A buoy cooperative underwater positioning system based on multi-path suppression and sound velocity profile correction

Abstract

The application provides a buoy cooperative underwater positioning system based on multipath suppression and sound velocity profile correction, and has the characteristics that the system comprises an intelligent buoy network module, a sound velocity measurement module, a signal suppression module and a cooperative positioning module; the intelligent buoy network module is used for constructing a positioning reference network through a plurality of buoys distributed in space in a target water area; the sound velocity measurement module is used for obtaining sound velocity distribution information of an underwater environment; the signal suppression module is used for identifying and suppressing multipath propagation interference in an underwater acoustic channel; and the positioning solution module is used for obtaining an accurate three-dimensional space position of an underwater target; through the cooperative positioning mechanism of multipath inversion suppression and trajectory prediction constraint, the underwater target positioning system achieves the technical effects of high positioning accuracy, strong stability and good robustness in a complex underwater acoustic environment.

Description

Technical Field

[0001] This invention relates to the field of underwater positioning system technology, and in particular to a buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction. Background Technology

[0002] With the widespread application of underwater unmanned platforms, marine exploration, and underwater operation equipment, the demand for high-precision positioning and continuous tracking of underwater targets is increasing. However, due to the complex propagation characteristics of underwater acoustic channels, underwater positioning generally faces problems such as severe multipath propagation interference, non-uniform spatial distribution of sound velocity, and frequent environmental changes, resulting in large ranging errors and unstable positioning results, especially in typical marine environments such as shallow water and high reflection rates. Existing underwater positioning technologies mostly rely on single feature discrimination or fixed models for processing, making it difficult to simultaneously ensure positioning accuracy and robustness. There is an urgent need for a positioning technology that can comprehensively consider the characteristics of underwater acoustic propagation and the continuity of target movement to improve the reliability and engineering applicability of underwater target positioning.

[0003] A review of publicly available technical solutions reveals that CN114666729B proposes a method for compensating underwater acoustic communication errors in collaborative navigation and positioning of underwater cluster UUVs. This method includes the following steps: establishing a multi-input multi-output dynamic neural network topology; designing a neuron number growth-decay mechanism; and considering a parameter training method for a dynamic fuzzy neural network. This aims to ensure the accuracy of predicting underwater acoustic ranging channel propagation delay and ranging error during the prediction stage. This invention combines fuzzy logic theory, integrating prior expert knowledge and system information into the neural network to construct input-output relationships. Simultaneously, it introduces a dynamic network structure mechanism to adaptively adjust neuron nodes during neural network training, ensuring the compactness of the fuzzy neural network structure. This results in a novel neural network prediction model for real-time, self-learning, self-organizing, and adaptive underwater acoustic ranging channel propagation delay and ranging error, further improving the accuracy and reliability of multi-UUV collaborative navigation and positioning. However, this scheme uses a post-hoc compensation method for ranging errors, relying on extensive historical data training. Its generalization ability is limited when the environment changes abruptly or training samples are lacking, and it does not fundamentally address the physical mechanisms of sound speed variation and multipath interference. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of current systems by proposing a buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction.

[0005] The present invention adopts the following technical solution:

[0006] A buoy-cooperative underwater positioning system based on multipath suppression and sound velocity profile correction, the system comprising an intelligent buoy network module, a sound velocity measurement module, a signal suppression module, and a cooperative positioning module.

[0007] The intelligent buoy network module is used to construct a positioning reference network using multiple buoys spatially distributed in the target water area; the sound velocity measurement module is used to obtain sound velocity distribution information of the underwater environment; the signal suppression module is used to identify and suppress multipath propagation interference in the underwater acoustic channel; and the positioning solution module is used to obtain the precise three-dimensional spatial position of the underwater target.

[0008] The intelligent buoy network module includes multiple buoy nodes set at predetermined locations in the target water area. Each buoy node includes an acoustic signal transceiver unit, a self-positioning unit, and a buoy communication unit. The acoustic signal transceiver unit is used to periodically transmit bidirectional ranging signals with the underwater target and record the timestamp and amplitude information of the received signals. The self-positioning unit is used to obtain the buoy's own position in real time via GPS. The buoy communication unit is used to complete wireless data transmission between buoys and between buoys and the control center.

[0009] Furthermore, the sound velocity measurement module includes a sensing and monitoring unit, a sound velocity calculation unit, a profile modeling unit, and a path integration unit. The sensing and monitoring unit is located at the buoy position and is used to monitor the physical influence data of sound velocity at different underwater depths. The physical influence data of sound velocity includes conductivity, temperature, and depth parameters. The sound velocity calculation unit is used to output a sound velocity sequence at discrete depth points based on the physical influence data of sound velocity. The profile modeling unit is used to construct an interpolation fitting model of the underwater sound velocity profile by combining the sound velocity sequence of discrete depth points. The path integration unit is used to calculate the theoretical propagation time of the sound wave along a specific path based on the given start point, end point, and the interpolation fitting model of the sound velocity profile.

[0010] Furthermore, the signal suppression module includes a signal preprocessing unit, a pulse detection unit, a feature extraction unit, and a multipath discrimination unit. The signal preprocessing unit is used to perform filtering preprocessing on the two-way ranging signal. The pulse detection unit is used to detect all pulse peaks exceeding a preset threshold from the preprocessed signal and extract the arrival time of each pulse signal. The feature extraction unit is used to extract the time delay parameter and amplitude parameter of each detected pulse signal and calculate the signal-to-noise ratio. The multipath discrimination unit is used to identify and analyze the direct wave pulse between the buoy and the underwater target by combining the detected pulse signals and suppress multipath echo interference.

[0011] Furthermore, the cooperative positioning module includes a distance calculation unit, a cooperative positioning unit, and a trajectory prediction unit. The distance calculation unit is used to analyze and calculate the distance between the buoy and the underwater target based on the arrival delay of the direct path pulse signal identified by the multipath identification unit, combined with the interpolation fitting model of the sound speed profile. The cooperative positioning unit is used to receive the calculated distances and buoy position coordinates of multiple buoy nodes, and obtain the precise three-dimensional position coordinates of the underwater target through analysis and iteration. The trajectory prediction unit is used to establish a motion state model of the underwater target and output the motion position prediction of the underwater target.

[0012] Furthermore, the specific workflow of the multipath discrimination unit is as follows:

[0013] S11: For a certain buoy, obtain its position information and the estimated position information of the underwater target, wherein the estimated position information of the underwater target is the positioning result of the underwater target at the previous moment provided by the cooperative positioning unit;

[0014] S12: Obtain all pulse signal sequences and their corresponding time delay and amplitude parameters. For any two pulse signals, calculate their time delay difference.

[0015] ;

[0016] in, For the first The pulse relative to the first The time delay difference of each pulse, and The first The pulse and the first The arrival time delay of each pulse; establishing a theoretical model of the time delay difference between sea surface reflection and direct wave:

[0017] ;

[0018] in, The underwater target depth is At that time, the theoretical time delay difference between the sea surface reflection path and the direct path; This represents the straight-line path between the buoy's position and the estimated position of the underwater target. This represents the return path between the buoy's position reflected from the sea surface and the estimated position of the underwater target. Points on the path The sound speed value at that location is obtained through an interpolation fitting model of the underwater sound speed profile;

[0019] S13: Combine any two pulse signals into a pulse pair, iterate through all pulse pairs, and for each pair, satisfy... The pulse pair combination is used to invert the corresponding signal source depth through a time delay difference theoretical model:

[0020] ;

[0021] in, For pulse pairs The depths of the signal sources are obtained by inversion using the time delay difference theoretical model, and the deviations between the depths of each signal source and the initial estimated depths are calculated:

[0022] ;

[0023] in, For pulse pairs The deviation between the corresponding signal source and the initial estimated depth, The initial estimated depth of the underwater target is obtained through step S1;

[0024] S14: For each pulse pair, calculate its overall matching confidence:

[0025] ;

[0026] in, For pulse pairs The corresponding signal source is used as the matching confidence level for the underwater target. This is the amplitude weighting factor, with a value range of... ; Amplitude matching degree characterizes the degree of amplitude matching between the pulse pair and the underwater target; Depth matching degree characterizes the degree of depth matching between the pulse pair and the underwater target;

[0027] S15: After completing the comprehensive matching confidence calculation for all pulse pairs, traverse all pulse pairs, select the pulse pair with the highest matching confidence as the optimal pulse pair, and determine the direct wave pulse of the underwater target based on the relationship between the arrival delays of the two pulse signals in the pulse pair.

[0028] The beneficial effects achieved by this invention are:

[0029] This invention introduces a multipath time delay inversion mechanism based on sound velocity profile constraints to achieve reliable identification of direct wave pulses, effectively reducing the impact of multipath propagation on ranging accuracy. At the same time, it introduces underwater target trajectory prediction results as prior constraints into the cooperative positioning solution process, and combines them with an adaptive weight update mechanism to significantly improve the stability, continuity, and robustness of multi-buoy cooperative positioning in complex underwater acoustic environments, thereby enhancing the overall accuracy and engineering applicability of underwater target three-dimensional positioning. Attached Figure Description

[0030] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0031] Figure 1 This is a schematic diagram of the overall modules of the present invention.

[0032] Figure 2 This is a schematic diagram of the workflow of the multipath discrimination unit of the present invention.

[0033] Figure 3 This is a schematic diagram comparing the positioning error index of the present invention and the traditional solution.

[0034] Figure 4 This is a schematic diagram comparing the effects of the present invention and the traditional solution on various comprehensive indicators. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention. Other systems, methods, and / or features of this embodiment will become apparent to those skilled in the art after reviewing the following detailed description. It is intended that all such additional systems, methods, features, and advantages are included within this specification, are included within the scope of the present invention, and are protected by the appended claims. Further features of the disclosed embodiments are described in the following detailed description, and these features will be apparent from the following detailed description.

[0036] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0037] Example 1:

[0038] like Figure 1 , Figure 2 As shown, this embodiment provides a buoy cooperative underwater positioning system based on multipath suppression and sound velocity profile correction. The system includes an intelligent buoy network module, a sound velocity measurement module, a signal suppression module, and a cooperative positioning module.

[0039] The intelligent buoy network module is used to construct a positioning reference network using multiple buoys spatially distributed in the target water area; the sound velocity measurement module is used to obtain sound velocity distribution information of the underwater environment; the signal suppression module is used to identify and suppress multipath propagation interference in the underwater acoustic channel; and the positioning solution module is used to obtain the precise three-dimensional spatial position of the underwater target.

[0040] The intelligent buoy network module includes multiple buoy nodes set at predetermined locations in the target water area. Each buoy node includes an acoustic signal transceiver unit, a self-positioning unit, and a buoy communication unit. The acoustic signal transceiver unit is used to periodically transmit two-way ranging signals with the underwater target and record the timestamp and amplitude information of the received signals. The self-positioning unit is used to obtain the buoy's own position in real time via GPS. The buoy communication unit is used to complete wireless data transmission between buoys and between buoys and the control center.

[0041] The sound velocity measurement module includes a sensing and monitoring unit, a sound velocity calculation unit, a profile modeling unit, and a path integration unit. The sensing and monitoring unit is located at the buoy position and is used to monitor the physical influence data of sound velocity at different underwater depths. The physical influence data of sound velocity includes conductivity, temperature, and depth parameters. The sound velocity calculation unit is used to output a sound velocity sequence at discrete depth points based on the physical influence data of sound velocity. The profile modeling unit is used to construct an interpolation fitting model of the underwater sound velocity profile by combining the sound velocity sequence of discrete depth points. The path integration unit is used to calculate the theoretical propagation time of the sound wave along a specific path based on the given start point, end point, and the interpolation fitting model of the sound velocity profile.

[0042] The signal suppression module includes a signal preprocessing unit, a pulse detection unit, a feature extraction unit, and a multipath discrimination unit. The signal preprocessing unit performs filtering preprocessing on the two-way ranging signal. The pulse detection unit detects all pulse peaks exceeding a preset threshold from the preprocessed signal and extracts the arrival time of each pulse signal. The feature extraction unit extracts the time delay and amplitude parameters of each detected pulse signal and calculates the signal-to-noise ratio. The multipath discrimination unit combines the detected pulse signals to identify and analyze the direct wave pulse between the buoy and the underwater target and suppresses multipath echo interference.

[0043] The cooperative positioning module includes a distance calculation unit, a cooperative positioning unit, and a trajectory prediction unit. The distance calculation unit is used to analyze and calculate the distance between the buoy and the underwater target based on the arrival delay of the direct path pulse signal identified by the multipath identification unit, combined with the interpolation fitting model of the sound speed profile. The cooperative positioning unit is used to receive the calculated distances and buoy position coordinates of multiple buoy nodes, and obtain the precise three-dimensional position coordinates of the underwater target through analysis and iteration. The trajectory prediction unit is used to establish a motion state model of the underwater target and output the predicted motion position of the underwater target.

[0044] Furthermore, the specific workflow of the multipath discrimination unit is as follows:

[0045] S11: For a certain buoy, obtain its position information and the estimated position information of the underwater target, wherein the estimated position information of the underwater target is the positioning result of the underwater target at the previous moment provided by the cooperative positioning unit;

[0046] S12: Obtain all pulse signal sequences and their corresponding time delay and amplitude parameters. For any two pulse signals, calculate their time delay difference.

[0047] ;

[0048] in, For the first The pulse relative to the first The time delay difference of each pulse, and The first The pulse and the first The arrival time delay of each pulse; establishing a theoretical model of the time delay difference between sea surface reflection and direct wave:

[0049] ;

[0050] in, The underwater target depth is At that time, the theoretical time delay difference between the sea surface reflection path and the direct path; This represents the straight-line path between the buoy's position and the estimated position of the underwater target. This represents the return path between the buoy's position reflected from the sea surface and the estimated position of the underwater target. Points on the path The sound speed value at that location is obtained through an interpolation fitting model of the underwater sound speed profile;

[0051] S13: Combine any two pulse signals into a pulse pair, iterate through all pulse pairs, and for each pair, satisfy... The pulse pair combination is used to invert the corresponding signal source depth through a time delay difference theoretical model:

[0052] ;

[0053] in, For pulse pairs The depths of the signal sources are obtained by inversion using the time delay difference theoretical model, and the deviations between the depths of each signal source and the initial estimated depths are calculated:

[0054] ;

[0055] in, For pulse pairs The deviation between the corresponding signal source and the initial estimated depth, The initial estimated depth of the underwater target is obtained from the estimated position information of the underwater target in step S1;

[0056] S14: For each pulse pair, calculate its overall matching confidence:

[0057] ;

[0058] in, For pulse pairs The corresponding signal source is used as the matching confidence level for the underwater target. This is the amplitude weighting factor, with a value range of... ; and For the feature extraction unit respectively, for the first The pulse and the first Amplitude parameters extracted from each pulse; Amplitude matching degree characterizes the pulse pair. The degree of amplitude matching with underwater targets; Depth matching degree characterizes the degree of depth matching between the pulse pair and the underwater target;

[0059] Furthermore, the amplitude weighting factor It can be set in the following ways:

[0060] ;

[0061] in, For the first Signal-to-noise ratio of a pulse signal For the first Signal-to-noise ratio of a pulse signal and The minimum and maximum signal-to-noise ratio thresholds are set based on engineering experience. A qualifying function is used to limit the range of values ​​a function can take. between;

[0062] Furthermore, the amplitude matching degree is calculated in the following way:

[0063] ;

[0064] Furthermore, the depth matching degree is calculated in the following way:

[0065] ;

[0066] in, The depth tolerance coefficient is set according to the uncertainty of the initial estimated depth of the underwater target, and preferably 2 to 3 times the standard deviation of the initial estimated depth of the underwater target for multiple buoys.

[0067] S15: After calculating the comprehensive matching confidence of all pulse pairs, all pulse pairs are traversed, and the pulse pair with the highest matching confidence is selected as the optimal pulse pair. Based on the arrival delay relationship between the two pulse signals in the pulse pair, the direct wave pulse of the underwater target is determined. This scheme introduces a multipath delay difference inversion mechanism based on sound velocity profile constraints to achieve physical consistency identification of direct wave pulses, effectively avoiding the misjudgment problem of traditional methods based on earliest arrival or amplitude characteristics in complex multipath environments. Simultaneously, by using the consistency between the inversion depth and the system's prior depth as the discrimination criterion, the reliability and stability of direct wave identification are significantly improved, thereby enhancing the accuracy and continuity of underwater target positioning results and strengthening the system's engineering applicability in complex underwater acoustic environments such as shallow water and multiple reflections. Example 2:

[0068] This embodiment should be understood to include at least all the features of any of the foregoing embodiments, and to further improve upon them;

[0069] This embodiment provides a buoy-cooperative underwater positioning system based on multipath suppression and sound velocity profile correction. The system includes an intelligent buoy network module, a sound velocity measurement module, a signal suppression module, and a cooperative positioning module.

[0070] The intelligent buoy network module is used to construct a positioning reference network using multiple buoys spatially distributed in the target water area; the sound velocity measurement module is used to obtain sound velocity distribution information of the underwater environment; the signal suppression module is used to identify and suppress multipath propagation interference in the underwater acoustic channel; and the positioning solution module is used to obtain the precise three-dimensional spatial position of the underwater target.

[0071] The cooperative positioning module includes a distance calculation unit, a cooperative positioning unit, and a trajectory prediction unit. The distance calculation unit is used to analyze and calculate the distance between the buoy and the underwater target based on the arrival delay of the direct path pulse signal identified by the multipath identification unit, combined with the interpolation fitting model of the sound speed profile. The cooperative positioning unit is used to receive the calculated distances and buoy position coordinates of multiple buoy nodes, and obtain the precise three-dimensional position coordinates of the underwater target through analysis and iteration. The trajectory prediction unit is used to establish a motion state model of the underwater target and output the predicted motion position of the underwater target.

[0072] Furthermore, the trajectory prediction unit incorporates the underwater target's trajectory prediction results into the calculation process of the underwater target's three-dimensional position coordinates in the cooperative localization unit using the underwater target motion state model as a priori constraint, thereby achieving robust cooperative localization with motion consistency constraints. The specific workflow of the trajectory prediction unit is as follows:

[0073] S21: Based on historical underwater target positioning results, an underwater target motion state model is established by analyzing the three-dimensional position changes of the underwater target at continuous time intervals. The motion state model is used to characterize the motion continuity characteristics of the underwater target in the time dimension, and preferably adopts a uniform motion model, an acceleration-constrained model, or a motion model based on historical trajectory fitting. Through the motion state model, the spatial position of the underwater target at the current time is predicted, and the predicted position of the underwater target at the current time is output.

[0074] S22: Using the predicted position as a priori constraint, the underwater target's three-dimensional position is calculated in the cooperative positioning unit, and the following constraint positioning function is constructed:

[0075] ;

[0076] in, The precise three-dimensional position coordinates of the underwater target are obtained after constraint optimization using the constrained positioning function. The location of the underwater target to be calculated; For the first Adaptive weights for buoy ranging; For the first The position coordinates of each buoy; For the first The buoy's calculated distance to the underwater target; The predicted position of the underwater target at the current moment; These are the trajectory prediction constraint coefficients, used to balance distance measurement observations and motion priors, and are set through pre-experimentation.

[0077] Furthermore, the adaptive weights for the ranging of each buoy are adaptively updated in the following manner:

[0078] ;

[0079] in, This is a weight stabilization factor used to prevent the weight from becoming unstable or excessively amplified when the signal-to-noise ratio is low. The preferred value range is 5% to 20% of the average signal-to-noise ratio of the system under normal operating conditions, which is determined by prior experiments. For the first The ranging residual of a buoy This is the residual scaling parameter, used to characterize the reasonable fluctuation range of the ranging residual. It is determined based on the statistical standard deviation of the ranging residual under normal operating conditions in the past, and preferably ranges from 2 to 3 times the statistical standard deviation. The ranging residual is calculated in the following way:

[0080] ;

[0081] By introducing a residual feedback mechanism, the weight of buoys with large ranging residuals is automatically reduced in subsequent positioning calculations, thereby suppressing the impact of abnormal ranging on positioning results.

[0082] Furthermore, the cooperative positioning unit receives the calculated distance information and corresponding buoy position coordinates output by multiple buoy nodes. Under the condition of introducing the underwater target prediction position provided by the trajectory prediction unit as a prior constraint, it fuses the multi-source ranging information and obtains the precise three-dimensional spatial position of the underwater target through iterative calculation. At the same time, the cooperative positioning unit adaptively adjusts the adaptive weight of each buoy ranging according to the ranging residual and signal quality, thereby suppressing the influence of abnormal ranging on the positioning results and improving the stability and robustness of the positioning results.

[0083] Example 3:

[0084] This embodiment provides a buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction. It further refines the system hardware configuration, working parameter configuration and engineering implementation method based on Embodiment 1 and Embodiment 2, and introduces multi-scenario comparative verification to demonstrate the overall performance improvement effect of the system.

[0085] The intelligent buoy network module consists of six to twelve intelligent buoy nodes, which are distributed in a ring or polygon in the target waters. The spacing between individual buoy nodes is preferably 500 to 2,000 meters. The main body of the buoy node adopts a sealed floating hull structure and has built-in attitude self-stabilization components, so that the buoy maintains the stable orientation of the antenna and acoustic transducer even in sea state 2. The acoustic signal transceiver unit adopts a broadband pulse acoustic module with a working frequency band of 8 kHz to 15 kHz. The duration of a single pulse is preferably 50 to 100 milliseconds, and the transmission power is set to be adjustable from 20 watts to 50 watts. The sampling rate of the receiving end is not less than 48 kHz to ensure the multipath pulse resolution accuracy. The self-positioning unit adopts a dual-antenna satellite positioning structure combined with magnetic compass calibration. The buoy's own position measurement accuracy is preferably better than one meter. The buoy communication unit adopts a low-power long-range wireless communication module with a communication distance of not less than 10 kilometers and supports self-organizing network transmission between buoys, so that the ranging data can be transmitted back to the collaborative positioning center processing terminal in real time.

[0086] The sound velocity measurement module is equipped with a multi-layer depth sensing chain below each buoy node. The depth sampling interval is preferably five to ten meters, covering a water depth range of one hundred to five hundred meters. The sensing and monitoring unit integrates temperature, conductivity, and pressure sensors and adopts a corrosion-resistant packaging structure. The single complete sound velocity profile acquisition cycle is preferably adjustable from three to ten minutes, enabling the system to dynamically reflect short-period water structure changes. The sound velocity calculation unit completes preliminary sound velocity data calculation at the buoy end and uploads it to the control center. The profile modeling unit generates a continuous sound velocity profile model using a piecewise interpolation method, ensuring that the sound velocity gradient remains smooth in the abrupt transition region. The path integration unit corrects the propagation time of each ranging path based on the generated sound velocity profile model, reducing the systematic ranging error caused by non-uniform sound velocity distribution to less than one-third of the original uncorrected condition.

[0087] The signal suppression module performs initial screening of multipath signals at the local end of the buoy and performs fine discrimination at the cooperative positioning center. The signal preprocessing unit uses an adaptive bandpass filter to suppress low-frequency flow noise and high-frequency random noise. After filtering, the signal-to-noise ratio is improved by an average of four to eight decibels. The pulse detection unit can identify at least three arriving pulses and record the arrival time and relative amplitude of each pulse. The feature extraction unit generates pulse feature vectors based on pulse energy and arrival sequence structure. The multipath discrimination unit combines the sound velocity profile with the target depth estimation result of the previous moment to perform physical consistency matching. Thus, even under the condition of strong reflection in shallow water, it can still stably identify direct wave pulses, reducing the false judgment probability from about fifteen percentage points of the traditional earliest arrival discrimination method to less than three percentage points.

[0088] The collaborative positioning module is deployed on a shore-based or shipborne processing terminal. The terminal processor's main frequency is preferably not less than one gigahertz and supports parallel floating-point operation acceleration, so that the multi-buoy ranging fusion calculation time is controlled within one hundred milliseconds to meet the real-time tracking requirements. The distance calculation unit receives the direct wave delay uploaded by each buoy and generates ranging data by combining the sound speed profile correction results. The collaborative positioning unit performs fusion iteration on the ranging results of no less than four buoys. The three-dimensional positioning calculation accuracy is preferably one to three meters within a 500-meter radius of action. The trajectory prediction unit uses a continuous historical position smoothing model to predict the short-term movement trend of the target and participates in the current positioning constraint, which significantly reduces the phenomenon of continuous trajectory jumps and maintains positioning continuity during low signal-to-noise ratio periods.

[0089] like Figure 3 , Figure 4 As shown, to verify the beneficial effects of the buoy-based cooperative underwater positioning system based on multipath suppression and sound velocity profile correction described in this invention, a systematic comparative test experiment was conducted in a target water area. In this experiment, eight smart buoy nodes were deployed in the target water area to form a cooperative positioning reference network, with the buoy spacing maintained at approximately one kilometer to cover the same tracking area. Each buoy performed bidirectional ranging with the underwater target at a ranging period of one to two seconds, recording the timestamp and amplitude information of each received signal. Simultaneously, a multi-layer depth sensor chain was attached to the buoy to collect temperature, conductivity, and pressure data, forming a sound velocity profile data sequence at five-meter depth intervals. The sound velocity profile was updated every five minutes and input into the positioning calculation terminal for propagation time correction.

[0090] Three processing paths were set up in the experiment, while keeping the hardware configuration and sampling conditions consistent except for the algorithm. Traditional scheme 1 uses a fixed equivalent sound velocity and the earliest arriving pulse as the direct wave discrimination criterion; traditional scheme 2 enables sound velocity profile correction but not multipath suppression discrimination; the scheme of this invention simultaneously enables sound velocity profile correction, multipath suppression discrimination, and multi-buoy collaborative calculation. Under the same environmental conditions, the system ran continuously for thirty minutes, and the positioning error was calculated in one-minute statistical windows, recording whether a valid positioning result was successfully output within that minute. A valid output was determined by passing the direct wave discrimination and the convergence of the ranging residual and the collaborative iterative calculation meeting the threshold requirements.

[0091] After the experiment, the average positioning error, 95th percentile value, and continuous positioning success rate of the three schemes were calculated respectively. The positioning error change curve over time and the comprehensive index comparison chart were plotted to evaluate the stability and robustness of the system in complex underwater acoustic environment.

[0092] Experimental data shows that traditional scheme 1 exhibits significant error fluctuations under strong multipath reflection conditions, with an average positioning error exceeding nine meters and noticeable abnormal peaks. Traditional scheme 2, after introducing sound velocity profile correction, shows a significant reduction in systematic deviation, with the average positioning error decreasing to approximately four meters, but local jumps due to multipath misjudgment still exist. The present invention, by simultaneously introducing sound velocity profile correction and multipath suppression in a coordinated solution, significantly reduces abnormal peaks, further lowering the average positioning error to within approximately three meters, while maintaining continuous and stable output. This verifies that the present invention has significant beneficial effects in suppressing multipath interference, reducing the risk of large error tails, and improving continuous tracking stability.

[0093] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction, characterized in that, The system includes an intelligent buoy network module, a sound velocity measurement module, a signal suppression module, and a cooperative positioning module; The intelligent buoy network module is used to construct a positioning reference network using multiple buoys spatially distributed in the target water area; the sound velocity measurement module is used to obtain sound velocity distribution information of the underwater environment; the signal suppression module is used to identify and suppress multipath propagation interference in the underwater acoustic channel; and the positioning solution module is used to obtain the precise three-dimensional spatial position of the underwater target. The intelligent buoy network module includes multiple buoy nodes set at predetermined locations in the target water area. Each buoy node includes an acoustic signal transceiver unit, a self-positioning unit, and a buoy communication unit. The acoustic signal transceiver unit is used to periodically transmit bidirectional ranging signals with the underwater target and record the timestamp and amplitude information of the received signals. The self-positioning unit is used to obtain the buoy's own position in real time via GPS. The buoy communication unit is used to complete wireless data transmission between buoys and between buoys and the control center.

2. The buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction according to claim 1, characterized in that, The sound velocity measurement module includes a sensing and monitoring unit, a sound velocity calculation unit, a profile modeling unit, and a path integration unit. The sensing and monitoring unit is located at the buoy position and is used to monitor the physical influence data of sound velocity at different underwater depths. The physical influence data of sound velocity includes conductivity, temperature, and depth parameters. The sound velocity calculation unit is used to output a sound velocity sequence at discrete depth points based on the physical influence data of sound velocity. The profile modeling unit is used to construct an interpolation fitting model of the underwater sound velocity profile by combining the sound velocity sequence of discrete depth points. The path integration unit is used to calculate the theoretical propagation time of the sound wave along a specific path based on the given start point, end point, and the interpolation fitting model of the sound velocity profile.

3. The buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction according to claim 1, characterized in that, The signal suppression module includes a signal preprocessing unit, a pulse detection unit, a feature extraction unit, and a multipath discrimination unit. The signal preprocessing unit is used to perform filtering preprocessing on the two-way ranging signal. The pulse detection unit is used to detect all pulse peaks exceeding a preset threshold from the preprocessed signal and extract the arrival time of each pulse signal. The feature extraction unit is used to extract the time delay parameter and amplitude parameter of each detected pulse signal and calculate the signal-to-noise ratio. The multipath discrimination unit is used to identify and analyze the direct wave pulse between the buoy and the underwater target by combining the detected pulse signals and suppress multipath echo interference.

4. The buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction according to claim 1, characterized in that, The cooperative positioning module includes a distance calculation unit, a cooperative positioning unit, and a trajectory prediction unit. The distance calculation unit is used to analyze and calculate the distance between the buoy and the underwater target based on the arrival delay of the direct path pulse signal identified by the multipath identification unit and the interpolation fitting model of the sound speed profile. The cooperative positioning unit is used to receive the calculated distances and buoy position coordinates of multiple buoy nodes and obtain the precise three-dimensional position coordinates of the underwater target through analysis and iteration. The trajectory prediction unit is used to establish a motion state model of the underwater target and output the motion position prediction of the underwater target.

5. A buoy-coordinated underwater positioning system based on multipath suppression and sound velocity profile correction according to claim 1, characterized in that, The specific workflow of the multipath discrimination unit is as follows: S11: For a certain buoy, obtain its position information and the estimated position information of the underwater target, wherein the estimated position information of the underwater target is the positioning result of the underwater target at the previous moment provided by the cooperative positioning unit; S12: Obtain all pulse signal sequences and their corresponding time delay and amplitude parameters. For any two pulse signals, calculate their time delay difference. ； in, For the first The pulse relative to the first The time delay difference of each pulse, and The first The pulse and the first The arrival time delay of each pulse; establishing a theoretical model of the time delay difference between sea surface reflection and direct wave: ； in, The underwater target depth is At that time, the theoretical time delay difference between the sea surface reflection path and the direct path; This represents the straight-line path between the buoy's position and the estimated position of the underwater target. This represents the return path between the buoy's position reflected from the sea surface and the estimated position of the underwater target. Points on the path The sound speed value at that location is obtained through an interpolation fitting model of the underwater sound speed profile; S13: Combine any two pulse signals into a pulse pair, iterate through all pulse pairs, and for each pair, satisfy... The pulse pair combination is used to invert the corresponding signal source depth through a time delay difference theoretical model: ； in, For pulse pairs The depths of the signal sources are obtained by inversion using the time delay difference theoretical model, and the deviations between the depths of each signal source and the initial estimated depths are calculated: ； in, For pulse pairs The deviation between the corresponding signal source and the initial estimated depth, The initial estimated depth of the underwater target is obtained through step S1; S14: For each pulse pair, calculate its overall matching confidence: ； in, For pulse pairs The corresponding signal source is used as the matching confidence level for the underwater target. This is the amplitude weighting factor, with a value range of... ; Amplitude matching degree characterizes the degree of amplitude matching between the pulse pair and the underwater target; Depth matching degree characterizes the degree of depth matching between the pulse pair and the underwater target; S15: After completing the comprehensive matching confidence calculation for all pulse pairs, traverse all pulse pairs, select the pulse pair with the highest matching confidence as the optimal pulse pair, and determine the direct wave pulse of the underwater target based on the relationship between the arrival delays of the two pulse signals in the pulse pair.

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