Acoustic multi-station correction method using a ray model

Abstract

The application discloses an acoustic multi-station correction method using a sound ray model, comprising the following steps: determining the position information of each acoustic station, collecting and acquiring the data of the sound signal transmitted and received by the stations in synchronization; obtaining the environmental data of the observation area, simulating the sound rays among the stations, and obtaining the reference sound ray length, the reference propagation time and the reference sound ray emission angle; performing the signal cross-correlation processing of the original data among the acoustic stations, matching the sound ray results among the stations, extracting the peak value at each time, and obtaining the actual propagation time of multiple sound ray matching peaks; recording the station data and comparing and calculating the real-time change of the station position and the drift distance generated from the original position according to the change of the transducer depth and the actual propagation time; obtaining the propagation time error among the stations by using the real-time station change, calibrating the accurate direct-path sound ray propagation time; and calibrating the propagation time of other peaks by using the actual propagation time difference among the peaks and the calibrated direct-path sound ray propagation time.

Description

Technical Field

[0001] This invention belongs to the field of underwater acoustic observation and positioning technology for oceans, rivers, reservoirs and ports, and specifically relates to an acoustic multi-station correction method using a ray model. Background Technology

[0002] Currently, underwater acoustic observation and positioning technologies are gradually being applied to specific marine environments such as small marine ranches, shallow hydrothermal vents, artificial upwellings, and port areas. The key to underwater acoustic applications is the accurate resolution of propagation times along different paths. However, the propagation time of sound waves is affected by instrument clock errors, station position errors, and environmental changes (flow velocity and temperature).

[0003] Currently, various positioning methods exist. For example, patent application CN112346102A provides an underwater acoustic positioning, navigation, and timing system. The surface segment deploys a two-way reference transfer device (surface / underwater) to obtain the BeiDou spatiotemporal reference from the BeiDou satellite navigation system and transfer it to the underwater segment. The user segment deploys user terminals to achieve underwater acoustic positioning, navigation, and timing using an acoustic / multi-source tight coupling method. The underwater segment deploys seabed base stations, with multiple master and slave seabed base stations forming a seabed array to publish the underwater spatiotemporal reference and provide high-precision underwater acoustic spatiotemporal reference information to the user segment. A shore-based control center monitors the operational status of the surface, user, and underwater segments and processes the acquired data. This system provides high-precision acoustic positioning, navigation, and timing services, especially with a two-way spatiotemporal reference transfer function (surface / underwater), which can provide underwater-to-surface spatiotemporal reference transfer services when satellite service is denied.

[0004] The patent application with publication number CN112947068A provides an acoustic positioning and tracking control method, which deploys three buoys emitting periodic acoustic signals on the water surface, estimates the AUV's position based on the arrival time of the three signals and the sound velocity profile; uses extended Kalman filtering to process system uncertainties caused by position estimation and ocean current interference; and designs a path tracking model predictive controller considering the AUV hydrodynamic model to effectively handle the physical constraints of the AUV system and achieve optimal tracking performance.

[0005] Furthermore, the positioning technology provided in the existing literature [Zhang C, Kaneko A, Zhu XH, Gohda NJJoGRO. Tomographic mapping of a coastal upwelling and the associated diurnal internal tides in Hiroshima Bay, Japan. 2015;120(6):4288-305] treats the change in station position as a single fixed value change and corrects it directly through acoustic simulation of the direct path, ignoring the real-time deflection of the station position. The real-time accurate correction of the station position has become the key to measuring the quality of the data. Summary of the Invention

[0006] This invention provides an acoustic multi-station correction method using a ray model, proposing to use three underwater acoustic stations to calculate and correct the position drift error of each station in real time, so as to solve the station propagation time error.

[0007] The specific technical solution adopted in this invention is as follows:

[0008] An acoustic multi-station correction method using ray models includes the following steps:

[0009] (1) Determine the location information of each acoustic station and collect and transmit acoustic signal data synchronously between each pair of stations;

[0010] (2) Obtain environmental data of the observation area and perform sound ray simulation between stations to obtain reference sound ray length, reference propagation time and reference sound ray emission angle;

[0011] (3) Perform signal cross-correlation processing on the raw data between acoustic stations, match the sound ray results between stations in step (2), extract the peak value at each time moment, and obtain the actual propagation time of multiple sound ray matching peaks;

[0012] (4) Based on the change in transducer depth and the actual propagation time in step (3), record the station location data and compare and calculate the real-time change in the station location and the drift distance from the original location.

[0013] (5) Use the real-time station position change obtained in step (4) to obtain the propagation time error between stations and calibrate the accurate direct path sound propagation time; and use the actual propagation time difference between each peak in step (3) combined with the calibrated direct path sound propagation time to calibrate the propagation time of other peaks.

[0014] In this application, the arrangement of each acoustic station includes: a buoy, an acoustic transducer, a depth gauge, a data acquisition system, a rope, an anchor, and other equipment, not limited to those mentioned above. Preferably, the arrangement of each acoustic station includes a buoy, an acoustic transducer, a depth gauge, a data acquisition system, a rope, and an anchor; the buoy, acoustic transducer, and anchor are connected by a rope, the data acquisition system is placed on the anchored ship or shore, and a depth gauge or a module with depth acquisition function is attached to the same position as the acoustic transducer.

[0015] In this application, the acoustic station deployment method, from top to bottom, is as follows: buoy, acoustic transducer, and anchor, all three connected by ropes. The data acquisition system is placed on the anchored vessel or shore, and a depth gauge or depth acquisition module is attached to the same position as the acoustic transducer. This deployment method does not require precise determination of the exact depth of the deployment location; an estimated depth can be used. Furthermore, due to the weight of the acoustic transducer, the deployment state of the station should be such that the rope between the buoy and the transducer is tightly connected, while the rope between the transducer and the anchor is loosely connected.

[0016] In step (1), after the clocks of the acquisition systems at each station are synchronized, the stations transmit and receive data signals simultaneously through the acoustic transceiver system; that is, signals are sent and acquired at the same time, and the transmitted and received signals are different modes of the same family of signals, ensuring that the distance between stations is greater than the minimum transmission distance of the signal.

[0017] Preferably, in step (2), the sound velocity profile data of the observed environment is collected by the sensor, and the terrain data between the stations is also collected. Combined with the location information, the sound ray simulation between the stations is performed.

[0018] In this application, sound velocity profiles and terrain data between stations are combined with GPS station spacing estimates recorded during station deployment to perform sound ray simulation between stations to obtain relevant reference data.

[0019] Preferably, the specific process of step (3) is as follows:

[0020] Perform signal correlation on the acoustic signal data obtained at each station in step (1) to identify and extract the propagation time of each peak on the acoustic signal at different times;

[0021] By matching the propagation time of each sound ray referenced in step (3), the propagation time of the extracted peak is matched, the peak and the reference sound ray are matched, the propagation time of the direct path sound ray matching the peak is extracted, and the sound velocity profile is converted into the station spacing.

[0022] Preferably, the real-time station distance is obtained by multiplying the direct path propagation time by the station depth reference sound speed, wherein the bidirectional propagation time of each sound ray between any two stations is calculated as follows:

[0023]

[0024] in and These represent the reference average propagation sound velocity and average flow velocity on each section of the profile, respectively, where i and j are the station numbers. It is the length of the vocal liner between the two positions.

[0025] Furthermore, a temperature, salinity, and depth sensor is used to collect the reference sound velocity at the station depth. Additionally, since the scale of horizontal velocity variation is much larger than that of vertical velocity variation, the vertical velocity can be ignored.

[0026] Preferably, the calibration calculation of the direct path sound ray propagation time is defined as follows:

[0027]

[0028] in For the corrected direct path propagation time, Let j be the drift distance of position j. vocal liner length Projection in the horizontal direction, and The angle between the original and the current station position after the station position has shifted.

[0029] Preferably, the propagation time of the other peaks is obtained by adding the time delay difference between the other ray forms and the original direct path sound ray to the corrected direct path sound ray time delay, as follows:

[0030]

[0031] in The propagation time of the other peaks after correction, and This refers to the propagation time of the direct path and other ray peaks before correction.

[0032] Furthermore, after obtaining the propagation time of each matching peak at each station, the drift superposition of each station to the propagation time of other stations is corrected, and finally all the correction results of each station are averaged.

[0033] Compared with the prior art, the method of the present invention has the following beneficial effects:

[0034] 1. By transmitting signals between multiple acoustic stations, a multi-station acoustic correction method using a ray model is proposed, providing a solution and method for acoustic station drift correction.

[0035] 2. Utilize the obtained direct path sound rays and station depth changes to quickly correct the drift positions of three or more stations, and simultaneously correct the propagation time of other peaks obtained at each moment.

[0036] 3. Compared to simulating the voice individually at each moment, this method has a faster correction effect. Attached Figure Description

[0037] Figure 1 This is a schematic flowchart of the method of the present invention;

[0038] Figure 2 This is a schematic diagram of the three-station position correction method of the present invention; wherein (a) shows the station layout model of the three stations; (b) shows the layout of each station before and after drift under the vertical projection of the three stations; and (c) shows the change model of the station layout in (a) before and after drift.

[0039] Figure 3 The following is a comparison of the profile temperature inversion results in an implementation verification example of the method of the present invention. (a) is the temperature inversion result before S1-S3 propagation time correction, (b) is the temperature inversion result after S1-S3 propagation time correction, and (c) is a temperature comparison between the S1-S3 and S1-S4 propagation time correction results and the temperature of the temperature sensor at depths of 5.5m and 18m during the same time period. Detailed Implementation

[0040] Numerous specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the invention is not limited to the specific embodiments disclosed below.

[0041] like Figure 1 As shown, an acoustic multi-station correction method using a ray model includes the following steps:

[0042] Step 1: Determine the location where each station needs to be deployed, record the GPS data of each station, and calculate the reference station spacing; at the same time, the two stations will simultaneously transmit and receive data signals through an acoustic transceiver system.

[0043] In this embodiment, three underwater acoustic stations are set up. Each acoustic station includes a buoy, acoustic transducer, depth gauge, data acquisition system, rope, anchor, and other equipment, not limited to those mentioned above. The acoustic stations are deployed as follows: from top to bottom, the buoy, acoustic transducer, and anchor are connected by ropes. The data acquisition system is placed on the anchored vessel or shore. A depth gauge or depth acquisition module is attached to the same location as the acoustic transducer. It is necessary to ensure that there are no obstacles between any two stations. The data acquisition system is synchronized using its internal clock. One end of the acoustic transducer is anchored, and the other end is connected by a buoy. A depth gauge is installed next to the acoustic transducer. The rope lengths between the buoy and the acoustic transducer, and between the acoustic transducer and the anchor, are measured.

[0044] Step 2: Combine the topographic data between stations and the sound velocity profile data of the environment collected by other sensors with the observation stations to obtain a station location model with multiple stations. Figure 2 (a) The figure shows a layout model of 3 stations.

[0045] In this embodiment, a simple sound velocity profile is collected from the observed environment using sensors such as a temperature, salinity, and depth sensor (CTD). Simultaneously, instruments such as a depth sounder and an ADCP (Acoustic Doppler Current Profiler) are used to conduct a continuous survey between each pair of stations. Furthermore, by combining the obtained sound velocity profiles and topographic data between stations with the estimated GPS station spacing recorded during station deployment, sound ray simulations between stations are performed to obtain relevant reference data.

[0046] Step 3: Perform correlation processing on the acoustic signal transmission results between multiple stations to obtain peak results in the time domain and distinguish fine multi-peak results. At the same time, perform acoustic ray simulation between stations using the multi-station model data to obtain possible acoustic ray forms, reference propagation times, and reference acoustic ray lengths.

[0047] Step 4: Compare the multi-peak propagation time results obtained in Step 3 with the reference propagation times of each ray to identify possible ray forms. Simultaneously, using the depth changes recorded by the depth gauge and the measured rope length from Step 1, calculate the distance of station drift. This process is as follows: Figure 2 As shown in (c).

[0048] Step 5: Using the obtained propagation time to the direct peak, the station position is corrected in real time, as follows:

[0049] First, by utilizing the time difference in two-way propagation, through Calculate the reference average flow velocity between station i and station j, where, and These represent the reference average propagating sound velocity and average flow velocity on each of the cross-sectional layers. The vocal liner length between the two positions. The forward propagation time from station i to station j. Let the backpropagation time be from station j to station i... The reference propagation time from station i to station j. The flow velocity is minimally affected by station location drift and can be ignored in this calculation.

[0050] Then, project the position onto the horizontal plane, such as... Figure 2 As shown in (b), to simplify the calculation, the drift error of one station can be superimposed on the other stations. Thus, the distance correction equations for the three stations can be established as follows (the error of station 1 is superimposed on the other stations):

[0051]

[0052] The explanation will be based on the formula in the first row. The straight-line distance between stations 1 and 2 is the corrected distance. and The corrected and uncorrected projected coordinates of station 1 and station 2 are given. and Reference propagation velocity and estimated average flow velocity between station 1 and station 2 The direct path propagation delay between station 1 and station 2.

[0053] Simultaneously, combining the station drift equations:

[0054]

[0055] Therefore, each station can be considered to have its accurate position corrected by the intersection of the two circles. After determining the real-time position of the station, the formula is used... The accurate propagation time on the direct path is obtained.

[0056] For other propagation time peaks, their propagation time can be obtained by adding the time delay difference between other ray forms and the original direct path sound ray to the corrected precise direct path time delay, as detailed below. For the propagation time of other peaks after correction, Let i be the corrected direct path propagation time from station i to station j. and This refers to the propagation time of the direct path and other ray peaks before correction.

[0057]

[0058] Step 7: At this point, the accurate propagation time of each matching peak at each station has been obtained. To further ensure accurate propagation time, the drift superposition of each station onto the propagation time of other stations is corrected, and finally, all correction results for each station are averaged.

[0059] To verify the effectiveness of this invention, the method was used to correct acoustic signal data obtained from an experiment at Huangcai Reservoir in Changsha in 2022. The correction results are as follows. Figure 3 As shown.

[0060] By analyzing the three stations S1, S3, and S4 in the experiment... Figure 1 The steps involve data correction processing to obtain a comparison of the final temperature before and after correction, as well as a comparison with the temperature sensor at the same depth. Figure 3 (a) shows the temperature inversion results before S1-S3 propagation time correction. Figure 3(b) shows the temperature inversion results after S1-S3 propagation time correction. Figure 3 (c) is a comparison of the temperatures of S1-S3 and S1-S4 after propagation time correction with those of temperature sensors at depths of 5.5m and 18m during the same time period.

[0061] After obtaining the propagation time of the original ray matching peak and the reference ray length for ray simulation, a propagation time correction program corresponding to this method was written using MATLAB to establish a multi-station correction model. Finally, the inversion method was used to obtain accurate temperature results to verify the accuracy of the comparison method.

[0062] Correcting the propagation time of the acoustic ray matching peak can yield more intuitive and accurate results. This method proposes an approach to solve the problem of underwater acoustic station drift, and its effectiveness is verified through examples.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An acoustic multi-station correction method using a ray model, characterized in that, Including the following steps: (1) Determine the location information of each acoustic station and collect and transmit acoustic signal data synchronously between each pair of stations; (2) Obtain environmental data of the observation area and perform sound ray simulation between stations to obtain reference sound ray length, reference propagation time and reference sound ray emission angle; (3) Perform signal cross-correlation processing on the raw data between acoustic stations, match the sound ray results between stations in step (2), extract the peak value at each time moment, and obtain the actual propagation time of multiple sound ray matching peaks; (4) Record the station position data and compare and calculate the real-time change of the station position based on the change in the depth of the acoustic transducer and the actual propagation time in step (3); calculate the drift distance between the original position and the acoustic transducer based on the change in the depth of the acoustic transducer and the length of the rope connecting the acoustic transducer. (5) Use the real-time station position changes obtained in step (4) to obtain the propagation time error between stations and calibrate the accurate direct path sound ray propagation time; The propagation time of other peaks is calibrated by combining the actual propagation time difference between each peak in step (3) with the direct path propagation time of the calibrated peaks.

2. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, In step (1), the arrangement of each acoustic station includes a buoy, an acoustic transducer, a depth gauge, a data acquisition system, a rope, and an anchor; the buoy, acoustic transducer, and anchor are connected by a rope, the data acquisition system is placed on the anchored ship or shore, and a depth gauge or a module with depth acquisition function is attached to the same position as the acoustic transducer.

3. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, In step (1), after the clocks of the acquisition systems at each station are synchronized, data signals are acquired simultaneously between each other through an acoustic transceiver system.

4. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, In step (2), the sensor is used to collect sound velocity profile data of the observed environment. At the same time, the terrain data between the stations is also collected, and the sound ray simulation between the stations is carried out in combination with the location information.

5. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, The specific process of step (3) is as follows: Perform signal correlation on the acoustic signal data obtained at each station in step (1) to identify and extract the propagation time of each peak on the acoustic signal at different times; By matching the propagation time of each sound ray referenced in step (3), the propagation time of the extracted peak is matched, the peak and the reference sound ray are matched, the propagation time of the direct path sound ray matching the peak is extracted, and the sound velocity profile is converted into the station spacing.

6. The acoustic multi-station correction method using a ray model according to claim 5, characterized in that, The real-time station distance is obtained by multiplying the direct path propagation time by the station depth reference sound speed. The bidirectional propagation time of each sound ray between any two stations is calculated as follows: in and These represent the reference average propagation sound velocity and average flow velocity on each section of the profile, respectively, where i and j are the station numbers. It is the length of the vocal liner between the two stations.

7. The acoustic multi-station correction method using a ray model according to claim 6, characterized in that, The station depth reference sound velocity is collected using a temperature, salinity, and depth sensor.

8. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, The calibration calculation for the direct path sound ray propagation time is defined as follows: in For the corrected direct path propagation time, Let j be the drift distance of position j. vocal liner length Projection in the horizontal direction, and The angle between the original and the current station position after the station position has shifted.

9. The acoustic multi-station correction method using a ray model according to claim 8, characterized in that, The propagation time of the other peaks is obtained by adding the time delay difference between the other ray forms and the original direct path sound ray to the corrected direct path sound ray time delay, as follows: in The propagation time of the other peaks after correction, and This refers to the propagation time of the direct path and other ray peaks before correction.

10. The acoustic multi-station correction method using a ray model according to claim 1, characterized in that, After obtaining the propagation time of each matching peak at each station, the drift superposition of each station to the propagation time of other stations is corrected, and finally all the correction results of each station are averaged.

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