of AUG to predict the position and velocity at the next moment.

[0063] The state transition equation f(·) is given by the motion model of AUG, including gliding motion, hydrodynamic effects, etc.

[0064]

[0065] The predicted covariance matrix P k,k-1 is calculated through the state transition matrix Φ k,k-1 and is used to measure the uncertainty of the prediction.

[0066] Q k-1 is the process noise covariance, mainly from environmental interference, water flow effects, etc.

[0067] 3. Update step

[0068] (1) Calculate the Kalman gain:

[0069]

[0070] The observation equation h(·) is determined by the sensor measurement model. For example, an inertial measurement unit (IMU) provides acceleration and angular velocity information, which can be used to calculate attitude angles and velocities; an ultra-short baseline (USBL) provides external measurement position information of the AUG.

[0071] (2) State update:

[0072]

[0073] Correct the predicted state: Combine the measurement values Z of the USBL and IMU K to optimize the position information of the AUG.

[0074] (3) Covariance update:

[0075] P k = (I - K k H k )P k,k-1

[0076] Calculate the updated uncertainty covariance P k， for the next iteration.

[0077] The role of the EKF in the AUG is to fuse multi-sensor data (IMU + USBL + dynamics model) to improve the position estimation accuracy. Prediction is performed using the dynamics model, and reasonable position information of the AUG can still be calculated when the measurement interval of the USBL is large or the signal is lost.

[0078] Filter out sensor noise, improve the navigation accuracy of the AUG, and make the positioning information smoother and more accurate.

[0079] Feed back the optimized position error to the inertial navigation unit to suppress its error accumulation.

[0080] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A real-time positioning system for an underwater glider, characterized in that, Comprising: An acoustic positioning system, which consists of an ultra-short baseline ranging instrument electronic cabin and an ultra-short baseline electro-acoustic transducer, and is used to transmit acoustic signals and perform underwater position calculation through a tracking ship; An inertial navigation unit, which includes a gyroscope, an accelerometer, and a magnetometer. The gyroscope is used to obtain the attitude angle data of the underwater glider; the accelerometer is used to obtain the specific force data of the body; the magnetometer is used to detect the direction of the earth's magnetic field to provide heading angle reference data; An electromagnetic current meter, which is used to obtain ocean current velocity data; A control unit, which is used to receive and fuse the data of the acoustic positioning system, the inertial navigation unit, and the electromagnetic current meter, and optimize the real-time position estimation of the underwater glider through a fusion algorithm based on Kalman filtering.

2. The real-time positioning system of the underwater glider according to claim 1, characterized in that: The ultra-short baseline electro-acoustic transducer is installed at the front end of the underwater glider and is used to directionally transmit acoustic signals; the ultra-short baseline ranging instrument electronic cabin is located on the central axis of the underwater glider and is connected to the ultra-short baseline electro-acoustic transducer. The ultra-short baseline ranging instrument electronic cabin is used to receive and process acoustic signals and calculate the relative distance between the underwater glider and the tracking ship.

3. The real-time positioning system of the underwater glider according to claim 1, characterized in that: The inertial navigation unit is installed on the central axis of the underwater glider and the Y-axis points to the forward direction, and is connected to the control unit through a watertight cable.

4. The real-time positioning system of the underwater glider according to claim 1, characterized in that: The electromagnetic current meter is installed on the central axis of the front end of the underwater glider and is connected to the control unit through a watertight cable.

5. A positioning method for a real-time positioning system of an underwater glider according to any one of claims 1-4, characterized in that, Including the following steps: S1. Data acquisition: Receiving acoustic ranging data through the ultra-short baseline positioning system; obtaining the attitude angle, angular velocity, and acceleration data of the underwater glider in real time through the inertial navigation unit; measuring the current ocean current velocity data through the electromagnetic current meter; S2. Data fusion and optimization: Inputting the attitude angle, angular velocity, and acceleration data into the dynamic model to predict the motion state of the underwater glider; Based on the extended Kalman filter formula, performing attitude angle optimization, velocity optimization, and position optimization. In performing attitude angle optimization, fusing the data of the gyroscope, accelerometer, and magnetometer, and compensating the attitude angle error through complementary filtering; in performing velocity optimization, introducing the ocean current velocity data into the dynamic model to correct the deviation between the integrated velocity of the accelerometer and the simulated velocity of the model; in performing position optimization, using the ultra-short baseline ranging data as an observation value to filter and correct the cumulative position error of inertial navigation; S3. Outputting the optimized real-time position, velocity, and attitude information.

6. The real-time positioning method of the underwater glider according to claim 7, characterized in that: The extended Kalman filter formula is:

7. The real-time positioning method of the underwater glider according to claim 8, characterized in that: The parameters of the dynamic model are calibrated through the historical sea trial data of the underwater glider, and include compensating the ocean current velocity measured by the electromagnetic current meter to both the integrated velocity of the accelerometer and the simulated velocity output by the dynamic model, and then performing fusion through a Kalman filter.

8. The real-time positioning method of the underwater glider according to claim 9, characterized in that: Including performing closed-loop feedback after step S2, feeding back the optimized position error to the inertial navigation unit to suppress its error accumulation.

9. An underwater glider, characterized in that: The underwater glider is equipped with the real-time positioning system according to any one of claims 1-4.

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