An auxiliary decision-making method for underwater acoustic communication based on marine environmental data

Abstract

The present invention relates to an auxiliary decision-making method for underwater acoustic communication based on marine environmental data. By introducing marine environmental data as a decision variable, the accuracy of underwater acoustic communication performance evaluation is improved. According to marine environmental library data, by performing sound field calculation on marine environmental historical data and measured data, the complex marine environmental data problem is integrated and simplified into a problem of solving the minimum propagation loss between communication nodes. A set of simple underwater acoustic communication auxiliary decision-making methods is formed through certain communication performance evaluation and communication restriction azimuth evaluation algorithms. The results output by the method include signal margin, communication distance, and communication restriction azimuth. Based on the above results, the communication azimuth with better communication effect can be effectively estimated, thereby providing numerical prediction support for the position arrangement of each communication node when the underwater acoustic communication is networked.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic communication, and in particular to an auxiliary decision-making method for underwater acoustic communication based on marine environment data. Background Art

[0002] Existing underwater acoustic communication has long been limited by communication means and communication distance, making it difficult for communication to play an effective role underwater. Although the results of traditional underwater acoustic communication auxiliary decision-making methods are parameters such as bit error rate and signal-to-noise ratio, which can evaluate the communication distance, they cannot provide auxiliary decision support for the deployment of communication node locations, nor can they provide communication location prediction results with the maximum communication distance and the best communication effect, that is, communication node parameter recommendations. Summary of the invention

[0003] The purpose of the present invention is to provide an auxiliary decision-making method for underwater acoustic communication based on marine environment data to solve the problems encountered in the above-mentioned background technology.

[0004] To achieve the above object, the technical solution of the present invention is as follows:

[0005] An auxiliary decision-making method for underwater acoustic communication based on marine environment data comprises the following steps:

[0006] Step 1: By setting the submersible parameters and communication node parameters, and obtaining the pre-processed ocean environment data based on the position parameters in the communication node parameters, the accuracy of underwater acoustic communication performance evaluation can be improved;

[0007] Step 2: By introducing all data into the acoustic field analysis, high-precision propagation loss is obtained for evaluating communication performance;

[0008] Step 3: Use the communication performance evaluation algorithm to digitize and visualize the effect of underwater acoustic communication in the form of communication distance and signal margin;

[0009] Step 4: Determine whether there is a convergence zone based on the sea depth and sound speed profile of the communication node. If it is determined that a convergence zone can be generated, combine the sound trajectory and limit angle in the calculation results to obtain the convergence zone location information with better communication effect;

[0010] Step 5: Obtain the optimal communication position based on communication distance, signal margin, and convergence area position.

[0011] In the above scheme, it is also necessary to evaluate the effect of underwater acoustic communication in different directions in combination with the communication distance, signal margin and convergence area calculation results obtained by the communication effectiveness evaluation algorithm.

[0012] In the above scheme, the communication restriction direction is also evaluated. After obtaining the communication performance evaluation results and the communication restriction direction evaluation results, the two are combined as the objective function to make a numerical prediction of the optimal communication position, thereby determining the optimal communication position.

[0013] Compared with the prior art, the beneficial effect of the present invention is that the accuracy of underwater acoustic communication performance evaluation is improved by introducing marine environmental data as a decision variable. Based on the marine environmental database data, by performing sound field calculation on the marine environmental historical data and measured data, the complex marine environmental data problem is integrated and simplified into the problem of solving the minimum propagation loss between communication nodes, and a set of simple underwater acoustic communication auxiliary decision-making methods are formed through certain communication performance evaluation and communication restriction azimuth evaluation algorithms. The results output by the method include signal margin, communication distance, and communication restriction azimuth. Based on the above results, the communication azimuth with better communication effect can be effectively estimated, thereby providing numerical prediction support for the position arrangement of each communication node when the underwater acoustic communication network is established. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The disclosure of the present invention is described with reference to the accompanying drawings. It should be understood that the drawings are for illustrative purposes only and are not intended to limit the scope of protection of the present invention. In the accompanying drawings, the same reference numerals are used to refer to the same components. Among them:

[0015] Figure 1 This is the architecture diagram of the underwater acoustic communication decision-making assistance solution of the present invention. DETAILED DESCRIPTION

[0016] In order to make the technical means, creative features, objectives and effects of the present invention easy to understand, the present invention is now further described in detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the relevant components of the present invention.

[0017] According to the technical solution of the present invention, without changing the essential spirit of the present invention, a person skilled in the art can propose a variety of interchangeable structural modes and implementation modes. Therefore, the following specific implementation modes and the accompanying drawings are only exemplary descriptions of the technical solution of the present invention, and should not be regarded as the entirety of the present invention or as a limitation or restriction to the technical solution of the present invention.

[0018] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0019] Embodiment 1, as Figure 1 As shown, an auxiliary decision-making method for underwater acoustic communication based on marine environment data includes the following steps:

[0020] Step 1: By setting the submersible parameters and communication node parameters, and obtaining the pre-processed ocean environment data based on the position parameters in the communication node parameters, the accuracy of the underwater acoustic communication performance evaluation can be improved.

[0021] The submersible parameters include the mission area location, sound source level, and emission directivity index; the communication node parameters include longitude and latitude and depth; the environmental data include seafloor elevation data, ocean hydrological data, and ocean bottom data. The data structure of the seafloor elevation data is: with the communication node location as the origin, the elevation changes with the distance at different directions.

[0022] Step 2: By introducing all data into the acoustic field analysis, high-precision propagation loss is obtained for evaluating communication performance.

[0023] The result of the acoustic field analysis is the propagation loss, which can be expressed as TL(θ, d, h), where θ is the azimuth, d is the horizontal distance from the origin, and h is the depth. The propagation loss is calculated using the classical ray model, which is based on environmental data, vehicle parameters, and communication node parameters.

[0024] Usually, signal-level simulation is performed after determining the positions of the receiving hydrophone and the transmitting hydrophone, focusing on analyzing parameters such as the bit error rate and signal-to-noise ratio of underwater acoustic communication, which are used as the basis for auxiliary decision-making in underwater acoustic communication, and the propagation loss calculated based on the marine environment data is treated as a constraint condition for communication.

[0025] Step 3: Obtain the communication distance and signal margin through the communication performance evaluation algorithm, and display the effect of underwater acoustic communication in the form of communication distance and signal margin in a digital and intuitive manner.

[0026] First, the maximum allowable propagation loss FOM value is calculated using the sonar communication equation, and the equation is:

[0027] FOM=SL-NL+AG-DT

[0028] Among them, SL represents the sound source level at the transmitting end, NL is the noise level, AG is the array processing gain, and DT is the threshold at which the receiving end just completes the communication task.

[0029] Among them, the communication distance is obtained: when the FOM value is equal to the propagation loss TL, the communication task can be completed. According to the sound field analysis results in different directions, the horizontal distance corresponding to the propagation loss reaching the quality factor is found, which is the maximum communication distance Dist of the platform.

[0030] Among them, the signal margin is obtained: the signal margin SE expression is:

[0031] SE(θ,d,h)=SL-NL+AG-DT-TL(θ,d,h)

[0032] Step 4: Determine whether there is a convergence zone based on the sea depth and sound speed profile of the communication node. If it is determined that a convergence zone can be generated, combine the sound trajectory and limit angle in the calculation results to obtain the convergence zone location information with better communication effect.

[0033] Step 5: Determine the communication position based on the communication distance, signal margin, convergence area position, and the simulated annealing algorithm. The communication position includes the communication node direction, communication node distance, and communication node depth.

[0034] Embodiment 2, as Figure 1 As shown, the difference from Example 1 is that after the fourth step, it is also necessary to evaluate the effect of underwater acoustic communication in different directions in combination with the communication distance, signal margin and convergence area calculation results calculated by the communication performance evaluation algorithm.

[0035] Among them, the evaluation rules for evaluating the effect of underwater acoustic communication in different directions are:

[0036] ① When there is a convergence area in a direction, there will be a shadow area in the adjacent sea area. When the required communication distance is not far, an evaluation coefficient A1 will be added to the direction where there is a convergence area, and the coefficient is a negative value;

[0037] ② Arrange the evaluation coefficient A2 of each direction according to the communication distance, and the value of the coefficient follows the rule of arranging from small to large according to the communication distance;

[0038] ③ Eliminate the evaluation coefficient A3 of each direction according to the signal margin. The value of this coefficient is determined by the distribution size of the upper shadow area of ​​the direction, and this coefficient is a negative value;

[0039] ④The final evaluation coefficient is the sum of all coefficients A=A1+A2+A3. When the coefficient is less than a certain value, the bearing is a communication navigation restricted bearing.

[0040] The design of the underwater acoustic communication effectiveness evaluation algorithm takes into account the historical and measured data of the ocean environment, communication node parameters, and submersible parameters, and implements the underwater acoustic communication effectiveness evaluation based on the underwater acoustic propagation analysis method, including signal margin and communication distance, making the communication results of underwater acoustic communication more accurate.

[0041] Embodiment 3, as Figure 1 As shown, the difference from Example 2 is that: the communication restriction direction is also evaluated. After obtaining the communication performance evaluation result and the communication restriction direction evaluation result, the two are combined as the objective function, and the objective function expression is:

[0042] F=a*SE+b*D+c*A

[0043] Among them, a, b, and c are coefficients, which are adjusted according to the actual debugging results. Here, the simulated annealing algorithm is used to combine parameters such as θ, d, and h, and F is used as the objective function to numerically predict the optimal communication position, thereby determining the optimal communication position.

[0044] The design of the underwater acoustic communication restricted azimuth evaluation algorithm takes into account the convergence zone effect and the acoustic field analysis results, and gives the underwater vehicle navigation communication restricted azimuth according to the communication target position parameters. By designing the underwater acoustic communication node position prediction, combining the underwater acoustic communication performance evaluation with the communication restricted azimuth evaluation, the underwater acoustic communication node position with the best communication effect is given.

[0045] In this method, the ocean environment statistical analysis data, communication node parameters and submersible parameters (unmanned underwater vehicle parameters) are first used to evaluate the effectiveness of underwater acoustic communication, that is, the calculation and analysis of underwater acoustic communication distances at different directions and signal margins at different positions. Then, on this basis, the system uses the convergence zone effect and the sound field analysis results to give a communication azimuth restriction evaluation on the horizontal plane, avoid navigation directions that are not conducive to communication, and give a communication position distribution prediction result with better communication effect, so as to achieve the maximum communication distance and the best communication effect.

[0046] In summary, this scheme improves the accuracy of underwater acoustic communication performance evaluation by introducing marine environmental data as a decision variable. Based on the marine environmental database data, by calculating the sound field of historical marine environmental data and measured data, the complex marine environmental data problem is integrated and simplified into the problem of solving the minimum propagation loss between communication nodes, and a set of simple underwater acoustic communication auxiliary decision-making methods are formed through certain communication performance evaluation and communication restriction azimuth evaluation algorithms. The results output by the method include signal margin, communication distance, and communication restriction azimuth. Based on the above results, the communication azimuth with better communication effect can be effectively estimated, thereby providing numerical prediction support for the position arrangement of each communication node when the underwater acoustic communication network is established.

[0047] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An auxiliary decision-making method for underwater acoustic communication based on marine environment data, characterized in that: The following steps are involved: Step 1: By setting the submersible parameters, communication node parameters, and the pre-processed ocean environment data obtained according to the position parameters in the communication node parameters; Step 2: By introducing all data into the acoustic field analysis, high-precision propagation loss is obtained for evaluating communication performance; Step 3: Use the communication performance evaluation algorithm to digitize and visualize the effect of underwater acoustic communication in the form of communication distance and signal margin; Step 4: Determine whether there is a convergence zone based on the sea depth and sound speed profile of the communication node. If it is determined that a convergence zone can be generated, obtain the convergence zone location information by combining the sound line trajectory and limit angle in the calculation results. Step 5: Obtain the optimal communication position based on the communication distance, signal margin, and convergence area position; Among them, the signal margin is obtained: expression: ； in, SL Represents the sound source level at the sending end, NL is the noise level, AG is the array processing gain, DT is the threshold at which the receiving end just completes the communication task, represents the result of the sound field analysis; For direction, is the horizontal distance from the origin, for depth; The evaluation rules for evaluating the effect of underwater acoustic communication in different directions are: ① When there is a convergence zone in a direction, there is a shadow zone in the adjacent sea area. If the required communication distance is not far, the direction with the convergence zone will be increased by an evaluation coefficient. , the coefficient is negative; ② Evaluate the evaluation coefficients for each direction based on the communication distance , the value of the coefficient follows the rule of arranging from small to large according to the communication distance; ③ Eliminate the evaluation coefficients of each direction based on the signal margin , the value of this coefficient is determined by the size of the upper shadow distribution in the azimuth, and this coefficient is a negative value; ④The final evaluation coefficient is the sum of all coefficients , when the coefficient is less than a certain value, the bearing is a communication navigation restricted bearing; The communication restriction direction is also evaluated. After obtaining the communication performance evaluation results and the communication restriction direction evaluation results, the two are combined as the objective function. The objective function expression is: ； in a, b, c is the coefficient, which is adjusted according to the actual debugging results. Here, the simulated annealing algorithm combination is used θ, d, h Parameters, with F The optimal communication position is numerically predicted as the objective function, thereby determining the optimal communication position.

2. The auxiliary decision-making method for underwater acoustic communication based on marine environment data according to claim 1, characterized in that: In the first step, the submersible parameters include the mission area location, sound source level, and emission directivity index; the communication node parameters include longitude and latitude and depth; and the environmental data include seabed elevation data, ocean hydrological data, and ocean bottom data.

3. The auxiliary decision-making method for underwater acoustic communication based on marine environment data according to claim 2 is characterized in that: The data structure of the seabed elevation data is as follows: the communication node position is taken as the origin, and the elevation changes with the distance at different locations.

4. The auxiliary decision-making method for underwater acoustic communication based on marine environment data according to claim 1, characterized in that: In the second step, the propagation loss is calculated using the classical ray model, which is based on environmental data, vehicle parameters, and communication node parameters.

5. The auxiliary decision-making method for underwater acoustic communication based on marine environment data according to claim 1, characterized in that: In the fifth step, the communication position includes the communication node direction, the communication node distance, and the communication node depth.

6. The auxiliary decision-making method for underwater acoustic communication based on marine environment data according to claim 1, characterized in that: After the fourth step, it is also necessary to evaluate the effect of underwater acoustic communication in different directions based on the communication distance, signal margin and convergence area calculation results calculated by the communication effectiveness evaluation algorithm.

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