Underwater robot real-time positioning method, system and terminal based on distributed optical fibers

Abstract

The invention discloses an underwater robot real-time positioning method, system and terminal based on distributed optical fibers, and the method comprises the steps: laying a distributed optical fiber sensing network, and enabling fiber grating sensors to be disposed at different positions of the distributed optical fiber sensing network along the optical fibers; debugging and calibrating the fiber grating sensor to obtain a target fiber grating sensor; optical fiber physical changes caused by movement of the underwater robot are collected through a target optical fiber grating sensor, and a target electric signal is obtained; performing amplification, filtering and digital processing on the target electric signal to obtain time data when the underwater robot arrives at the target fiber grating sensor; according to the time data, the relative position of the underwater robot is calculated based on a time difference of arrival algorithm; and obtaining the absolute coordinate of the distributed optical fiber sensing network in the global coordinate system, and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinate. According to the invention, high-precision positioning of the underwater robot is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater information positioning, and in particular, to a real-time positioning method, system, terminal and computer-readable storage medium for an underwater robot based on distributed optical fiber. Background Art

[0002] Underwater operations refer to various operational activities carried out in an underwater environment. In an underwater operation environment, due to the complexity of signal propagation and the difficulty of communication and navigation, it is often difficult for an underwater robot to accurately obtain its own position information.

[0003] Existing underwater positioning technologies, such as acoustic positioning and inertial navigation, have many limitations. Acoustic positioning is easily affected by underwater environmental noise and multipath effects, and the positioning accuracy decreases with the increase of distance; the inertial navigation system will generate cumulative errors over time, resulting in inaccurate positioning results.

[0004] Therefore, the existing technology still needs to be improved and developed. Summary of the Invention

[0005] The main purpose of the present invention is to provide a real-time positioning method, system, terminal and computer-readable storage medium for an underwater robot based on distributed optical fiber, aiming to solve the deficiencies of underwater positioning technology in the existing technology, where the positioning effect is easily affected by underwater environmental noise and multipath effects, and accurate and stable position information of the underwater robot cannot be provided.

[0006] To achieve the above purpose, the present invention provides a real-time positioning method for an underwater robot based on distributed optical fiber. The real-time positioning method for an underwater robot based on distributed optical fiber includes the following steps:

[0007] Lay a distributed optical fiber sensing network in the underwater operation area, and arrange a plurality of fiber Bragg grating sensors along the optical fiber at different positions of the distributed optical fiber sensing network;

[0008] Debug and calibrate the plurality of fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors;

[0009] Collect the optical fiber physical changes caused by the movement of the underwater robot through the plurality of target fiber Bragg grating sensors to obtain target electrical signals;

[0010] Amplify, filter and digitize the target electrical signals to obtain the time data of the underwater robot reaching the plurality of target fiber Bragg grating sensors;

[0011] Based on the time data, calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network by using the time difference of arrival algorithm;

[0012] Obtain the absolute coordinates of the distributed fiber optic sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

[0013] Optionally, in the real-time positioning method of the underwater robot based on distributed fiber optics, when laying the distributed fiber optic sensing network in the underwater operation area and setting a plurality of fiber Bragg grating sensors at different positions of the distributed fiber optic sensing network, it specifically includes:

[0014] Plan the fiber laying path according to the size, shape and task requirements of the underwater operation area;

[0015] Lay the optical fiber according to the fiber laying path to form a distributed fiber optic sensing network, and fix and test the laid optical fiber.

[0016] Optionally, in the real-time positioning method of the underwater robot based on distributed fiber optics, when debugging and calibrating a plurality of the fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors, it specifically includes:

[0017] Input a standard signal source into the distributed fiber optic sensing network, obtain the optical signals reflected by each of the fiber Bragg grating sensors, analyze the optical signals to obtain wavelength changes, obtain strain information according to the wavelength changes, and calibrate the positions and angles of the plurality of fiber Bragg grating sensors according to the strain information;

[0018] According to the type of underwater robot to be positioned, calibrate the sensitivity and response frequency range of the plurality of fiber Bragg grating sensors after adjusting the positions and angles to obtain a plurality of target fiber Bragg grating sensors.

[0019] Optionally, in the real-time positioning method of the underwater robot based on distributed fiber optics, when amplifying, filtering and digitizing the target electrical signal to obtain the time data of the underwater robot reaching a plurality of the target fiber Bragg grating sensors, it specifically includes:

[0020] Adjust the gain of the low-noise amplifier according to the noise level in the test environment to obtain a target amplifier, and use the target amplifier to amplify the target electrical signal to obtain an amplified signal;

[0021] Select a filter whose type and cut-off frequency match the spectrum of the underwater environmental noise as the target filter, and use the target filter to filter the amplified signal to obtain filtered data;

[0022] Adjust the sampling frequency and resolution of the analog-to-digital converter according to the test environment to obtain the target analog-to-digital converter, and use the target analog-to-digital converter to digitize the filtered data to obtain the time data of the underwater robot reaching multiple target fiber Bragg grating sensors.

[0023] Optionally, in the real-time positioning method of the underwater robot based on distributed optical fiber, wherein, according to the time data, calculating the relative position of the underwater robot relative to the distributed optical fiber sensing network based on the time difference of arrival algorithm specifically includes:

[0024] Calculate the distance difference between three target fiber Bragg grating sensors according to the time data:

[0025] Δd AB = v·(t2 - t1);

[0026] Δd AC = v·(t3 - t1);

[0027] Wherein, Δd AB is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor B, Δd AC is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor C, v is the propagation speed of light in the optical fiber, and t1, t2, and t3 are the time data of target fiber Bragg grating sensor A, target fiber Bragg grating sensor B, and target fiber Bragg grating sensor C respectively;

[0028] Obtain the sensing point coordinates of target fiber Bragg grating sensor A, target fiber Bragg grating sensor B, and target fiber Bragg grating sensor C, and the sensing point coordinates are obtained from the coordinate system pre-constructed in the distributed optical fiber sensing network;

[0029] Calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network according to the sensing point coordinates and the distance difference:

[0030]

[0031] Wherein, x, y, and z are the abscissa, ordinate, and vertical coordinate of the relative position respectively, x1, y1, and z1 are the abscissa, ordinate, and vertical coordinate of target fiber Bragg grating sensor A respectively, x2, y2, and z2 are the abscissa, ordinate, and vertical coordinate of target fiber Bragg grating sensor B respectively, and x3, y3, and z3 are the abscissa, ordinate, and vertical coordinate of target fiber Bragg grating sensor C respectively.

[0032] Optionally, in the real-time positioning method for an underwater robot based on distributed optical fiber, the step of obtaining the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinates specifically includes:

[0033] Previously, use GPS and an underwater acoustic positioning system to locate the key nodes of the distributed optical fiber sensing network, obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and store the absolute coordinates;

[0034] After calculating the relative position, read the stored absolute coordinates, and use a coordinate transformation formula to calculate the absolute position of the underwater robot according to the absolute coordinates and the relative position.

[0035] Optionally, in the real-time positioning method for an underwater robot based on distributed optical fiber, after calculating the absolute position of the underwater robot, the following steps are further included:

[0036] Transmit the absolute position of the underwater robot to the control center or receiving device in real time through the optical fiber, and ensure the accuracy of data transmission through optical modulation technology, data encoding, and error correction functions.

[0037] In addition, to achieve the above object, the present invention also provides a real-time positioning system for an underwater robot based on distributed optical fiber, wherein the real-time positioning system for an underwater robot based on distributed optical fiber includes:

[0038] An optical fiber network setting module, configured to lay a distributed optical fiber sensing network in the underwater operation area, and arrange a plurality of fiber Bragg grating sensors at different positions of the distributed optical fiber sensing network along the optical fiber;

[0039] An optical fiber debugging and calibration module, configured to debug and calibrate the plurality of fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors;

[0040] A signal acquisition module, configured to collect the optical fiber physical changes caused by the movement of the underwater robot through the plurality of target fiber Bragg grating sensors to obtain target electrical signals;

[0041] A signal processing module, configured to amplify, filter, and digitize the target electrical signals to obtain the time data of the underwater robot reaching the plurality of target fiber Bragg grating sensors;

[0042] A relative position calculation module, configured to calculate the relative position of the underwater robot with respect to the distributed optical fiber sensing network based on the time difference of arrival algorithm according to the time data;

[0043] An absolute position calculation module, configured to obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

[0044] In addition, to achieve the above object, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a real-time positioning program for an underwater robot based on distributed optical fiber stored on the memory and executable on the processor. When the real-time positioning program for an underwater robot based on distributed optical fiber is executed by the processor, the steps of the real-time positioning method for an underwater robot based on distributed optical fiber as described above are implemented.

[0045] In addition, to achieve the above object, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a real-time positioning program for an underwater robot based on distributed optical fiber. When the real-time positioning program for an underwater robot based on distributed optical fiber is executed by a processor, the steps of the real-time positioning method for an underwater robot based on distributed optical fiber as described above are implemented.

[0046] In the present invention, a distributed optical fiber sensing network is laid, and fiber Bragg grating sensors are arranged at different positions of the distributed optical fiber sensing network along the optical fiber; the fiber Bragg grating sensors are debugged and calibrated to obtain target fiber Bragg grating sensors; through the target fiber Bragg grating sensors, the physical changes of the optical fiber caused by the movement of the underwater robot are collected to obtain target electrical signals; the target electrical signals are amplified, filtered, and digitized to obtain the time data of the underwater robot reaching the target fiber Bragg grating sensors; according to the time data, the relative position of the underwater robot relative to the distributed optical fiber sensing network is calculated based on the time difference of arrival algorithm; the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system are obtained, and the absolute position of the underwater robot is calculated according to the relative position and the absolute coordinates. The present invention realizes the high-precision positioning of the underwater robot. Description of the Drawings

[0047] Figure 1 is a flowchart of a preferred embodiment of the real-time positioning method for an underwater robot based on distributed optical fiber of the present invention;

[0048] Figure 2 is a structural diagram of a preferred embodiment of the real-time positioning system for an underwater robot based on distributed optical fiber of the present invention;

[0049] Figure 3 is a structural diagram of a preferred embodiment of the terminal of the present invention. Detailed Embodiments

[0050] This application provides a real-time positioning method, system and terminal for an underwater robot based on distributed optical fiber. To make the purpose, technical solution and effect of this application clearer and more definite, the following further elaborates on this application with reference to the accompanying drawings and by way of examples. It should be understood that the specific examples described herein are only used to explain this application and are not used to limit this application.

[0051] Those skilled in the art of this technology can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used here have the same meaning as the general understanding of those of ordinary skill in the field to which this application belongs. It should also be understood that terms such as those defined in a general dictionary should be understood to have a meaning consistent with the meaning in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless specifically defined as here.

[0052] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, such descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the technical features indicated. Thus, features defined with "first", "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0053] The real-time positioning method for an underwater robot based on distributed optical fiber described in the preferred embodiment of the present invention is as Figure 1 shown. The real-time positioning method for an underwater robot based on distributed optical fiber includes the following steps:

[0054] Step S10: Lay a distributed optical fiber sensing network in the underwater operation area, and arrange a plurality of fiber Bragg grating sensors along the optical fiber at different positions of the distributed optical fiber sensing network.

[0055] The distributed optical fiber system has the advantages of high sensitivity and strong environmental adaptability, and can perform high-density detection and positioning on large-scale underwater close-range targets. However, currently, the distributed optical fiber system has not been applied to the position positioning of underwater robots.

[0056] Specifically, according to the size, shape and task requirements of the underwater operation area, plan the optical fiber laying path; lay the optical fiber according to the optical fiber laying path to form a distributed optical fiber sensing network, and fix and test the laid optical fiber to ensure that the optical fiber meets the performance requirements.

[0057] In this embodiment, according to the size, shape and task requirements of the underwater operation area, the optical fiber laying path is planned. For example, when conducting underwater topographic surveying, according to the scope of the survey area, special underwater laying equipment is used to lay the optical fiber on the seabed in a grid pattern. For the fixation of the optical fiber, special fixing fixtures can be used or buried to a certain depth in the seabed to ensure the stability of the optical fiber under the impact of water flow. At the same time, it is necessary to ensure that the connection points between the optical fibers are firm and reliable to avoid signal transmission interruption. The laid optical fiber is tested to check its continuity and loss to ensure that it meets the performance requirements.

[0058] Among them, the special fixing fixtures include but are not limited to: Compression fixtures: Generally composed of a clamping module and a compression module. The contact surfaces of the upper and lower parts of the clamping module have small arc grooves, which together form a cavity for fixing the optical fiber or optical cable; the contact surfaces of the upper and lower parts of the compression module have large arc grooves for fixing the clamping module, and the opening and closing and fastening are realized through a hinge structure and a fastening structure. Wedge fixtures: Usually have a fastening part, including a clamping body, an outer armor clamping cone and an inner armor clamping cone arranged in sequence from outside to inside, and are provided with a first clamping hole for clamping the outer armor steel wire and a second clamping hole for clamping the inner armor steel wire. Both holes are tapered holes, and the outer armor steel wire and the inner armor steel wire are respectively clamped and fixed in the corresponding holes. U-shaped fixtures: The shape is U-shaped, one end is fixed to a fixed object or equipment on the seabed, and the other end fixes the optical fiber or optical cable in the U-shaped groove through components such as nuts.

[0059] It can be seen that different from traditional underwater positioning technologies, the present invention uses a distributed optical fiber system to construct a sensing network in the underwater operation area. In the selection of optical fibers, special material optical fibers with high corrosion resistance, flexibility and compressive resistance (such as armored optical fibers) are selected, and according to different underwater operation scenarios (large-area monitoring, linear pipeline detection, etc.), targeted laying methods (grid pattern or laying along the pipeline) are adopted to form a sensing network with a wide coverage range and adapted to the complex underwater environment. This layout method makes full use of the large-scale advantages of the distributed optical fiber system, can conduct all-round monitoring of the underwater robot, and provides a stable basis for subsequent precise position positioning.

[0060] Step S20: Debug and calibrate the multiple fiber Bragg grating sensors to obtain multiple target fiber Bragg grating sensors.

[0061] Specifically, a standard signal source is input into the distributed optical fiber sensing network to obtain the optical signals reflected by each of the fiber Bragg grating sensors, analyze the optical signals to obtain the wavelength change, obtain the strain information according to the wavelength change, and calibrate the positions and angles of the multiple fiber Bragg grating sensors according to the strain information.

[0062] A fiber Bragg grating is a periodic refractive index modulation structure formed within the core of an optical fiber, which has the characteristic of reflecting light of a specific wavelength. When the fiber Bragg grating is subjected to strain, its grating period and refractive index change, resulting in a wavelength shift of the reflected light. This wavelength shift is linearly related to the applied strain.

[0063] It can be understood that for fiber Bragg grating sensors, their positions and angles need to be precisely adjusted to maximize their perception of physical changes in the optical fiber. Therefore, in this embodiment, the signal acquisition module is first calibrated by a standard signal source. Specifically, in a distributed optical fiber system, multiple fiber Bragg grating sensors are distributed along the optical fiber at different positions. By inputting broadband light (i.e., the signal emitted by the underwater robot) into the optical fiber, each fiber Bragg grating will reflect an optical signal of its respective specific wavelength. By using equipment such as a spectral analyzer to measure the wavelength changes of these reflected lights, the strain information at the location of each fiber Bragg grating can be obtained, thereby achieving distributed strain measurement at multiple positions along the optical fiber.

[0064] Furthermore, according to the type of underwater robot to be positioned, the sensitivity and response frequency range of the multiple fiber Bragg grating sensors after adjusting their positions and angles are calibrated to obtain multiple target fiber Bragg grating sensors.

[0065] It can be understood that the sensitivity and response frequency range of the fiber Bragg grating sensor determine the type of signal that the fiber Bragg grating sensor can receive. In this application, the sensitivity and response frequency range of the multiple fiber Bragg grating sensors after adjusting their positions and angles are calibrated according to the type of underwater robot to be positioned. When the multiple obtained target fiber Bragg grating sensors collect signals, they will only collect signals within the corresponding range, making them match the signal characteristics generated by the movement of the underwater robot, which can avoid interference from other signals.

[0066] Step S30: Through the multiple target fiber Bragg grating sensors, collect the physical changes in the optical fiber caused by the movement of the underwater robot to obtain a target electrical signal.

[0067] Specifically, in this application, a distributed optical fiber sensing network is laid in the underwater operation area, and the signal acquisition module is used to sense the physical changes in the optical fiber caused by the movement of the underwater robot, including strain and vibration, etc., to obtain a target electrical signal.

[0068] Step S40: Amplify, filter, and digitize the target electrical signal to obtain the time data of the underwater robot reaching the multiple target fiber Bragg grating sensors.

[0069] Specifically, the gain of the low-noise amplifier is adjusted according to the noise level in the test environment to obtain a target amplifier, and the target amplifier is used to amplify the target electrical signal to obtain an amplified signal.

[0070] In this embodiment, the gain of the low-noise amplifier is adjusted, and according to the noise level in the test environment, the gain is set within a suitable range to avoid signal distortion or excessive amplification of noise.

[0071] Further, a filter whose type and cut-off frequency match the spectrum of the underwater ambient noise is selected as the target filter, and the target filter is used to filter the amplified signal to obtain filtered data.

[0072] According to the spectral analysis of the underwater ambient noise, a suitable filter type and cut-off frequency are selected. For example, if the noise is mainly concentrated in the low-frequency range, a high-pass filter is selected and the cut-off frequency is set at a position higher than the noise frequency.

[0073] Even further, the sampling frequency and resolution of the analog-to-digital converter are correspondingly adjusted according to the test environment to obtain a target analog-to-digital converter, and the target analog-to-digital converter is used to digitize the filtered data to obtain the time data of the underwater robot reaching multiple target fiber Bragg grating sensors.

[0074] It can be understood that the sampling frequency and resolution of the analog-to-digital converter are adjusted to ensure that it can accurately digitize the signal, while avoiding data redundancy and processing burden caused by too high sampling frequency.

[0075] Step S50: Based on the time data, calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network using the time difference of arrival algorithm.

[0076] Specifically, the distance differences between three target fiber Bragg grating sensors are calculated according to the time data:

[0077] Δd AB = v·(t2 - t1);

[0078] Δd AC = v·(t3 - t1);

[0079] where, Δd AB is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor B, Δd AC is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor C, v is the propagation speed of light in the optical fiber, and t 11 , t2, and t3 are the time data of target fiber Bragg grating sensor A, target fiber Bragg grating sensor B, and target fiber Bragg grating sensor C respectively.

[0080] It is understandable that obtaining time data requires the use of high-precision time measurement devices, such as atomic clocks or high-precision time synchronization mechanisms, to ensure the accuracy of the signal arrival time measurement, accurately calculate the time difference, and use the iterative method or matrix method to solve the above hyperbolic equations to improve the calculation speed and accuracy.

[0081] Furthermore, in this embodiment, in order to accurately measure and record the coordinates of each sensing point in the distributed optical fiber sensing network and establish an accurate coordinate system, the sensing point coordinates are obtained from the coordinate system pre-constructed in the distributed optical fiber sensing network.

[0082] Obtain the sensing point coordinates of the target fiber Bragg grating sensor A, target fiber Bragg grating sensor B, and target fiber Bragg grating sensor C.

[0083] Even further, calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network according to the sensing point coordinates and the distance difference:

[0084]

[0085] Wherein, x, y, and z are respectively the abscissa, ordinate, and vertical coordinate of the relative position, x1, y1, and z1 are respectively the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor A, x2, y2, and z2 are respectively the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor B, and x3, y3, and z3 are respectively the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor C.

[0086] It is understandable that this application calculates the relative position of the underwater robot relative to the distributed optical fiber sensing network using the time difference of arrival algorithm. Assume that the underwater robot emits a signal at time t0, and the times for the signal to propagate to two different sensing points A and B on the optical fiber are t1 and t2 respectively, and the propagation speed of light in the optical fiber is v (usually known and approximately constant), then the distance difference Δd AB and Δd AC can be calculated by the following formula: Δd AB = v·(t2 - t1), Δd AC = v·(t3 - t1); According to the definition of a hyperbola, the position of the underwater robot is located on the hyperbola with A and B as the foci and the distance difference as Δd AB and Δd AC . To determine the accurate position of the underwater robot, at least three sensing points are required to form multiple hyperbolas, and the intersection point is the position of the underwater robot.

[0087] It can be seen that the present invention calculates the relative position of the underwater robot with respect to the distributed optical fiber sensing network by using the time difference of arrival algorithm. By accurately measuring the time difference of the signals emitted by the underwater robot reaching different optical fiber sensing points, and combining with the propagation speed of light in the optical fiber, the precise calculation of the relative position can be achieved by applying the hyperbolic positioning principle. Although traditional acoustic positioning also has calculations based on time difference, its accuracy is severely affected by multipath effects and noise in the complex underwater environment; while the TDOA algorithm of the present invention utilizes the advantage of the distributed optical fiber system being immune to noise interference and can calculate the relative position more accurately. In addition, compared with the relative positioning method of inertial navigation, the TDOA algorithm will not produce cumulative errors during long-term operation and can provide accurate relative position information within a large scale range.

[0088] It should be noted that in addition to the time difference of arrival algorithm, the present application can further optimize the positioning algorithm based on signal strength. For example, establish a more accurate underwater signal propagation attenuation model, consider the influence of more environmental factors (such as water quality, water temperature, water flow, etc.) on the signal strength, and improve the accuracy of calculating the relative position according to the signal strength. Or adopt machine learning or deep learning algorithms, use a large amount of underwater robot position and corresponding signal strength data for training to obtain an intelligent model that can predict the position according to the signal strength, and continuously optimize the algorithm through online learning to improve the positioning accuracy.

[0089] Step S60: Obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

[0090] Specifically, the key nodes of the distributed optical fiber sensing network are pre-positioned by GPS and the underwater acoustic positioning system to obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and the absolute coordinates are stored.

[0091] Given the position information of the distributed optical fiber sensing network in the global coordinate system, determine the absolute coordinates of the reference point for relative position calculation. Assume the coordinates of this reference point in the global coordinate system are (x0, y0, z0), where x0, y0, and z0 are the abscissa, ordinate, and vertical coordinate of the absolute coordinates respectively. These absolute coordinates can be obtained by means of pre-high-precision measurement. For example, when laying the distributed optical fiber sensing network, use high-precision positioning equipment (such as GPS combined with the underwater acoustic positioning system or other high-precision positioning systems) to position the key nodes of the distributed optical fiber sensing network, and store the position information of these nodes in the system.

[0092] Further, after calculating the relative position, read the stored absolute coordinates, and calculate the absolute position of the underwater robot according to the absolute coordinates and the relative position using a coordinate transformation formula.

[0093] The relative position can be converted to absolute coordinates using a coordinate transformation formula. In three-dimensional space, the most common is to use a translation transformation formula, and the coordinate transformation is expressed as:

[0094] x a = x + x0;

[0095] y a = y + y0;

[0096] z a = z + z0;

[0097] Where, (x a , y a , z a ) is the absolute position of the underwater robot in the global coordinate system, and x a , y a , z a are the abscissa, ordinate, and vertical coordinate of the underwater robot in the global coordinate system, respectively.

[0098] Even further, after calculating the absolute position of the underwater robot, it further includes:

[0099] Transmit the absolute position of the underwater robot to the control center or receiving device in real time through an optical fiber, and ensure the accuracy of data transmission through optical modulation technology, data encoding, and error correction functions.

[0100] In this embodiment, the calculated absolute position information of the underwater robot is transmitted using an optical fiber, and at the same time, advanced optical modulation technologies (such as intensity modulation, phase modulation) and data encoding (such as Manchester encoding, differential Manchester encoding) and error correction mechanisms (such as cyclic redundancy check) are adopted.

[0101] When performing data transmission, select an appropriate optical modulation method. For example, according to the transmission distance and bandwidth requirements, if the transmission distance is short, intensity modulation can be used; if high requirements are placed on bandwidth and anti-interference performance, phase modulation can be used. For data encoding, Manchester encoding or differential Manchester encoding can be adopted to improve the reliability and synchronization of data transmission. Establish a data verification mechanism, such as cyclic redundancy check, to verify the transmitted data and ensure that the data received at the receiving end is accurate and error-free. This ensures the accuracy, reliability, and anti-interference performance of the position information during transmission, guaranteeing that the position information can be stably and accurately transmitted to the control center or receiving device in the complex underwater environment. The data transmission scheme of this application utilizes the low attenuation and anti-interference characteristics of optical fibers, combined with advanced modulation and encoding technologies, to improve the overall performance of data transmission.

[0102] It should be noted that in another embodiment of this application, existing different positioning technologies (such as acoustic positioning, inertial navigation, and distributed optical fiber systems) can be integrated instead of relying solely on the distributed optical fiber system. For example, use the distributed optical fiber system as the main positioning means, supplemented by acoustic positioning and inertial navigation at the same time, and utilize the advantages of different technologies for data fusion. In the data processing stage, through weighted average, Kalman filtering, or other data fusion algorithms, comprehensively integrate the large-scale detection of acoustic positioning, the short-term high-precision of inertial navigation, and the high-resolution positioning information of the distributed optical fiber system to obtain more stable and accurate position information. The advantage of doing this is to integrate the advantages of multiple technologies and improve the robustness and adaptability of the positioning system. However, the disadvantage is that the system complexity increases, and problems such as data compatibility, synchronization, and weight allocation between different technologies need to be solved, and the cost may be relatively high.

[0103] Furthermore, as Figure 2 shown, based on the above-mentioned real-time underwater robot positioning method based on distributed optical fiber, the present invention also correspondingly provides a real-time underwater robot positioning system based on distributed optical fiber, wherein the real-time underwater robot positioning system based on distributed optical fiber includes:

[0104] An optical fiber network setting module 51, configured to lay a distributed optical fiber sensing network in the underwater operation area, and arrange multiple fiber Bragg gratings sensors at different positions of the distributed optical fiber sensing network along the optical fiber;

[0105] An optical fiber debugging and calibration module 52, configured to debug and calibrate multiple fiber Bragg gratings sensors to obtain multiple target fiber Bragg gratings sensors;

[0106] A signal acquisition module 53, configured to collect the optical fiber physical changes caused by the movement of the underwater robot through multiple target fiber Bragg gratings sensors to obtain target electrical signals;

[0107] A signal processing module 54, configured to amplify, filter, and digitize the target electrical signal to obtain time data of the underwater robot reaching multiple target fiber Bragg grating sensors;

[0108] A relative position calculation module 55, configured to calculate the relative position of the underwater robot with respect to the distributed optical fiber sensing network based on the time difference of arrival algorithm according to the time data;

[0109] An absolute position calculation module 56, configured to obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

[0110] Further, as Figure 3 shown, based on the above-mentioned real-time positioning method and system of the underwater robot based on distributed optical fiber, the present invention also correspondingly provides a terminal, and the terminal includes a processor 10, a memory 20, and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0111] The memory 20 may be an internal storage unit of the terminal in some embodiments, such as a hard disk or a memory of the terminal. The memory 20 may also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal. Further, the memory 20 may also include both the internal storage unit and the external storage device of the terminal. The memory 20 is used to store application software installed on the terminal and various types of data, such as program codes installed on the terminal. The memory 20 may also be used to temporarily store data that has been output or will be output. In one embodiment, a real-time positioning program 40 of the underwater robot based on distributed optical fiber is stored on the memory 20, and the real-time positioning program 40 of the underwater robot based on distributed optical fiber can be executed by the processor 10, so as to implement the real-time positioning method of the underwater robot based on distributed optical fiber in this application.

[0112] The processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chips in some embodiments, and is used to run the program codes stored in the memory 20 or process data, such as executing the real-time positioning method of the underwater robot based on distributed optical fiber, etc.

[0113] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch screen, etc. The display 30 is used to display information of the terminal and to display a visual user interface. Components of the terminal communicate with each other through a system bus.

[0114] In one embodiment, when the processor 10 executes the real-time positioning program 40 of the underwater robot based on distributed optical fiber in the memory 20, the following steps are implemented:

[0115] Lay a distributed optical fiber sensing network in the underwater operation area, and arrange a plurality of fiber Bragg grating sensors at different positions of the distributed optical fiber sensing network along the optical fiber;

[0116] Debug and calibrate a plurality of the fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors;

[0117] Collect the physical changes of the optical fiber caused by the movement of the underwater robot through a plurality of the target fiber Bragg grating sensors to obtain target electrical signals;

[0118] Amplify, filter, and digitize the target electrical signals to obtain the time data of the underwater robot reaching a plurality of the target fiber Bragg grating sensors;

[0119] Based on the time data, calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network based on the time difference of arrival algorithm;

[0120] Obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

[0121] Among them, the laying of the distributed optical fiber sensing network in the underwater operation area and arranging a plurality of fiber Bragg grating sensors at different positions of the distributed optical fiber sensing network specifically includes:

[0122] Plan the optical fiber laying path according to the size, shape, and task requirements of the underwater operation area;

[0123] Lay the optical fiber according to the optical fiber laying path to form a distributed optical fiber sensing network, and fix and test the laid optical fiber.

[0124] Among them, the debugging and calibration of a plurality of the fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors specifically includes:

[0125] Input a standard signal source into the distributed optical fiber sensing network, obtain the optical signals reflected by each of the fiber Bragg grating sensors, analyze the optical signals to obtain wavelength changes, obtain strain information based on the wavelength changes, and calibrate the positions and angles of multiple fiber Bragg grating sensors according to the strain information;

[0126] According to the type of underwater robot to be positioned, calibrate the sensitivity and response frequency range of multiple fiber Bragg grating sensors after adjusting their positions and angles to obtain multiple target fiber Bragg grating sensors.

[0127] Among them, the amplification, filtering, and digital processing of the target electrical signal to obtain the time data of the underwater robot reaching multiple target fiber Bragg grating sensors specifically include:

[0128] Adjust the gain of the low-noise amplifier according to the noise level in the test environment to obtain a target amplifier, and use the target amplifier to amplify the target electrical signal to obtain an amplified signal;

[0129] Select a filter with a type and cut-off frequency matching the spectrum of underwater environmental noise as the target filter, and use the target filter to filter the amplified signal to obtain filtered data;

[0130] Adjust the sampling frequency and resolution of the analog-to-digital converter according to the test environment to obtain a target analog-to-digital converter, and use the target analog-to-digital converter to digitally process the filtered data to obtain the time data of the underwater robot reaching multiple target fiber Bragg grating sensors.

[0131] Among them, the calculation of the relative position of the underwater robot relative to the distributed optical fiber sensing network based on the time difference of arrival algorithm according to the time data specifically includes:

[0132] Calculate the distance differences between three target fiber Bragg grating sensors according to the time data:

[0133] Δd AB =v·(t2 - t1);

[0134] Δd AC =v·(t3 - t1);

[0135] Among them, Δd AB is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor B, Δd ACΔ is the distance difference between the target fiber Bragg grating sensor A and the target fiber Bragg grating sensor C, v is the propagation speed of light in the optical fiber, and t1, t2, and t3 are the time data of the target fiber Bragg grating sensor A, the target fiber Bragg grating sensor B, and the target fiber Bragg grating sensor C, respectively;

[0136] Obtain the sensing point coordinates of the target fiber Bragg grating sensor A, the target fiber Bragg grating sensor B, and the target fiber Bragg grating sensor C, where the sensing point coordinates are obtained from the coordinate system pre-constructed in the distributed optical fiber sensing network;

[0137] Calculate the relative position of the underwater robot with respect to the distributed optical fiber sensing network according to the sensing point coordinates and the distance difference:

[0138]

[0139]

[0140] Where x, y, and z are the abscissa, ordinate, and vertical coordinate of the relative position, x1, y1, and z1 are the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor A, x2, y2, and z2 are the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor B, and x3, y3, and z3 are the abscissa, ordinate, and vertical coordinate of the target fiber Bragg grating sensor C.

[0141] Where obtaining the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinates specifically includes:

[0142] Pre-locate the key nodes of the distributed optical fiber sensing network through GPS and the underwater acoustic positioning system to obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and store the absolute coordinates;

[0143] After calculating the relative position, read the stored absolute coordinates, and calculate the absolute position of the underwater robot according to the absolute coordinates and the relative position using the coordinate transformation formula.

[0144] Where calculating the absolute position of the underwater robot, and then further includes:

[0145] Transmit the absolute position of the underwater robot to the control center or the receiving device in real time through the optical fiber, and ensure the accuracy of data transmission through optical modulation technology, data coding, and error correction functions.

[0146] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a real-time positioning program for an underwater robot based on distributed optical fiber. When the real-time positioning program for the underwater robot based on distributed optical fiber is executed by a processor, the steps of the real-time positioning method for the underwater robot based on distributed optical fiber as described above are implemented.

[0147] In summary, the present invention proposes a real-time positioning method, system and terminal for an underwater robot based on distributed optical fiber. The method includes: laying a distributed optical fiber sensing network, arranging fiber Bragg grating sensors along the optical fiber at different positions of the distributed optical fiber sensing network; debugging and calibrating the fiber Bragg grating sensors to obtain target fiber Bragg grating sensors; collecting the optical fiber physical changes caused by the movement of the underwater robot through the target fiber Bragg grating sensors to obtain target electrical signals; amplifying, filtering and digitizing the target electrical signals to obtain the time data of the underwater robot reaching the target fiber Bragg grating sensors; calculating the relative position of the underwater robot based on the time difference of arrival algorithm according to the time data; obtaining the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinates. The present invention realizes the high-precision positioning of the underwater robot.

[0148] It should be noted that in this article, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of another identical element in the process, method, article or terminal including the element.

[0149] Of course, those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided by the present invention can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0150] It should be understood that the application of the present invention is not limited to the above examples. For those of ordinary skill in the art, improvements or transformations can be made according to the above description. All such improvements and transformations should fall within the protection scope of the appended claims of the present invention.

Claims

1. A real-time positioning method for an underwater robot based on distributed optical fiber, characterized in that The described real-time positioning method for an underwater robot based on distributed optical fiber includes: Laying a distributed optical fiber sensing network in the underwater operation area, and arranging a plurality of fiber Bragg grating sensors at different positions of the distributed optical fiber sensing network along the optical fiber; Debugging and calibrating the plurality of fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors; Collecting the physical changes of the optical fiber caused by the movement of the underwater robot through the plurality of target fiber Bragg grating sensors to obtain target electrical signals; Amplifying, filtering, and digitizing the target electrical signals to obtain the time data of the underwater robot reaching the plurality of target fiber Bragg grating sensors; Based on the time data, calculating the relative position of the underwater robot with respect to the distributed optical fiber sensing network using the time difference of arrival algorithm; Obtaining the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinates.

2. The real-time positioning method of the underwater robot based on distributed optical fiber according to claim 1, characterized in that, The step of laying a distributed optical fiber sensing network in the underwater operation area and arranging a plurality of fiber Bragg grating sensors at different positions of the distributed optical fiber sensing network specifically includes: Planning the optical fiber laying path according to the size, shape, and task requirements of the underwater operation area; Laying the optical fiber according to the optical fiber laying path to form a distributed optical fiber sensing network, and fixing and testing the laid optical fiber.

3. The real-time positioning method of the underwater robot based on distributed optical fiber according to claim 1, characterized in that, The step of debugging and calibrating the plurality of fiber Bragg grating sensors to obtain a plurality of target fiber Bragg grating sensors specifically includes: Inputting a standard signal source into the distributed optical fiber sensing network to obtain the optical signals reflected by each fiber Bragg grating sensor, analyzing the optical signals to obtain wavelength changes, obtaining strain information according to the wavelength changes, and calibrating the positions and angles of the plurality of fiber Bragg grating sensors according to the strain information; Calibrating the sensitivity and response frequency range of the plurality of fiber Bragg grating sensors with adjusted positions and angles according to the type of the underwater robot to be positioned to obtain a plurality of target fiber Bragg grating sensors.

4. The real-time positioning method of the underwater robot based on distributed optical fiber according to claim 1, characterized in that The step of amplifying, filtering, and digitizing the target electrical signals to obtain the time data of the underwater robot reaching the plurality of target fiber Bragg grating sensors specifically includes: Adjusting the gain of the low-noise amplifier according to the noise level in the test environment to obtain a target amplifier, and using the target amplifier to amplify the target electrical signals to obtain amplified signals; Selecting a filter with a type and cut-off frequency matching the spectrum of the underwater environment noise as the target filter, and using the target filter to filter the amplified signals to obtain filtered data; Correspondingly adjusting the sampling frequency and resolution of the analog-to-digital converter according to the test environment to obtain a target analog-to-digital converter, and using the target analog-to-digital converter to digitize the filtered data to obtain the time data of the underwater robot reaching the plurality of target fiber Bragg grating sensors.

5. The real-time positioning method of the underwater robot based on distributed optical fiber according to claim 1, wherein, The step of calculating the relative position of the underwater robot with respect to the distributed optical fiber sensing network based on the time data using the time difference of arrival algorithm specifically includes: The distance difference between the three target fiber grating sensors is calculated according to the time data: Δd AB = v·(t2 - t1); Δd AC =v·(t3-t1); Where Δd AB is the distance difference between target fiber Bragg grating sensor A and target fiber Bragg grating sensor B, Δd AC is the distance difference between the target fiber Bragg grating sensor A and the target fiber Bragg grating sensor C, v is the propagation speed of light in the optical fiber, t1, t2 and t3 are the time data of the target fiber Bragg grating sensor A, the target fiber Bragg grating sensor B and the target fiber Bragg grating sensor C respectively; Acquiring the sensing point coordinates of the target fiber grating sensor A, the target fiber grating sensor B, and the target fiber grating sensor C, wherein the sensing point coordinates are obtained from a coordinate system pre-constructed in the distributed fiber optic sensing network; The relative position of the underwater robot relative to the distributed optical fiber sensing network is calculated according to the sensing point coordinates and the distance difference: Among them, x, y and z are the horizontal coordinate, vertical coordinate and vertical coordinate of the relative position, x1, y1 and z1 are the horizontal coordinate, vertical coordinate and vertical coordinate of the target fiber Bragg grating sensor A, x2, y2 and z2 are the horizontal coordinate, vertical coordinate and vertical coordinate of the target fiber Bragg grating sensor B, and x3, y3 and z3 are the horizontal coordinate, vertical coordinate and vertical coordinate of the target fiber Bragg grating sensor C.

6. The real-time positioning method for underwater robots based on distributed optical fibers according to claim 5, characterized in that: The step of obtaining the absolute coordinates of the distributed optical fiber sensing network in a global coordinate system and calculating the absolute position of the underwater robot according to the relative position and the absolute coordinates specifically includes: Positioning key nodes of the distributed optical fiber sensing network using GPS and an underwater acoustic positioning system to obtain absolute coordinates of the distributed optical fiber sensing network in a global coordinate system, and storing the absolute coordinates; After the relative position is calculated, the stored absolute coordinates are read, and the absolute position of the underwater robot is calculated using a coordinate conversion formula based on the absolute coordinates and the relative position.

7. The real-time positioning method of the underwater robot based on distributed optical fiber according to claim 1, characterized in that The absolute position of the underwater robot is calculated, and then the method further includes: The absolute position of the underwater robot is transmitted to a control center or a receiving device in real time via optical fiber, and optical modulation technology, data encoding and error correction functions are used during the data transmission process.

8. A real-time positioning system for an underwater robot based on distributed optical fiber, characterized in that, The distributed optical fiber-based underwater robot real-time positioning system includes: An optical fiber network setting module is used to lay a distributed optical fiber sensing network in the underwater operation area and set a plurality of optical fiber Bragg grating sensors at different positions along the optical fiber in the distributed optical fiber sensing network; An optical fiber debugging and calibration module is used to debug and calibrate the plurality of optical fiber Bragg grating sensors to obtain a plurality of target optical fiber Bragg grating sensors; A signal acquisition module, configured to acquire the physical changes of the optical fiber caused by the movement of the underwater robot through the plurality of target fiber Bragg grating sensors, and obtain a target electrical signal; a signal processing module, configured to amplify, filter, and digitize the target electrical signal to obtain time data of when the underwater robot reaches the plurality of target fiber grating sensors; A relative position calculation module, configured to calculate the relative position of the underwater robot relative to the distributed optical fiber sensing network based on the time data and an arrival time difference algorithm; The absolute position calculation module is used to obtain the absolute coordinates of the distributed optical fiber sensing network in the global coordinate system, and calculate the absolute position of the underwater robot according to the relative position and the absolute coordinates.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and a real-time positioning program for an underwater robot based on distributed optical fiber stored on the memory and executable on the processor. When the real-time positioning program for the underwater robot based on distributed optical fiber is executed by the processor, the steps of the real-time positioning method for the underwater robot based on distributed optical fiber according to any one of claims 1-7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a real-time positioning program for an underwater robot based on distributed optical fiber. When the real-time positioning program for the underwater robot based on distributed optical fiber is executed by a processor, the steps of the real-time positioning method for the underwater robot based on distributed optical fiber according to any one of claims 1-7 are implemented.

Images