Fish movement visual simulation method, device and equipment

Abstract

The fish motion visualization simulation method comprises the steps that a simulation system is constructed, simulation parameters are configured, and the simulation system comprises an arc array transmitting and receiving model composed of a plurality of array elements and a fish motion model; simulating an actual movement track of the fish based on the initial position of the fish and a fish movement model; each array element is controlled to transmit and receive signals according to a preset transmitting and receiving period, and each array element transmits a detection signal in a transmitting state and receives a return signal in a receiving state; in each transmitting and receiving period, estimating the measurement and calculation position of the fish according to the detection signal and the return signal of each array element; determining the trajectory deviation of the fish according to the measurement and calculation motion trajectory formed by the plurality of measurement and calculation positions and the actual motion trajectory; and generating a visual report for reflecting the motion state of the fish based on the actual motion trail, the measured motion trail and the trail deviation. According to the fish motion visual simulation method, device and equipment provided by the invention, accurate and reliable data can be provided for fishery management, acoustic detection and biological behavioral research.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of motion simulation, in particular to a fish motion visual simulation method, device and equipment. BACKGROUND

[0002] In the field of aquaculture, the law of fish motion is directly related to the management of the breeding environment, the optimization of the feeding strategy, and the early warning and control of the escape risk. In the prior art, the research on fish group behavior mainly relies on artificial observation or detection means based on video images. Although this kind of method can obtain part of the motion state of fish, the accuracy is low when the underwater environment is complex, the light is insufficient or the fish group is dense, and at the same time, this kind of method stays on the two-dimensional level and is difficult to accurately reflect the motion trajectory of fish in the three-dimensional space.

[0003] The existing research is also single in the presentation mode of the motion result, lacks intuitive visualization tools, and cannot provide accurate and reliable data for fishery management, acoustic detection and biological behavior research. SUMMARY

[0004] Therefore, the present application provides a fish motion visual simulation method, device and equipment for visualizing the fish motion state to provide accurate and reliable data for fishery management, acoustic detection and biological behavior research.

[0005] Specifically, the present application is realized by the following technical solutions:

[0006] The first aspect of the present application provides a fish motion visual simulation method, which comprises:

[0007] constructing a simulation system and configuring simulation parameters for the simulation system; the simulation system comprises a base array transceiver model and a fish motion model; the base array transceiver model is a circular arc array composed of a plurality of array elements;

[0008] simulating the actual motion trajectory of the fish based on the initial position of the fish and the fish motion model;

[0009] controlling each array element in the base array transceiver model to periodically transmit and receive signals according to a preset transmission and reception cycle; wherein each array element is in a transmission state for a preset time length in each transmission and reception cycle, transmits a detection signal, and is in a receiving state for the remaining time length, receives a return signal; the detection signal of each array element is composed of a sine modulated pulse coded by a Gold sequence;

[0010] In each transmission and reception cycle, the estimated position of the fish is estimated according to the detection signal of each array element and the return signal of each array element;

[0011] determining the trajectory deviation of the fish according to the estimated motion trajectory composed of a plurality of estimated positions and the actual motion trajectory.

[0012] The actual motion trajectory, the estimated motion trajectory and the trajectory deviation are used to generate a visual report reflecting the fish motion state, and the visual report is displayed to a user.

[0013] The second aspect of the present application provides a fish motion visual simulation device, the device comprising a simulation module, a control module, an estimation module, a determination module and a display module; wherein,

[0014] The simulation module is configured to construct a simulation system and configure simulation parameters for the simulation system; the simulation system comprises a base array transceiver model and a fish motion model; the base array transceiver model is a circular arc array composed of multiple array elements;

[0015] The simulation module is configured to simulate the actual motion trajectory of the fish based on the initial position of the fish and the fish motion model;

[0016] The control module is configured to control each array element in the base array transceiver model to periodically transmit and receive signals according to a preset transmission and reception cycle; wherein each array element is in a transmission state to transmit a detection signal in a preset time length of each transmission and reception cycle, and is in a receiving state to receive a return signal in the remaining time length; the detection signal of each array element is composed of a sine modulated pulse coded by a Gold sequence;

[0017] The estimation module is configured to estimate the estimated position of the fish according to the detection signal of each array element and the return signal of each array element in each transmission and reception cycle;

[0018] The determination module is configured to determine the trajectory deviation of the fish according to the estimated motion trajectory composed of multiple estimated positions and the actual motion trajectory;

[0019] The display module is configured to generate a visual report reflecting the fish motion state according to the actual motion trajectory, the estimated motion trajectory and the trajectory deviation, and display the visual report to a user.

[0020] The third aspect of the present application provides a fish motion visual simulation device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any one of the methods provided in the first aspect of the present application.

[0021] The fish motion visual simulation method, device and equipment provided by the application realize simulation and calculation of fish motion trajectory by constructing a base array transceiver model and a fish motion model. First, the actual motion trajectory of the fish is generated based on the initial position of the fish and the motion model, serving as a reference benchmark for subsequent comparative analysis. Then, through the arrangement of the base array in the form of a circular arc array, the array elements periodically emit and receive sinusoidal modulated pulses encoded by the GOLD sequence, and the mutual correlation calculation between the detection signal and the return signal is used to estimate the calculated position of the fish at each time. Further, by comparing the calculated trajectory formed by the multiple calculated positions with the actual trajectory obtained by simulation, not only the trajectory deviation of the fish motion process can be obtained, but also a visual report reflecting the motion state of the fish can be generated. The method can comprehensively reflect the motion state of the fish, intuitively display the difference between the calculated results and the actual situation, help verify the accuracy and reliability of the simulation system, and improve the analysis efficiency and visual effect in fish motion research and related applications. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The flowchart of the fish motion visual simulation method provided by the application;

[0023] Figure 2 The schematic diagram of the circular arc array shown by an exemplary embodiment of the application;

[0024] Figure 3 The timing diagram of each array element in each transmission and reception cycle shown by an exemplary embodiment of the application;

[0025] Figure 4 The schematic diagram of the trajectory comparison diagram shown by an exemplary embodiment of the application;

[0026] Figure 5 The schematic diagram of the fish motion trajectory tracking diagram shown by an exemplary embodiment of the application;

[0027] Figure 6 The schematic diagram of the trajectory deviation diagram shown by an exemplary embodiment of the application;

[0028] Figure 7 The schematic diagram of the speed change curve shown by an exemplary embodiment of the application;

[0029] Figure 8 The schematic diagram of the motion direction change diagram shown by an exemplary embodiment of the application;

[0030] Figure 9 The schematic diagram of the motion direction angle of the fish at a certain time shown by an exemplary embodiment of the application;

[0031] Figure 10 The schematic diagram of the detection signal shown by an exemplary embodiment of the application;

[0032] Figure 11 A schematic diagram of a detection signal and a return signal according to an exemplary embodiment of the present application;

[0033] Figure 12 A schematic diagram of a cross-correlation curve shown in an exemplary embodiment of the present application;

[0034] Figure 13 This is a schematic diagram of the structure of the first embodiment of the fish movement visualization simulation device provided by this application;

[0035] Figure 14 A schematic diagram of a fish movement visualization simulation device is provided for the purpose of an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0036] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with this application.

[0037] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a," "the," and "the" used in this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0038] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0039] Specific embodiments are given below to introduce the technical solutions of the present application in detail.

[0040] Figure 1 This is a flow chart of the first embodiment of the fish movement visualization simulation method provided by this application. Figure 1 The method provided in this embodiment may include:

[0041] S101, construct a simulation system, and configure simulation parameters for the simulation system; the simulation system comprises a base array transceiver model and a fish motion model; the base array transceiver model is a circular arc array composed of multiple array elements.

[0042] Specifically, the simulation system can run in a computer terminal or a distributed simulation platform, and can provide functions such as fish motion trajectory generation, signal transmission and reception, cross-correlation processing, and visualization display. The simulation system is implemented by software, and can be independently run or interfaced with external data acquisition equipment or underwater sensor systems.

[0043] It should be noted that the base array transceiver model is a circular arc array composed of multiple array elements. The circular arc array can provide a wide coverage angle in the horizontal direction, and at the same time form a certain spatial interval between the array elements, which is beneficial to improving the three-dimensional positioning accuracy and enhancing the echo signal resolution. In addition, compared with linear or regular rectangular arrays, the circular arc array can better reduce the blind area when tracking moving targets and improve the multi-target simultaneous monitoring capability.

[0044] Figure 2 For a schematic diagram of the circular arc array shown in an exemplary embodiment of the present application, please refer to Figure 2 , Figure 2 Figure (A) in the above is a top view of the circular arc array in the horizontal direction, Figure 2 Figure (B) in the above is a cross-sectional view of the circular arc array in the vertical direction, the circular arc array comprises 9 array elements; the 9 array elements are distributed in a circular arc shape in the horizontal direction, and are distributed in a triangular wave shape in the vertical direction. Among them, the circular arc shape distribution in the horizontal direction can provide a wide coverage angle, so that a certain spatial interval is formed between the array elements, thereby improving the three-dimensional positioning accuracy in the horizontal direction, reducing the blind area, and improving the multi-target simultaneous monitoring capability. The triangular wave shape distribution in the vertical direction is distributed in a staggered manner, which can improve the spatial resolution of the array elements in the vertical direction, improve the fish vertical position measurement accuracy, reduce the mutual interference between the array elements, enhance the target distinguishability, and optimize the overall array coverage range, so that the system can more comprehensively and accurately monitor the motion trajectory of the fish school in the water space.

[0045] It can be understood that the base array transceiver model is used to simulate the transmission and reception process of the sound wave signal, to detect the fish, and to calculate the position of the fish based on the detection result.

[0046] Further, the fish motion model is used to represent the motion law of the fish in the simulation scene. In one possible implementation, the fish motion model is established based on a random walk model, which can generate three-dimensional position coordinates of the fish to approximate the motion characteristics of the fish school in the actual water area.

[0047] Further, the simulation parameters configured for the simulation system are configured according to actual needs, and in this embodiment, the simulation parameters are not limited. In a possible implementation manner, the simulation parameters can include acoustic parameters, array parameters, signal parameters, and monitoring parameters, and specific contents and meanings of the simulation parameters are shown in Table 1:

[0048] Table 1 Simulation system parameters

[0049] S102, simulating an actual motion trajectory of the fish based on the initial position of the fish and the fish motion model.

[0050] Specifically, the initial position of the fish is set by a user according to actual needs, and in this embodiment, the initial position of the fish is not limited. In a specific implementation, the user can set the initial position of the fish in a simulation environment. The fish motion model is used to represent a motion law of the fish in the simulation scene. The fish motion model can be implemented based on random walk, circular motion, wave motion, or other algorithms conforming to actual behavior characteristics of the fish school. Optionally, in a possible implementation manner, it is assumed that the fish performs circular motion in a horizontal direction and performs fluctuation motion in a z direction, and the fish motion model can be represented as:

[0051] ;

[0052] ;

[0053] ;

[0054] wherein (x, y, z) represents an actual position of the fish, (x0, y0, z0) represents a center of a preset activity region, and radius represents a radius of the preset activity region. 、 、

[0055] Based on the initial position of the fish and the fish motion model, the real-time actual position of the fish can be calculated, and an actual motion trajectory composed of multiple actual positions is obtained.

[0056] It should be noted that the generated actual motion trajectory will serve as a reference for subsequent signal transmission and echo reception of the array transceiver model, supporting position calculation, trajectory deviation analysis, and motion visualization display of the fish.

[0057] S103, controlling each array element in the array transceiver model to periodically transmit and receive signals according to a preset transmission and reception cycle; wherein each array element is in a transmission state in a preset time length of each transmission and reception cycle to transmit a detection signal, and is in a receiving state in a remaining time length to receive a return signal; the detection signal of each array element is composed of a sine modulated pulse coded by a Gold sequence.

[0058] ​Figure 3 This is a timing diagram of each array element in each transmit and receive cycle shown in an exemplary embodiment of the present application. Figure 3 In each transmission and reception cycle, each array element goes through two stages, namely the transmission state and the reception state in the figure.

[0059] Specifically, within each transmit-receive cycle, the array elements are in a transmitting state for a predetermined duration, emitting detection signals. During the remaining duration, the array elements switch to a receiving state, receiving return signals reflected from targets in the water (such as fish). This periodic operation ensures that the system continuously tracks and monitors targets in the time domain.

[0060] Specifically, in one possible implementation, the detection signal uses a sinusoidally modulated pulse encoded with a Gold sequence. As a pseudo-random sequence, the Gold sequence has excellent autocorrelation characteristics and low cross-correlation characteristics, which can improve the anti-interference performance and target resolution of signal detection in complex underwater noisy environments. The sinusoidally modulated pulse provides a stable carrier frequency, enabling efficient signal propagation in water and suitable for cross-correlation detection. By combining these two, a detection signal with both periodicity and anti-interference properties can be generated, providing a reliable foundation for subsequent distance estimation and target positioning.

[0061] Furthermore, in the multi-element transmission scenario, the present application preferably uses the Gold sequence for encoding. The Gold sequence is generated by an XOR operation on a pair of preferred M sequences. It inherits the good autocorrelation characteristics of the M sequence and has better performance in cross-correlation characteristics. It is particularly suitable for independent encoding scenarios of multiple elements. Compared with a single M sequence, the Gold sequence can provide more encoding options. For the Gold sequence of order, we can generate Gold sequences use different sequences, ensuring that even with a large number of array elements, each element can be assigned an independent code that does not interfere with each other. Furthermore, the low cross-correlation between Gold sequences significantly reduces mutual interference between transmitted signals from different elements, thereby improving signal separation and positioning accuracy. Furthermore, the Gold sequence is well balanced, with a roughly equal number of "0s" and "1s" in the sequence. This property facilitates signal detection and balanced energy distribution, further enhancing the system's stability and reliability in complex underwater environments.

[0062] Specifically, this embodiment uses a total of 9 array elements. By using only a 5th-order Gold sequence, 9 sequences can be selected from the 33 available Gold sequences and assigned to each array element for independent encoding. This ensures sufficient mutual discrimination and strong anti-interference performance. In terms of signal form, the transmitted detection signal can be expressed as:

[0063]

[0064] in, is the Gold sequence, whose value is ; is the sinusoidal carrier frequency.

[0065] It is understandable that, in theory, The return signal received by each array element can be expressed as:

[0066]

[0067] in, is the distance decay factor, It's a formation element The actual distance to the fish, is the round-trip propagation delay of the signal, is the propagation delay of the signal in water, It is the superimposed ambient noise.

[0068] Specifically, as shown in Table 1, in this embodiment, the transmit / receive cycle is 2 seconds, of which the transmit duration is 20 milliseconds, and the remaining duration is used to receive the return signal. Furthermore, the carrier frequency of the detection signal is set to 25 kHz, and the sampling rate is 100 kHz to ensure the accuracy of signal acquisition and processing.

[0069] S104: In each transmitting and receiving cycle, the measured position of the fish is estimated based on the detection signal of each array element and the return signal of each array element.

[0070] Specifically, the detection signals emitted by each array element and the received return signals are used to determine the distance between the fish and each element. Combined with the known distribution of the elements in three-dimensional space, the fish's estimated position in the simulation scene is inferred based on the ranging results of multiple elements.

[0071] Optionally, in a possible implementation, the specific implementation process of this step may include:

[0072] Step 1: For each array element, discretize the detection signal and return signal of the array element according to the same sampling frequency to obtain a first discretization sequence corresponding to the detection signal and a second discretization sequence corresponding to the return signal.

[0073] Specifically, for the continuous detection signal emitted by the array element , and the continuous return signal received by the array element , according to the uniform sampling frequency (Unit: Hz) for sampling. The sampling time is ,in is an integer index. The discretized probe signal (i.e., the first discretized sequence) and the discretized return signal (i.e., the second discretized sequence) can be represented as:

[0074] ;

[0075] ;

[0076] wherein, is the number of discrete points contained in the first discretized sequence, is the number of discrete points contained in the second discretized sequence.

[0077] As described above, the receiving duration is greater than the transmitting duration, and the number of discrete points contained in the second discretized sequence is much greater than the number of discrete points contained in the first discretized sequence.

[0078] Step 2, determining the number of discrete points contained in the first discretized sequence, and determining the size of the sliding window according to the number; wherein the size of the sliding window is equal to the number.

[0079] Specifically, the number of discrete points contained in the first discretized sequence is , and the size of the sliding window is set to . For example, in a possible implementation, the number of discrete points contained in the first discretized sequence is 10, and at this time, the size of the sliding window is set to 10.

[0080] Step 3, taking the first discrete point in the second discretized sequence as the starting point of the sliding window, calculating the cross-correlation value of the subsequence corresponding to the sliding window and the first discretized sequence, and moving the sliding window according to a preset moving step, and calculating the cross-correlation value of the subsequence corresponding to the sliding window and the first discretized sequence again to obtain the cross-correlation value corresponding to each discrete point in the second discretized sequence.

[0081] The sliding window will slide on the second discretized sequence, and each time a subsequence with a length of is intercepted to perform cross-correlation operation with the first discretized sequence to ensure that the time domain length of the comparison is consistent with the transmitting signal.

[0082] In a specific implementation, in this step, the starting point of the sliding window is placed at the first discrete point of the second discretized sequence, a subsequence with a length of is intercepted to perform cross-correlation operation with the first discretized sequence. The specific calculation formula is as follows:

[0083] ;

[0084] wherein, is the first discretized sequence, is the second discretization sequence; is the starting index of the sliding window. As the sliding window moves according to the preset step size Move sequentially to obtain the cross-correlation values ​​corresponding to all possible positions in the second discretization sequence.

[0085] It should be noted that the specific value of the preset step size is set according to actual needs and is not limited in this embodiment. The following description is made taking the preset step size of 1 as an example.

[0086] Step 4: Find the maximum value of the mutual correlation value from the mutual correlation values ​​corresponding to the discrete points in the second discretization sequence, and estimate the measured distance between the array element and the fish based on the position of the maximum value.

[0087] Referring to the previous description, it can be understood that through step 3, the cross-correlation value corresponding to each discrete point can be calculated. In this step, first, the maximum value among multiple cross-correlation values ​​is found, and further, the measured distance between the array element and the fish is estimated based on the position of the maximum value.

[0088] In a specific implementation, optionally, in a possible implementation manner, estimating the measured distance between the array element and the fish based on the position of the maximum value includes:

[0089] (1) Determine a time delay based on the position and the sampling frequency.

[0090] Specifically, in the cross-correlation sequence Find the position corresponding to the maximum value:

[0091]

[0092] in, is the index corresponding to the maximum value in the cross-correlation value, The maximum value of the cross-correlation value is the index corresponding to the maximum value in the cross-correlation value, which reflects the time delay between the transmitted signal and the returned signal. The mathematical expression for calculating the delay is as follows:

[0093]

[0094] in, is the total delay of the return signal propagation, in seconds.

[0095] (2) Determine the measured distance based on the time delay and a preset sound wave propagation speed.

[0096] Specifically, combined with the speed of sound in water , the measured distance between the fish and the array element can be obtained, and its mathematical expression is as follows:

[0097]

[0098] Among them, d is the measured distance between the fish and the array element.

[0099] It should be noted that according to the above method, the measured distance between the fish and each array element can be calculated, which is recorded as , Take 1 to 9.

[0100] S305 , determining the measured position of the fish according to the position of each array element in the array transceiver model, the measured distance between each array element and the fish, and the preset movement range of the fish.

[0101] In a specific implementation, in one possible implementation manner, the specific implementation process of this step may include:

[0102] (1) Constructing an objective function; wherein the objective function optimizes the estimation of the fish position by minimizing the difference between the actual distance between the fish position and the position of each array element and the measured distance between each array element and the fish.

[0103] It should be noted that the position of each element in the array transceiver model is set according to actual needs and is not limited in this embodiment. The position of the array element is Furthermore, after the above steps, the distance between each array element and the fish is calculated as .

[0104] In this step, the ranging results of multiple array elements are integrated to construct the objective function as follows:

[0105] ;

[0106] in, is the estimated position of the fish to be measured, For the fish to the formation The actual distance, For the calculation of The measured distance between each array element and the fish, The objective function achieves the fusion of multi-element distance information by solving the minimum residual sum of squares between the fish position and the distance of each array element, thus obtaining the optimal measured position of the fish.

[0107] (2) Based on the preset movement range of the fish and the measured distance of each element fish, the objective function is iteratively solved by a specified optimization algorithm to obtain the measured position of the fish.

[0108] Further, during optimization solving, the preset fish movement range can be combined as a constraint condition to prevent solutions beyond the reasonable water range. The target function is iteratively solved by a specified optimization algorithm. The optimization algorithm can be a general nonlinear least square solving method. In this embodiment, an iterative nonlinear least square algorithm (such as Levenberg-Marquardt method) is selected, which is suitable for processing highly nonlinear and multi-dimensional estimation problems and can effectively converge to a global optimal solution.

[0109] S105, determining the trajectory deviation of the fish according to the calculated movement trajectory formed by the plurality of calculated positions and the actual movement trajectory.

[0110] Specifically, the calculated positions of the fish in each transmission and reception cycle obtained through the above steps The calculated positions of the plurality of transmission and reception cycles form the calculated movement trajectory of the fish Meanwhile, the actual movement trajectory obtained by using the fish movement model wherein is the actual position of the fish at the corresponding time point. According to the calculated trajectory and the actual trajectory, the trajectory deviation of the fish at each time point can be calculated, and the specific formula is as follows:

[0111]

[0112] wherein, is the trajectory deviation at the time point.

[0113] Further, the trajectory deviations at each time point are summarized to form an overall trajectory deviation index, for example, the average deviation or the maximum deviation can be calculated. Through this step, the system can quantify the deviation between the calculated trajectory and the actual movement trajectory, which provides a basis for subsequent simulation accuracy evaluation, model optimization or fish driving strategy adjustment, and can also serve as the core data basis for visualization and performance analysis.

[0114] S106, generating a visualization report reflecting the fish movement state according to the actual movement trajectory, the calculated movement trajectory and the trajectory deviation, and displaying the visualization report to the user.

[0115] Specifically, according to the actual movement trajectory , the calculated movement trajectory and the trajectory deviation, a visualization report reflecting the fish movement state can be generated. Through visualization, the user can intuitively understand the fish movement state, the calculation accuracy and the potential deviation distribution, which helps to adjust the simulation model parameters, optimize the calculation algorithm or develop more reasonable monitoring and fish driving strategies. At the same time, the visualization result can be exported as a report file, which is convenient for long-term monitoring and comparative analysis.

[0116] In a possible implementation, when the method is implemented, the generating a visualization report reflecting the fish movement state according to the actual movement trajectory, the calculated movement trajectory and the trajectory deviation comprises:

[0117] (1) generating a trajectory comparison diagram according to the actual movement trajectory and the calculated movement trajectory; the trajectory comparison diagram is used to simultaneously display the actual movement trajectory and the calculated movement trajectory in the same coordinate system.

[0118] (2) generating a fish movement trajectory tracking diagram according to the actual movement trajectory, the calculated movement trajectory and the positions of the array elements in the array transceiving model; the fish movement trajectory tracking diagram is used to simultaneously display the positions of the array elements, the actual movement trajectory and the calculated movement trajectory in the same coordinate.

[0119] (3) generating a trajectory deviation diagram according to the trajectory deviation.

[0120] (4) integrating the trajectory comparison diagram, the fish movement trajectory tracking diagram and the trajectory deviation diagram to generate the visualization report.

[0121] Specifically, Figure 4 For a schematic diagram of the trajectory comparison diagram shown in an example embodiment of the present application, please refer to Figure 4 , Figure 4 which shows the comparison between the actual movement trajectory and the calculated movement trajectory in the same coordinate system, including the overall path form of the actual trajectory and the calculated trajectory, and the identification of the actual starting point, the actual ending point, the calculated starting point and the calculated ending point. Through the diagram, the difference between the calculated trajectory and the actual trajectory can be clearly observed, and the accuracy of the positioning method in the spatial path restoration can be intuitively reflected. The visualization result not only helps to quantitatively analyze the trajectory deviation, but also provides intuitive reference for subsequent optimization of the fish movement model or the array parameters, thereby improving the verification and explainability of the system.

[0122] Figure 5 For a schematic diagram of the fish movement trajectory tracking diagram shown in an example embodiment of the present application, please refer to Figure 5 , Figure 5 which shows the position distribution of the array elements in the array transceiving model, the actual movement trajectory and the calculated movement trajectory of the fish, and the actual position and the calculated position at different time points, and is accompanied by the identification of the movement speed. Through the three-dimensional tracking diagram, the user can intuitively understand the relationship between the array distribution and the fish movement in the spatial dimension, and clearly compare the deviation between the calculated trajectory and the actual trajectory. The visualization method not only helps to analyze the accuracy performance of the positioning algorithm in the three-dimensional space, but also provides intuitive reference for further optimization of the array arrangement and the signal processing method, thereby improving the reliability and applicability of the overall system.

[0123] Figure 6 This is a schematic diagram of a trajectory deviation diagram shown in an exemplary embodiment of the present application, please refer to Figure 6 This graph allows for intuitive observation of the trajectory error fluctuations at different time points, reflecting the changing pattern of the deviation between the measured and actual positions. This visualization helps analyze the stability of the positioning algorithm's accuracy during dynamic processes, providing a reference for subsequent model optimization and parameter adjustments.

[0124] Furthermore, in a preferred implementation, after estimating the measured position of the fish based on the detection signal of each array element and the return signal of each array element, the method further includes:

[0125] (1) Based on the estimated position of the fish at the current moment and the estimated position of the fish at the previous moment, determine the X-direction velocity component of the fish at the current moment, the Y-direction velocity component of the fish at the current moment, and the Z-direction velocity component of the fish at the current moment.

[0126] Specifically, the current position of the fish is , the position of the fish at the last moment is The time interval between two measurements is The fish is direction, Direction and The X-direction velocity component, Y-direction velocity component, and Z-direction velocity component of the direction are:

[0127]

[0128]

[0129]

[0130] in, 、 、 The fish are direction, Direction and The X-direction velocity component, Y-direction velocity component, and Z-direction velocity component in the direction, is the sampling time interval.

[0131] (2) Calculate the total speed of the fish at the current moment based on the X-direction speed component, the Y-direction speed component, and the Z-direction speed component.

[0132] Specifically, the total speed of the fish is calculated based on the X-axis velocity component, the Y-axis velocity component, and the Z-axis velocity component. Specifically, the total speed is obtained using the Euclidean distance formula:

[0133]

[0134] wherein, is the current velocity of the fish in three-dimensional space.

[0135] (3) determining the horizontal direction angle of the fish in the horizontal direction at the current time according to the X-direction velocity component and the Y-direction velocity component.

[0136] Specifically, the horizontal direction angle of the fish in the XY plane is calculated by the following formula:

[0137]

[0138] wherein, is the horizontal direction angle of the fish in the horizontal direction, , are the X-direction velocity component and the Y-direction velocity component respectively.

[0139] (4) calculating the pitch angle of the fish in the vertical direction at the current time according to the X-direction velocity component, the Y-direction velocity component and the Z-direction velocity component.

[0140] Specifically, the pitch angle of the fish is calculated according to the velocity components in three directions, which is used to represent the motion posture of the fish in the vertical direction. Specifically, the pitch angle is calculated by the following formula:

[0141]

[0142] wherein, is the pitch angle of the fish in the vertical direction, is the vertical direction velocity, and the pitch angle reflects the tendency of the fish in the up-and-down motion.

[0143] (5) generating the speed change curve of the fish according to the velocity of the fish at each time, and generating the motion direction change graph of the fish according to the horizontal direction angle of the fish in the horizontal direction at each time and the pitch angle of the fish in the vertical direction at each time.

[0144] Specifically, the velocity change curve of the fish is generated by the velocity values calculated at each time, and the tendency of the change of the fish speed with time can be intuitively displayed through the velocity change curve. Further, the motion azimuth angle and the pitch angle are combined to generate the motion direction change graph of the fish, which can display the motion direction change of the fish at different time points in three-dimensional or two-dimensional coordinate system.

[0145] Specifically, Figure 7 is a schematic diagram of the speed change curve shown in an example embodiment of the present application, please refer to Figure 7, the horizontal axis represents time, and the vertical axis represents the instantaneous speed of the fish, and the curve depicts the speed change of the fish at different time points. Through the graph, the user can intuitively understand the acceleration, deceleration, and motion state change law of the fish.

[0146] Figure 8 For a schematic diagram of the motion direction change graph shown in an exemplary embodiment of the present application, please refer to Figure 8 , which shows the change of the horizontal direction angle of the fish in the horizontal direction and the pitch angle of the fish in the vertical direction over time, where the horizontal axis represents time, and the vertical axis represents the horizontal direction angle and the pitch angle, respectively. Through the graph, the user can intuitively observe the motion direction change law of the fish at different time points and understand the dynamic behavior of the fish in the horizontal and vertical dimensions, providing visual basis for analyzing the fish school motion pattern, calculating the motion trajectory, and verifying the accuracy of the positioning algorithm.

[0147] Further, Figure 9 For a schematic diagram of the motion direction angle of the fish at a certain time point, please refer to Figure 9 , which is used to intuitively show the numerical value of the horizontal direction angle of the fish in the horizontal direction and the pitch angle of the fish in the vertical direction at the current time point.

[0148] It should be noted that, Figure 4 , Figure 5 and Figure 9 can be displayed in linkage, i.e. when the fish moves once in the motion trajectory tracking graph ( Figure 5 ), the trajectory comparison graph ( Figure 4 ) and the motion direction angle ( Figure 9 ) are updated synchronously, and the speed, direction and calculation deviation of the current position of the fish are reflected accordingly. Through this linkage display mode, the user can simultaneously observe the real-time position, motion trajectory and speed direction change of the fish in space, thereby more intuitively understanding the motion behavior of the fish and the array measurement relationship, improving the analysis accuracy and interactive experience, and facilitating the discovery of calculation deviation, adjustment of array parameters or optimization of positioning algorithm, realizing the integration of system visualization, analysis and verification.

[0149] (6) displaying the speed change curve and the motion direction change graph to the user.

[0150] Specifically, the generated speed change curve and motion direction change graph are displayed to the user, supporting zooming in, zooming out and rotating for viewing, so that the user can intuitively analyze the motion state and trend of the fish, providing visual data support for subsequent fish school behavior research, ecological monitoring or breeding management.

[0151] The method provided by the embodiment realizes accurate monitoring and trajectory calculation of fish movement state by combining the array transceiver model, the Gold sequence coded sinusoidal modulation pulse detection signal and the fish movement model, and has at least the following advantages:

[0152] (1) Improve simulation reality, reduce artificial intervention and error: By introducing the array transceiver model in the simulation system and using the circular arc array composed of multiple array elements for signal transmission and reception, the actual underwater acoustic detection environment can be more realistically simulated, avoiding the problem that the traditional method relies only on a simplified model and has a large difference with the real detection situation. In addition, manual measurement and judgment are not required, avoiding human operation errors and improving the reliability and stability of monitoring.

[0153] (2) Improve positioning and trajectory calculation accuracy: Using the spatial distribution of multiple array elements and the characteristics of Gold sequence coded signals, combined with the target function minimization optimization algorithm, the calculated position and movement trajectory of the fish are accurately calculated, effectively reducing the measurement error in the complex underwater noise environment, and ensuring the accuracy of the monitoring data.

[0154] (3) Support real-time visual analysis and multi-chart linkage: By generating trajectory comparison chart, fish movement trajectory tracking chart and speed direction chart, multi-dimensional visualization of fish school movement state is realized. When observing the changes of fish school movement trajectory, the three types of charts are updated in linkage, so that the user can more intuitively understand the movement behavior of the fish and the calculation deviation. This linkage display not only enhances the data interpretability, but also facilitates quick detection of abnormal behavior, improves operation decision-making efficiency, supports zoom-in and zoom-out viewing, and realizes fine-grained analysis.

[0155] (4) Improve monitoring efficiency: The system can process data of multiple array elements at the same time, quickly generate fish calculation position and trajectory deviation analysis report, avoid the time-consuming process of traditional manual analysis, and is suitable for real-time monitoring and long-term water ecological management.

[0156] (5) Wide application value: The method of the present application can provide scientific basis for fishery management, provide auxiliary verification means for underwater acoustic detection, and provide reliable data support for fish behavior research, and has strong practicality and promotion value.

[0157] The fish motion visual simulation method provided in the application can realize accurate monitoring and trajectory calculation of fish school motion in underwater environment through the array transceiving model and the fish motion model. First, a circular arc array composed of multiple elements is set, and each element is controlled to emit a sine modulated pulse signal coded by Gold sequence, then the fish body reflection return signal is efficiently collected in a complex underwater noise environment, and the mutual correlation analysis method is used to process the return signal and the transmitted signal, so as to accurately estimate the calculation distance between each element and the fish. Then, the three-dimensional calculation position of the fish is obtained through the iteration calculation of the target function minimization and optimization algorithm combined with the spatial position of each element and the preset fish motion range, and the calculation motion trajectory is constructed. Especially, by comparing the actual motion trajectory and the calculation motion trajectory, and generating trajectory deviation analysis, the calculation accuracy can be intuitively evaluated. Further, by generating trajectory comparison graph, fish motion trajectory tracking graph and speed direction graph, and realizing three graph linkage display, the user can observe the real-time change of the fish school motion state in the three-dimensional view, and can zoom in or zoom out for viewing, thereby enhancing the data interpretation and decision assistance capability. The method significantly improves the accuracy and reliability of fish school motion monitoring, especially in dynamic water area and multi-fish school environment, which can provide visual real-time feedback, and provide efficient and intuitive technical support for underwater breeding monitoring, scientific research experiment and water area ecological management.

[0158] Optionally, in a possible implementation, the method further includes:

[0159] (1) For each transceiving cycle, a graphical representation of the detection signal of each element is generated according to the detection signal of each element.

[0160] Figure 10 For the schematic diagram of the detection signal shown in an exemplary embodiment of the application, please refer to Figure 10 , Figure 10 (A) of FIG. is a schematic diagram of the complete detection signal, Figure 10 (B) of FIG. is a partial schematic diagram of the detection signal.

[0161] (2) A graphical representation of the return signal of each element is generated according to the return signal of each element.

[0162] Figure 11 For the schematic diagram of the detection signal and the return signal shown in an exemplary embodiment of the application, please refer to Figure 11 , Figure 11 (A) of FIG. is a schematic diagram of the detection signal, Figure 11 (B) of FIG. is a schematic diagram of the return signal received by the element. In each transceiving cycle, each element experiences two stages of transmission and reception. This periodic working mode can ensure that the system continuously tracks and monitors the target in the time domain.

[0163] (3) For each array element, according to the time delay corresponding to each discrete point in the second discrete sequence and the cross-correlation value corresponding to the discrete point, a cross-correlation value-time delay relationship curve is generated, and a cross-correlation relationship curve corresponding to the array element is obtained.

[0164] Figure 12 For a schematic diagram of the cross-correlation relationship curve shown in an exemplary embodiment of the present application, please refer to Figure 12 . The figure intuitively shows the correspondence between the cross-correlation value and the time delay, improving the understanding and verification of the distance estimation process.

[0165] (4) For each array element, a transceiving performance visualization report corresponding to the array element in the transceiving cycle is generated by integrating the graphical representation of the detection signal of the array element, the graphical representation of the return signal of the array element, and the cross-correlation relationship curve corresponding to the array element.

[0166] In specific implementation, the graphical representation of the detection signal of the array element, the graphical representation of the return signal of the array element, and the cross-correlation relationship curve corresponding to the array element can be integrated together to generate the transceiving performance visualization report corresponding to the array element in the transceiving cycle.

[0167] (5) The transceiving performance visualization report is displayed to the user.

[0168] As can be understood from the foregoing description, by graphically representing the detection signal, return signal and cross-correlation relationship of each array element, and combining the speed change curve and motion direction change diagram of the fish for visualization display, the user can intuitively master the change law of the motion trajectory, speed and motion direction of the fish, and clearly understand the performance of each array element in the transceiving process. This multi-level and intuitive visualization method not only enhances the interpretability and reliability of the simulation results, but also facilitates the discovery of abnormal motion or signal deviation, improves the research efficiency and accuracy of data analysis, and has important application value for fishery management, underwater acoustic detection and biological behavior research.

[0169] Corresponding to the foregoing embodiment of the fish motion visualization simulation method, the present application also provides an embodiment of a fish motion visualization simulation device.

[0170] Figure 13 For a structural schematic diagram of the fish motion visualization simulation device embodiment provided by the present application, please refer to Figure 13 . The device provided in this embodiment comprises a simulation module 1301, a control module 1302, a calculation module 1303, a determination module 1304 and a display module 1305; wherein,

[0171] The simulation module 1301 is configured to construct a simulation system and configure simulation parameters for the simulation system; the simulation system comprises a base array transceiver model and a fish motion model; the base array transceiver model is a circular arc array composed of multiple array elements;

[0172] The simulation module 1301 is configured to simulate an actual motion trajectory of the fish based on an initial position of the fish and the fish motion model.

[0173] The control module 1302 is configured to control each array element in the base array transceiver model to periodically transmit and receive signals according to a preset transmission and reception cycle; in each preset time length of each transmission and reception cycle, each array element is in a transmission state to transmit a detection signal, and is in a receiving state to receive a return signal in the remaining time length; the detection signal of each array element is composed of sine modulation pulses coded by a Gold sequence.

[0174] The measurement module 1303 is configured to estimate a measurement position of the fish according to the detection signal of each array element and the return signal of each array element in each transmission and reception cycle.

[0175] The determination module 1304 is configured to determine a trajectory deviation of the fish according to a measurement motion trajectory composed of multiple measurement positions and the actual motion trajectory.

[0176] The display module 1305 is configured to generate a visual report reflecting a motion state of the fish according to the actual motion trajectory, the measurement motion trajectory and the trajectory deviation, and display the visual report to a user.

[0177] The device of the embodiment can be used to execute the steps of the method embodiment, and the specific implementation principles and implementation processes are similar, which will not be described here. Figure 1 The steps of the method embodiment are similar to the specific implementation principles and implementation processes, which will not be described here.

[0178] Figure 14 FIG. 1 shows a schematic diagram of a fish motion visual simulation device according to an example embodiment of the present application. Figure 14 The fish motion visual simulation device provided by the present application also comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of any method provided by the first aspect of the present application when executing the program.

[0179] The implementation processes of the functions and roles of the units in the above device are specifically described in the implementation processes of the corresponding steps in the above method, which will not be described here.

[0180] For the apparatus embodiment, since it basically corresponds to the method embodiment, the relevant part can be seen from the part of the method embodiment. The apparatus embodiment described above is only illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the application according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0181] The above only describes the preferred embodiments of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A fish movement visualization simulation method, characterized in that: The method comprises: Constructing a simulation system and configuring simulation parameters for the simulation system; the simulation system includes a base array transceiver model and a fish movement model; the base array transceiver model is a circular array composed of multiple array elements; simulating the actual movement trajectory of the fish based on the initial position of the fish and the fish movement model; Controlling each element in the array transceiver model to periodically transmit and receive signals according to a preset transmit / receive cycle; wherein each element is in a transmitting state for the preset duration of each transmit / receive cycle, transmitting a detection signal, and is in a receiving state for the remaining duration, receiving a return signal; the detection signal of each element is composed of sinusoidally modulated pulses encoded with a Gold sequence; In each transmission and reception cycle, the fish's measured position is estimated based on the detection signal of each array element and the return signal of each array element; Determining a fish track deviation based on a measured motion track formed by a plurality of measured positions and the actual motion track; A visual report reflecting the movement state of the fish is generated according to the actual movement trajectory, the measured movement trajectory and the trajectory deviation, and the visual report is displayed to the user.

2. The method according to claim 1, characterized in that After estimating the measured position of the fish based on the detection signals of each array element and the return signals of each array element, the method further includes: Determine the X-direction velocity component of the fish in the X direction at the current moment, the Y-direction velocity component of the fish in the Y direction at the current moment, and the Z-direction velocity component of the fish in the Z direction at the current moment based on the measured position of the fish estimated at the current moment and the measured position of the fish estimated at the previous moment; Calculate the total speed of the fish at the current moment based on the X-direction speed component, the Y-direction speed component, and the Z-direction speed component; Determine the horizontal direction angle of the fish in the horizontal direction at the current moment according to the X-direction velocity component and the Y-direction velocity component; Calculate the vertical pitch angle of the fish at the current moment based on the X-direction velocity component, the Y-direction velocity component, and the Z-direction velocity component; Generate a fish speed change curve based on the total speed of the fish at each moment, and generate a fish movement direction change diagram based on the horizontal direction angle of the fish at each moment and the pitch angle of the fish at each moment; The speed change curve and the motion direction change diagram are displayed to the user.

3. The method according to claim 1, characterized in that The generating of a visual report reflecting the movement state of the fish according to the actual movement trajectory, the calculated movement trajectory and the trajectory deviation comprises: generating a trajectory comparison graph based on the actual motion trajectory and the measured motion trajectory; the trajectory comparison graph is used to simultaneously display the actual motion trajectory and the measured motion trajectory in the same coordinate system; Generate a fish motion trajectory tracking diagram based on the actual motion trajectory, the calculated motion trajectory, and the position of each array element in the array transceiver model; the fish motion trajectory tracking diagram is used to simultaneously display the position of each array element, the actual motion trajectory, and the calculated motion trajectory under the same coordinate system; generating a trajectory deviation map according to the trajectory deviation; The trajectory comparison graph, the fish movement trajectory tracking graph and the trajectory deviation graph are integrated to generate the visualization report.

4. The method according to claim 1, wherein The method of estimating the measured position of the fish based on the detection signal of each array element and the return signal of each array element includes: For each array element, discretize the detection signal and return signal of the array element according to the same sampling frequency to obtain a first discretization sequence corresponding to the detection signal and a second discretization sequence corresponding to the return signal; Determining the number of discrete points included in the first discretization sequence, and determining the size of a sliding window according to the number; wherein the size of the sliding window is equal to the number; Taking the first discrete point in the second discretization sequence as the starting point of a sliding window, calculating a mutual correlation value between a subsequence corresponding to the sliding window and the first discretization sequence, moving the sliding window according to a preset moving step size, and again calculating a mutual correlation value between the subsequence corresponding to the sliding window and the first discretization sequence to obtain a mutual correlation value corresponding to each discrete point in the second discretization sequence; Finding a maximum value of the mutual correlation value from the mutual correlation values ​​corresponding to the discrete points in the second discretization sequence, and estimating the measured distance between the array element and the fish based on the position of the maximum value; The measured position of the fish is determined according to the position of each array element in the array transceiver model, the measured distance between each array element and the fish, and the preset movement range of the fish.

5. The method according to claim 4, characterized in that Determining the measured position of the fish based on the position of each array element in the array transceiver model, the measured distance between each array element and the fish, and the preset movement range of the fish includes: Constructing an objective function; wherein the objective function optimizes the estimation of the fish position by minimizing the difference between the actual distance between the fish position and the position of each array element and the measured distance between each array element and the fish; Based on the preset movement range of the fish and the measured distance of each array element fish, the objective function is iteratively solved by a specified optimization algorithm to obtain the measured position of the fish.

6. The method according to claim 4, characterized in that The method further comprises: For each transmit / receive cycle, generating a graphical representation of the detection signal of each array element based on the detection signal of each array element; generating a graphical representation of the return signal of each array element according to the return signal of each array element; For each array element, generating a relationship curve between the cross-correlation value and the time delay based on the time delay corresponding to each discrete point in the second discretization sequence and the cross-correlation value corresponding to the discrete point, thereby obtaining a cross-correlation relationship curve corresponding to the array element; For each array element, generate a visualization report of the transmit / receive performance of the array element corresponding to the transmit / receive cycle based on the graphical representation of the detection signal of the array element, the graphical representation of the return signal of the array element, and the cross-correlation curve corresponding to the array element; The visual report of the sending and receiving performance is presented to the user.

7. The method according to claim 4, characterized in that The estimating the measured distance between the array element and the fish according to the position of the maximum value includes: determining a time delay according to the position and the sampling frequency; The measured distance is determined according to the time delay and a preset sound wave propagation speed.

8. The method according to claim 1, characterized in that The arc array includes 9 array elements; the 9 array elements are distributed in an arc shape in the horizontal direction and in a triangular wave shape in the vertical direction.

9. A fish movement visualization simulation device, characterized in that: The device includes a simulation module, a control module, a calculation module, a determination module and a display module; wherein, The simulation module is used to construct a simulation system and configure simulation parameters for the simulation system; the simulation system includes a base array transceiver model and a fish movement model; the base array transceiver model is a circular array composed of multiple array elements; The simulation module is used to simulate the actual movement trajectory of the fish based on the initial position of the fish and the fish movement model; The control module is configured to control each array element in the array transceiver model to periodically transmit and receive signals according to a preset transmit / receive cycle. Each array element is in a transmitting state for a preset duration of each transmit / receive cycle, transmitting a detection signal, and is in a receiving state for the remaining duration, receiving a return signal. The detection signal of each array element is composed of sinusoidally modulated pulses encoded with a Gold sequence. The calculation module is used to estimate the measured position of the fish based on the detection signal of each array element and the return signal of each array element in each transmission and reception cycle; The determining module is configured to determine a fish track deviation based on a measured motion track formed by a plurality of measured positions and the actual motion track; The display module is used to generate a visual report reflecting the movement status of the fish based on the actual movement trajectory, the measured movement trajectory and the trajectory deviation, and display the visual report to the user.

10. A fish movement visualization simulation device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when executing the program.

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