Unidirectional communication UUV rapid iteration positioning and speed measuring method

Abstract

The invention provides a UUV rapid iteration positioning and speed measuring method based on one-way communication, and relates to the technical field of acoustic positioning. The method comprises the specific implementation steps that unknown UUV nodes acquire known information through one-way communication with anchor nodes, a ranging equation is constructed, a linear-nonlinear iterative optimization algorithm is executed according to the known information, and coordinate data and speed data of the unknown UUV nodes are updated according to the result of the algorithm. According to the technical scheme, rapid positioning and speed measurement of the unknown UUV node can be completed only through one-way communication, the exposure risk of the unknown UUV node is reduced, and the accuracy of positioning and speed measurement is improved through the linear-nonlinear iterative optimization algorithm.

Description

Technical Field

[0001] This disclosure relates to the field of acoustic positioning technology, and in particular to a method for rapid iterative positioning and velocity measurement of UUVs using one-way communication. Background Technology

[0002] With the gradual depletion of traditional terrestrial resources and the increasing difficulty of their development, human demand for the exploration, development, and sustainable utilization of the ocean continues to grow. Deep-sea oil and gas exploration, seabed mining, and the utilization of marine renewable energy have all become important components of the resource strategies of many countries. Developing advanced marine exploration, communication, and navigation technologies to achieve efficient, precise, and sustainable development of marine resources has become a focal point of international technological competition. Against this backdrop, unmanned underwater vehicles (UUVs), as key technological equipment, have significantly promoted the development of capabilities in marine observation, resource exploration, and underwater operations. However, precise underwater positioning of UUVs remains a key challenge in marine technology. Traditional positioning methods typically rely on inertial navigation systems (INS), acoustic positioning systems, and buoy-assisted GPS combinations. Inertial navigation autonomously calculates position using gyroscopes and accelerometers, offering high accuracy in the short term, but errors accumulate over time, requiring periodic calibration; significant position drift occurs during long-endurance missions.

[0003] Acoustic positioning methods mainly include long baseline (LBL), short baseline (SBL), and ultra-short baseline (USBL) systems. These systems utilize acoustic beacons deployed at known locations on the seabed or surface to achieve positioning by measuring the propagation time or phase difference of acoustic signals. While offering high accuracy, these systems are complex to deploy, costly, and have limited coverage. Furthermore, multi-beacon coordination requires sophisticated aquatic environmental conditions. In addition, some applications employ GPS buoy-assisted positioning, where UUVs periodically surface to obtain their absolute position via GPS, thus correcting inertial navigation errors. However, this surfacing process increases energy consumption and exposure risk, and its real-time performance is relatively poor.

[0004] The main limitations of these traditional methods can be summarized as follows: reliance on external infrastructure (such as acoustic beacons), difficulty in achieving high-precision autonomous positioning in unknown or open waters; accumulation of multi-source errors over time, resulting in limited system robustness; and frequent surfacing or reliance on surface support units reducing stealth and operational efficiency. Furthermore, traditional acoustic positioning is highly sensitive to the underwater acoustic environment and is susceptible to multipath effects, noise, and propagation delays.

[0005] To overcome the aforementioned limitations, UUV positioning methods have shown new development trends in recent years. On the one hand, more tightly integrated navigation systems are being widely used, such as combining inertial navigation with Doppler logs (DVL), underwater acoustic ranging, geomagnetic matching, and gravity field-assisted navigation technologies. Algorithms like Kalman filtering are used to achieve deep fusion of multi-sensor information, significantly suppressing error divergence. On the other hand, cooperative positioning technologies based on single anchor nodes or moving reference nodes are maturing. These technologies utilize a small number of surface or underwater reference nodes to achieve positioning information transmission and calibration through time-series ranging and motion estimation, reducing system deployment complexity. Furthermore, researchers are beginning to explore distributed positioning based on underwater acoustic communication, cross-domain cooperative positioning (e.g., using aerial or surface unmanned platforms for assistance), and introducing new methods such as learning methods and environmental feature matching to improve positioning adaptability in GPS-denied environments.

[0006] Therefore, there is an urgent need in the existing technology for a rapid UUV positioning method that can be completed using only a single anchor node, is not affected by the accumulation of speed errors over a long period of time, and only requires one-way communication. Summary of the Invention

[0007] Firstly, this disclosure provides a method for rapid iterative positioning and velocity measurement of UUVs using unidirectional communication, including:

[0008] The anchor node sends ranging sound waves to the unknown UUV node at a preset ranging time interval, including the sending time information as well as its own horizontal position information, velocity information and depth information at that time, until the preset number of transmissions N is reached;

[0009] The unknown UUV node receives and parses the ranging sound wave to obtain the information contained in the ranging sound wave, and records the reception time information and its own depth information at that time.

[0010] The unknown UUV node obtains its distance information from the anchor node based on the transmission time information, the reception time information, and the underwater sound speed;

[0011] Unknown UUV nodes acquire their own velocity information and construct ranging equations;

[0012] The unknown UUV node executes a linear-nonlinear iterative optimization algorithm based on the ranging equation and known information to suppress the influence of errors in the known information on coordinate calculation and correct its own velocity information. It then uses the corrected velocity information to achieve iterative optimization. After meeting the preset conditions, it updates its own coordinate data and velocity data to complete positioning and velocity measurement.

[0013] Secondly, this disclosure provides a piecewise linear method for obtaining the velocity magnitude information of unknown UUV nodes, including:

[0014] The anchor node remains stationary and sends M channels of velocity measurement sound waves containing transmission time information to the unknown UUV node at preset velocity measurement time intervals; where M is a positive integer greater than or equal to 3.

[0015] An unknown UUV node receives M channels of velocity measurement sound waves and records the reception time information. Based on the transmission and reception time information of two adjacent channels of velocity measurement sound waves, and combined with the underwater sound speed, M velocity measurement equations are obtained.

[0016] An unknown UUV node performs first-order difference processing on M velocity measurement equations to obtain M-1 velocity magnitude information. It then averages the M-1 velocity magnitude information to obtain its own velocity magnitude information.

[0017] The content described in this section is not intended to identify key or important features of the embodiments of this disclosure, nor does it constitute a limitation on the scope of this disclosure.

[0018] Other features of this disclosure will be described in detail in the following description to aid understanding. Attached Figure Description

[0019] Figure 1 This is a schematic diagram illustrating a specific application scenario of an embodiment of this disclosure;

[0020] Figure 2 This is a flowchart illustrating a one-way communication method for rapid iterative positioning and velocity measurement of UUVs according to an embodiment of this disclosure.

[0021] Figure 3 This is a schematic diagram illustrating the positional relationship between the anchor node and the unknown UUV node during the positioning and speed measurement process in one embodiment of this disclosure;

[0022] Figure 4 This is a flowchart illustrating a linear-nonlinear iterative optimization algorithm in one embodiment of this disclosure;

[0023] Figure 5 This is a schematic flowchart of the broken line method in one embodiment of this disclosure;

[0024] Figure 6 This is a schematic diagram showing the positional relationship between the anchor node and the unknown UUV node in a broken line method according to an embodiment of this disclosure. Detailed Implementation

[0025] The present disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments provided below are merely exemplary. Furthermore, for the sake of brevity and clarity, common knowledge has been omitted from the description of the embodiments below.

[0026] In this document, terms such as "first," "second," and "third" are used only to distinguish identical or similar descriptive objects and are not intended to limit the specific order or sequence of the described objects, nor are they used to limit the importance of the described objects. At the same time, in order to enable those skilled in the art to clearly understand the technical solutions provided in this disclosure, expressions such as "red," "yellow," and "blue" and the specific colors in the accompanying drawings are also used only to distinguish identical or similar descriptive objects and do not represent the color attributes possessed by the descriptive objects when this solution is actually deployed.

[0027] Figure 1 The illustration shows an application scenario of an embodiment of this disclosure. The anchor node performs satellite navigation (which may be a Beidou satellite) by surfacing, and then communicates one-way with an unknown UUV node. The unknown UUV node integrates all known information and executes a linear-nonlinear iterative optimization algorithm. Based on the output of the algorithm, it updates its own coordinate data and velocity data to complete positioning and speed measurement.

[0028] The following describes a method for rapid iterative positioning and velocity measurement of UUVs using one-way communication, based on an embodiment of this disclosure. Figure 2 As shown, the specific steps include:

[0029] Step S201: The anchor node sends a ranging sound wave to the unknown UUV node at a preset ranging time interval, including the sending time information and its own horizontal position information, velocity information and depth information at that time, until the preset number of transmissions N is reached.

[0030] N is a positive integer greater than or equal to 1.

[0031] The time information is provided by atomic clocks deployed at the anchor nodes, and the depth information is provided by depth gauges deployed at the anchor nodes.

[0032] The anchor node obtains its horizontal position and velocity information by surfacing and using satellite navigation. The velocity information of the anchor node includes the magnitude and direction of the velocity.

[0033] Step S202: The unknown UUV node receives and parses the ranging sound wave to obtain the information contained in the ranging sound wave, and records the reception time information and its own depth information at that time.

[0034] Depth information is provided by a depth meter deployed at the unknown UUV node, and the receiving time information is provided by an atomic clock deployed at the unknown UUV node.

[0035] It should be understood that the atomic clocks of the anchor node and the unknown UUV node are pre-calibrated to ensure that their times are consistent and accurate.

[0036] Step S203: The unknown UUV node obtains its distance information from the anchor node based on the transmission time information, the reception time information, and the underwater sound speed.

[0037] Step S204: The unknown UUV node acquires its own velocity information and constructs a ranging equation.

[0038] Since the speed of the unknown UUV node is within the preset typical cruising speed range, and the positioning and speed measurement time is relatively short when the technical solution of this disclosure is actually deployed, the motion state of the unknown UUV node can be approximated as uniform linear motion.

[0039] The speed information of unknown UUV nodes includes speed magnitude information and speed direction information. The speed magnitude information is provided by the inertial navigation deployed on the unknown UUV nodes, and the speed direction information is provided by the gyroscopes deployed on the unknown UUV nodes.

[0040] Step S205: The unknown UUV node executes a linear-nonlinear iterative optimization algorithm based on the ranging equation and known information to suppress the influence of errors in the known information on coordinate calculation and correct its own velocity information. It then uses the corrected velocity information to achieve iterative optimization. After meeting the preset conditions, it updates its own coordinate data and velocity data to complete the positioning and velocity measurement.

[0041] The technical solution provided in this disclosure requires only one anchor node, and this anchor node communicates unidirectionally with the unknown UUV node. Subsequently, the unknown UUV node executes a linear-nonlinear iterative optimization algorithm locally to update its coordinate and velocity data, thereby achieving positioning and velocity measurement. Unidirectional communication is not only faster but also avoids the unknown UUV node from surfacing, reducing the risk of its exposure.

[0042] Figure 3 This is a schematic diagram illustrating the positional relationship between the anchor node and the unknown UUV node during the positioning and velocity measurement process in this embodiment. Figure 3 Further explanation of one-way communication will aid in understanding.

[0043] Assumption The coordinates of the anchor node and the unknown UUV node at time [time] are respectively and It should be understood that coordinates are composed of their respective horizontal and depth information.

[0044] The horizontal position information is obtained through satellite positioning. The horizontal position information is an unknown quantity;

[0045] At any given moment, the anchor node packages its own horizontal position information, depth information, velocity information, and transmission time information, modulates them into a ranging sound wave, and sends it to the unknown UUV node.

[0046] It should be noted that the modulation process is very short and can be ignored; the transmission time of the sound wave is the [specific information]. .

[0047] At a certain time (receiving time information), the unknown UUV node receives and analyzes the ranging acoustic wave. At this point, the coordinates of the unknown UUV node are: , The propagation time of the ranging sound wave is [missing information], and the anchor node is [missing information]. The coordinates of the moment and the unknown UUV node are in The coordinate difference vector at time t is denoted as The magnitude of this difference vector represents the distance information between the unknown UUV node and the anchor node, denoted as... , The underwater sound speed is recorded simultaneously by an unknown UUV node. The depth information of the moment itself.

[0048] After a preset distance measurement time interval ,exist time( The anchor node then packages its horizontal position information, depth information, velocity information, and transmission time information into a ranging sound wave and sends it to the unknown UUV node.

[0049] At a certain time (receiving time information), the unknown UUV node receives and analyzes the ranging acoustic wave. At this time, the coordinates of the unknown UUV node are: , The propagation time of the ranging sound wave is [missing information], and the anchor node is [missing information]. The coordinates of the moment and the unknown UUV node are in The coordinate difference vector at time t is denoted as The magnitude of this difference vector represents the distance information between the unknown UUV node and the anchor node, denoted as... Unknown UUV nodes record simultaneously The depth information of the moment itself.

[0050] After executing the above process N times, the unknown UUV node will store the protocol interaction information obtained during the execution of the communication protocol in its local storage.

[0051] The following is combined Figure 3 Further explanation of the distance measurement equations will aid in understanding.

[0052] The distance measurement equation is expressed as follows:

[0053]

[0054]

[0055]

[0056] ...

[0057]

[0058] Combination Figure 3 It can be known that:

[0059] Indicates from Time's up The displacement vector of the anchor node at time t is expressed as:

[0060]

[0061] For unknown UUV nodes The displacement vector within is expressed as:

[0062]

[0063] like and The expression for equivectors can be found in [reference]. Figure 5 Equations 5 and 6 are obtained and will not be repeated here.

[0064] Ranging constraints also include the following physical quantities defined by the unknown UUV nodes:

[0065]

[0066]

[0067] in,

[0068]

[0069]

[0070] in,

[0071] For anchor nodes at Time to The magnitude of the displacement velocity within a given moment;

[0072] For anchor nodes at Time to The direction of displacement velocity within a given moment;

[0073] The magnitude of the displacement velocity of the unknown UUV node during the entire positioning and velocity measurement process;

[0074] The direction of displacement velocity of the unknown UUV node during the entire positioning and velocity measurement process.

[0075] It should be understood that the ranging equation defines the precise geometric relationship between the anchor node and the unknown UUV node. The linear-nonlinear iterative optimization algorithm provided in this disclosure aims to start from known information with errors, suppress the influence of errors as much as possible, and approximate the precise geometric relationship to obtain relatively accurate coordinate data and velocity data of the unknown UUV node itself, so as to achieve positioning and speed measurement.

[0076] Figure 4 This is a flowchart illustrating the linear-nonlinear iterative optimization algorithm in this embodiment, as shown below. Figure 4 As shown, the specific steps include:

[0077] Step S401: Construct a linear matrix model of the relative position vectors of the anchor node and the unknown UUV node, solve it using the overall least squares method, and obtain the linear result of the relative position vectors.

[0078] like Figure 3 As shown, the relative position vector specifically refers to the difference vector between the anchor node position at the time of transmission of the first ranging acoustic wave and the unknown UUV node position at the time of reception.

[0079] The linear matrix model expression is:

[0080]

[0081]

[0082]

[0083]

[0084] in,

[0085]

[0086]

[0087] It should be noted that the known information obtained during the aforementioned communication process contains errors, the main sources of which include:

[0088] Satellite positioning introduces errors, therefore, the speed information of anchor nodes is inaccurate;

[0089] Because the speed of sound underwater is not a constant value in real-world environments, errors will occur when calculating distance information.

[0090] The error of inertial navigation accumulates as the unknown UUV node travels underwater, therefore, the speed information of the unknown UUV node before correction will contain errors;

[0091] Gyroscopes produce errors, approximately 0.05°, therefore, the velocity and direction information of unknown UUV nodes will contain errors;

[0092] Although depth gauges may have very small errors, in the implementation scenario of the technical solution disclosed herein, depth gauge errors do not play a dominant role and can be ignored.

[0093] As can be seen from the aforementioned formula, the above-mentioned error exists in the coefficient matrix. and observation matrix middle.

[0094] In existing technical solutions, solving the above linear matrix model mostly employs ordinary least squares or Kalman filtering methods, all of which assume that the error exists only in the observation matrix. In this case, the coefficient matrix is ​​ignored. The influence of mean square error.

[0095] Therefore, the total least squares method is used to solve the linear matrix model. The total least squares method establishes a more complete error model and coordinates the handling of the coefficient matrix. and observation matrix The mean square error is used to suppress the influence of the mean square errors of the two matrices in a balanced manner, thus obtaining the relative position vector. The estimated value.

[0096] Step S402: Construct a first nonlinear least squares model for the relative position vector. Using the linear result of the relative position vector as the initial value, solve the model using the LM method to obtain the optimized result of the relative position vector. Based on the optimized result of the relative position vector, obtain the predicted coordinates.

[0097] The first nonlinear least squares model expression is:

[0098]

[0099] Using the estimated value of the relative position vector obtained in step S401 as the initial value, the Levenberg-Marquardt method (LM method) is used to iteratively solve Equation 17. This nonlinear optimization process can correct the error influence that still exists in the linear result of the relative position vector, and thus obtain the optimized result of the relative position vector with higher estimation accuracy.

[0100] Combination Figure 3 Based on the optimization results of the relative position vector, , and unknown UUV nodes The predicted coordinates can be obtained from the depth information at each time point. .

[0101] Step S403: Define a new unknown vector with its own coordinates and velocity magnitude, construct a second nonlinear least squares model with respect to the new unknown vector, use the predicted coordinates and its own velocity magnitude information as initial values, and solve the model using the LM method to obtain the optimized results of its own predicted coordinates and velocity magnitude information.

[0102] The expression for the new unknown vector is: .

[0103] The expression for the second nonlinear least squares model is:

[0104]

[0105] Step S403 aims to further correct the impact of errors and obtain more accurate predicted coordinates and velocity information of unknown UUV nodes.

[0106] Furthermore, from the perspective of positioning, simply stacking the first nonlinear least squares model may cause overfitting and thus affect robustness; from the perspective of speed measurement, the solution result of the new unknown vector obtained in step S403 can correct the speed information.

[0107] Step S404: Determine whether the preset conditions are met; if the determination is no, proceed to step S405; if the determination is yes, proceed to step S406.

[0108] Step S405: Update the self-velocity information and the coefficients related to the self-velocity information in the linear matrix model with the optimization results of the velocity magnitude information. Then, sequentially solve the optimization results of the relative position vector, predicted coordinates, and predicted coordinate information and velocity magnitude information. Finally, make a judgment again.

[0109] Step S406: Output the optimized results of the predicted coordinates and velocity magnitude information. The positioning and velocity measurement algorithm has been completed.

[0110] It should be understood that after the algorithm finishes execution, the optimized result of the predicted coordinates output is... By constantly knowing the coordinates of the unknown UUV node, and updating its own speed information with the optimized results of the output speed magnitude information, a more accurate speed of the unknown UUV node can be obtained.

[0111] According to the aforementioned formula, there exists such a formula in the linear matrix model. , The coefficients related to the speed and magnitude information of the unknown UUV nodes are obtained. In step S405, these coefficients are updated with the more accurate speed and magnitude information of the unknown UUV nodes obtained in step S403.

[0112] In one embodiment of this disclosure, the preset condition is that the number of times the cascaded architecture (steps S401-S403) in the algorithm is executed is equal to 2.

[0113] It should be understood that the above-mentioned preset conditions are termination conditions limited from the dimension of the number of times the algorithm is executed. In the actual deployment of the technical solution disclosed herein, the termination conditions can also be limited from the dimension of the accuracy of the algorithm result (output accuracy of Equation 18) as needed.

[0114] Since the error of inertial navigation accumulates as the unknown UUV node travels underwater, when the unknown UUV node travels underwater for more than a preset threshold (the unknown UUV node can detect whether it has exceeded the threshold through its own navigation log), the speed information it provides will have too large an error, thus affecting the coordinate and speed data finally calculated by the algorithm.

[0115] Therefore, the speed information of unknown UUV nodes can be obtained using the broken line method.

[0116] One embodiment of this disclosure provides a piecewise linear method for obtaining the velocity information of unknown UUV nodes. Figure 5 Its flowchart is as follows: Figure 5 As shown, the broken line method specifically includes the following steps:

[0117] Step S501: The anchor node remains stationary and sends M-channel speed measurement sound waves containing transmission time information to the unknown UUV node at a preset speed measurement time interval.

[0118] Where M is a positive integer greater than or equal to 3.

[0119] Step S502: The unknown UUV node receives M channels of velocity measurement sound waves and records the reception time information. Based on the transmission and reception time information of two adjacent channels of velocity measurement sound waves, M velocity measurement equations are obtained by combining the underwater sound speed.

[0120] Step S503: The unknown UUV node performs first-order difference processing on the M velocity measurement equations to obtain M-1 velocity magnitude information, and averages the M-1 velocity magnitude information to obtain its own velocity magnitude information.

[0121] It should be understood that, in the actual deployment of the technical solution disclosed herein, the process of estimating the speed of unknown UUV nodes using the broken line method is completed before the aforementioned positioning and speed measurement process.

[0122] After the polyline method is executed, in the aforementioned step S303, it is no longer necessary to obtain the speed information of the unknown UUV node from the inertial navigation.

[0123] Figure 6 This is a schematic diagram illustrating the positional relationship between anchor nodes and unknown UUV nodes during the execution of the polyline method, combined with... Figure 6 To aid understanding, we will further explain the broken line method.

[0124] In one embodiment of this disclosure, M=3 is taken. To distinguish it from the previous text, it is used here. to Indicates the time.

[0125] The anchor node remains stationary, from Starting at a certain time interval, the speed measurement will begin at a preset time interval. Three velocity-measuring sound waves were emitted toward the unknown UUV node.

[0126] Unknown UUV nodes at , and The velocity-measuring sound waves are received continuously. Based on the transmission and reception times of the first and second ranging sound waves, and combined with the underwater sound speed, the following velocity-measuring equation is obtained:

[0127]

[0128]

[0129] Subtracting equation 20 from equation 19, we get:

[0130]

[0131] like Figure 6 As shown, the transmission paths of two adjacent ranging sound waves and the movement path of the unknown UUV node form a triangular relationship, from which we can obtain:

[0132]

[0133] In the implementation scenarios of this disclosed technical solution, compared to In other words, and It is a very large value, therefore ,and then Therefore, equation 22 can be expressed as:

[0134]

[0135] Similarly, based on the second and third ranging sound waves, a... The value is obtained by averaging these two values. , for use in the aforementioned positioning and speed measurement process.

[0136] The technical solution provided in this disclosure utilizes the iterative interaction of linear least squares and nonlinear least squares to gradually reduce positioning and speed measurement errors using known information.

[0137] When an unknown UUV node is navigating underwater for an extended period, the inertial navigation system may have excessive errors due to the lack of calibration over a long time. This disclosure provides a broken line method to estimate the speed before the positioning and speed measurement process.

[0138] In this disclosed technical solution, only one anchor node is needed, and the unknown UUV node only needs to receive the signal and process it itself, which can reduce the upward movement of the unknown UUV node and ensure its concealment.

[0139] Any changes made to the above embodiments by those skilled in the art without departing from the true spirit and scope of this disclosure should be included within the scope of protection covered by the claims. The scope of protection claimed by this invention is limited only by the claims.

Claims

1. A method for rapid iterative positioning and velocity measurement of UUVs using one-way communication, characterized in that, The method is executed by an anchor node and an unknown UUV node, including: Anchor nodes transmit ranging acoustic waves to unknown UUV nodes at preset ranging time intervals, including the transmission time information and their own horizontal position, velocity, and depth information at that moment, until a preset number of transmissions N is reached; where N is a positive integer greater than or equal to 1; the transmission time information is provided by an atomic clock deployed on the anchor node; the depth information is provided by a depth gauge deployed on the anchor node; the horizontal position and velocity information are obtained through satellite navigation when the anchor node surfaces, and the velocity information of the anchor node includes velocity magnitude and velocity direction information; An unknown UUV node receives and analyzes the ranging acoustic wave to obtain the information contained in the ranging acoustic wave, and records the reception time information and its own depth information at that time; wherein, the depth information is provided by a depth gauge deployed on the unknown UUV node; and the reception time information is provided by an atomic clock deployed on the unknown UUV node. The unknown UUV node obtains its distance information from the anchor node based on the transmission time information, reception time information, and underwater sound speed; The unknown UUV node acquires its own speed information and constructs a ranging equation; wherein, the speed of the unknown UUV node during the positioning and speed measurement process is within a preset typical cruising speed range, and its motion is approximately uniform linear motion; the speed information of the unknown UUV node includes speed magnitude information and speed direction information, wherein the speed magnitude information is provided by the inertial navigation deployed on the unknown UUV node, and the speed direction information is provided by the gyroscope deployed on the unknown UUV node; The unknown UUV node executes a linear-nonlinear iterative optimization algorithm based on the ranging equation and known information to suppress the influence of errors in the known information on coordinate calculation and correct its own velocity information. It then uses the corrected velocity information to perform iterative optimization. After meeting preset conditions, it updates its own coordinate and velocity data to complete positioning and velocity measurement. The linear-nonlinear iterative optimization algorithm includes: A linear matrix model of the relative position vectors of the anchor node and the unknown UUV node is constructed and solved by the overall least squares method to obtain the linear result of the relative position vector; wherein, the relative position vector is defined as the difference vector between the position of the anchor node at the time of transmission of the first ranging sound wave and the position of the unknown UUV node at the time of reception. A first nonlinear least squares model is constructed for the relative position vector. The linear result of the relative position vector is used as the initial value, and the LM method is used to solve it to obtain the optimized result of the relative position vector. The predicted coordinates are obtained based on the optimized result of the relative position vector. A new unknown vector is defined with its own coordinates and velocity magnitude. A second nonlinear least squares model is constructed with the new unknown vector. The predicted coordinates and its own velocity magnitude information are used as initial values. The LM method is used to solve the model and obtain the optimized result of its own predicted coordinates and velocity magnitude information. If the preset conditions are not met, the coefficients related to the linear matrix model are updated based on the optimization results of the self-velocity information, and iterative optimization is performed until the preset conditions are met.

2. The method according to claim 1, characterized in that, When the unknown UUV node's underwater travel time exceeds a preset threshold, its speed information can be obtained using a broken-line method before the positioning and speed measurement process, including: The anchor node remains stationary and sends M channels of velocity measurement sound waves containing transmission time information to the unknown UUV node at preset velocity measurement time intervals; where M is a positive integer greater than or equal to 3. An unknown UUV node receives the M channels of velocity-measuring sound waves and records the reception time information. Based on the transmission and reception time information of two adjacent channels of velocity-measuring sound waves, and combined with the underwater sound speed, M velocity-measuring equations are obtained. The unknown UUV node performs first-order difference processing on the M velocity measurement equations to obtain M-1 velocity magnitude information, and averages the M-1 velocity magnitude information to obtain its own velocity magnitude information.

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