An underwater acoustic communication signal level simulation evaluation method, device and equipment

Abstract

This application relates to the field of underwater acoustic communication technology, and discloses a method, apparatus, and device for signal-level simulation evaluation of underwater acoustic communication. The method includes: acquiring configuration parameters to generate an original transmitted signal; constructing an underwater acoustic channel transmission response model characterizing physical propagation characteristics; simulating the signal and superimposing noise to obtain the original received signal; extracting intermediate parameters characterizing the physical propagation state during the simulation process to generate visualized data of the channel transmission process; processing the received signal to recover demodulated data; and performing performance evaluation based on the demodulated data, the original received signal, and the transmitted signal. This invention, by constructing a channel model containing physical propagation characteristics and extracting intermediate parameters to generate visualized data, quantifies the internal physical state of the channel, improves the interpretability of the model, and provides a physical basis for optimization algorithms. Simultaneously, the multi-dimensional evaluation system, combined with demodulated data and signal waveforms, achieves a comprehensive performance characterization from the physical layer to the link layer, significantly improving the credibility and guiding value of the simulation evaluation.

Description

Technical Field

[0001] This application relates to the field of underwater acoustic communication technology, specifically to a method, apparatus, and equipment for underwater acoustic communication signal level simulation evaluation. Background Technology

[0002] Underwater acoustic communication is a key technology for realizing long-distance underwater information transmission and is widely used in marine resource exploration, underwater environmental monitoring, and national defense security. Due to the characteristics of the underwater acoustic environment, such as strong noise, high attenuation, and complex multipath effects, conducting on-site sea trials is not only costly and time-consuming, but also greatly constrained by marine meteorological conditions and uncontrollable environmental factors.

[0003] Therefore, in the early stages of system development, computer simulation technology is typically used to pre-verify and evaluate the communication scheme to reduce R&D risks. While existing underwater acoustic communication simulation technologies possess some signal simulation capabilities and can assist system design to a certain extent, they still have many limitations. On the one hand, existing simulation technologies are insufficient in terms of channel modeling fidelity and parameter configuration flexibility. Traditional simulation methods often use simplified channel models, making it difficult to accurately simulate the complex processes of multi-physics coupling, such as multipath effects, sound velocity gradients, and marine environmental noise. This results in low similarity between the generated simulated signals and real underwater signals in terms of statistical characteristics, affecting the reliability of the simulation results. On the other hand, existing technologies are lacking in visualization of the simulation process and performance evaluation. Most simulation tools only focus on the final communication results, making it impossible for researchers to intuitively trace the specific causes of signal distortion. Summary of the Invention

[0004] This paper addresses the problems in underwater acoustic communication simulation technology, such as low channel modeling fidelity, insufficient parameter configuration flexibility, lack of visualization of the simulation process, and single performance evaluation dimension. Furthermore, the lack of visualization of the simulation process and performance evaluation dimension makes it difficult to intuitively trace the cause of signal distortion.

[0005] In a first aspect, embodiments of this application provide a method for simulating and evaluating underwater acoustic communication signal levels, the method comprising: Obtain the simulation configuration parameters and generate the original transmission signal based on the simulation configuration parameters; Based on the simulation configuration parameters, an underwater acoustic channel transmission response model characterizing the physical propagation characteristics of the channel is constructed. The underwater acoustic channel transmission response model is then used to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal. Intermediate parameters characterizing the physical propagation state of the channel are extracted during the channel transmission simulation, and visual data characterizing the channel transmission process are generated based on the intermediate parameters. The original received signal is processed to recover the demodulated data; Communication performance is evaluated based on demodulated data, raw received signals, and raw transmitted signals.

[0006] In conjunction with the first aspect, in one implementation, the step of constructing an underwater acoustic channel transmission response model characterizing the physical propagation characteristics of the channel based on simulation configuration parameters, and using the underwater acoustic channel transmission response model to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal, includes: Calculate the sound wave propagation path and acoustic parameters based on the simulation configuration parameters; A linear time-varying impulse response model for the underwater acoustic channel is constructed based on the acoustic ray parameters. The original transmitted signal is convolved with a linear time-varying impulse model, and environmental composite noise is superimposed on the convolved and distorted signal to obtain the original received signal.

[0007] In conjunction with the first aspect, in one implementation, the calculation of the sound wave propagation path and ray parameters based on simulation configuration parameters includes: The sound velocity distribution at different depths is obtained by using a layered calculation method based on the sound velocity profile in the simulation configuration parameters. Sound wave propagation path tracing is performed using ray theory and sound velocity distribution to obtain sound ray parameters.

[0008] In conjunction with the first aspect, in one implementation, the step of extracting intermediate parameters characterizing the physical propagation state of the channel during channel transmission simulation and generating visual data characterizing the channel transmission process based on the intermediate parameters includes: The trajectory of each ray is dynamically drawn based on the sound wave propagation path and ray parameters; Extract the time-varying amplitude and delay parameters from the acoustic parameters, and plot the dynamic curve of the channel impulse response over time based on the time-varying amplitude and delay parameters; The dynamic signal-to-noise ratio (SNR) within the sliding time window is calculated based on the acoustic parameters, and the SNR changes are presented using a line graph.

[0009] In conjunction with the first aspect, in one embodiment, the step of processing the original received signal to recover demodulated data includes: Automatic gain control is performed on the original received signal to output an equalized received signal; The noise in the equalized received signal is filtered out by a bandpass filter module to obtain the filtered signal. The filtered signal is subjected to multi-stage synchronization processing to obtain a synchronization signal; The synchronization signal is demodulated and decoded, and the binary received content is output as the demodulated data.

[0010] In conjunction with the first aspect, in one embodiment, after processing the original received signal to recover the demodulated data, the method further includes: The original received signal is analyzed using time-frequency analysis methods to generate a time-frequency diagram; Based on the demodulated data, a scatter plot of the baseband constellation is drawn, and time-domain waveforms containing the original transmitted signal, the original received signal, and the demodulated data are output in parallel on the same time axis.

[0011] In conjunction with the first aspect, in one implementation, the communication performance evaluation based on demodulated data, the original received signal, and the original transmitted signal includes: Calculate the signal distortion ratio, channel fading depth, and bit error rate based on the demodulated data, the original received signal, and the original transmitted signal. The evaluation results for signal distortion, channel characteristics, and communication quality are generated based on the signal distortion ratio, channel fading depth, and bit error rate.

[0012] In conjunction with the first aspect, in one embodiment, the environmental composite noise includes: ship radiated noise, marine biological noise, and turbulence noise.

[0013] Secondly, embodiments of this application provide an underwater acoustic communication signal level simulation and evaluation device, the underwater acoustic communication signal level simulation and evaluation device comprising: A signal generation module is used to acquire simulation configuration parameters and generate an original transmission signal based on the simulation configuration parameters; The channel simulation module is used to construct an underwater acoustic channel transmission response model that characterizes the physical propagation characteristics of the channel based on simulation configuration parameters, and to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise using the underwater acoustic channel transmission response model. The process visualization module is used to extract intermediate parameters that characterize the physical propagation state of the channel during the channel transmission simulation process, and generate visualization data characterizing the channel transmission process based on the intermediate parameters. A receiving and processing module is used to process the original received signal and recover the demodulated data. The performance evaluation module is used to perform a multi-dimensional evaluation of communication performance based on the demodulated data, the original received signal, and the original transmitted signal.

[0014] Thirdly, embodiments of this application provide an underwater acoustic communication signal level simulation and evaluation device, the underwater acoustic communication signal level simulation and evaluation device including a processor, a memory, and an underwater acoustic communication signal level simulation and evaluation program stored in the memory and executable by the processor, wherein when the underwater acoustic communication signal level simulation and evaluation program is executed by the processor, it implements the steps of the underwater acoustic communication signal level simulation and evaluation method as described in any of the above claims.

[0015] The beneficial effects of the technical solutions provided in this application include: This invention breaks through the traditional "black box" mode of simulation, which only focuses on input and output results, by constructing a channel transmission response model that incorporates physical propagation characteristics and extracting intermediate parameters to generate visualized data during the simulation process. This design allows for the quantitative presentation of the physical propagation state within the channel, not only improving the interpretability of the simulation model but also providing a clear physical basis for subsequent optimization of communication algorithms. Simultaneously, the multi-dimensional evaluation system, combined with demodulated data and signal waveforms, achieves a comprehensive performance characterization from the physical layer to the link layer, significantly improving the credibility and guiding value of the simulation evaluation. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the underwater acoustic communication signal level simulation evaluation method of this application; Figure 2 This is a time-domain waveform diagram of the transmitted signal in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 3 This is a three-dimensional display diagram of the sound ray trajectory in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 4 This is a dynamic diagram of the channel impulse response in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 5 This is a dynamic change diagram of the signal-to-noise ratio in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 6 This is a time-frequency diagram of the received signal in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 7 This is a 16QAM demodulation constellation diagram in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 8 This is a comparison diagram of the original and processed signals in one embodiment of the underwater acoustic communication signal level simulation evaluation method of this application; Figure 9 This is a schematic diagram of the hardware structure of the underwater acoustic communication signal level simulation and evaluation device involved in the embodiments of this application. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0018] This paper addresses the problems in underwater acoustic communication simulation technology, such as low channel modeling fidelity, insufficient parameter configuration flexibility, lack of visualization of the simulation process, and single performance evaluation dimension. Furthermore, the lack of visualization of the simulation process and performance evaluation dimension makes it difficult to intuitively trace the cause of signal distortion.

[0019] In a first aspect, embodiments of this application provide a method for simulating and evaluating underwater acoustic communication signal levels, the method comprising: Step S1: Obtain simulation configuration parameters and generate the original transmission signal based on the simulation configuration parameters.

[0020] Understandably, by flexibly configuring parameters, a raw transmission signal that meets the user's needs can be generated, providing an input basis for subsequent simulations.

[0021] Step S1 above includes: Step S1a: Multi-dimensional parameter configuration.

[0022] Specifically, a modular parameter configuration system is established, supporting user-defined core parameters, with configuration results presented as a simulation configuration parameter vector. It means that, among them, Email content Supports multiple data types including text, binary data streams, and voice signals. Text signals must first be converted into binary sequences. ; Equipment parameters : Including the depth z of the transmitting transducer t Receiver transducer depth z r Transmit and receive distance R Transducer directivity coefficient, etc.; Transmit power The configurable range is 10W to 1000W, and linear adjustment is supported. Modulation method It supports multiple mainstream modulation methods such as FSK (Frequency Shift Keying), PSK (Phase Shift Keying), and QAM (Quadrature Amplitude Modulation), which users can choose as needed; Frequency bandwidth Configure the signal carrier frequency and bandwidth; the default range is 1kHz to 20kHz. Channel scenario : Preset typical scenarios such as shallow sea, deep sea, nearshore, and open sea, or customize parameters such as sound velocity profile and ocean noise intensity.

[0023] It is worth noting that step S1a aims to provide accurate environmental boundary conditions and initial calculation parameters for the subsequent underwater acoustic channel transmission simulation (step S2). The parameter configuration process supports preset typical underwater acoustic scenarios such as shallow sea, deep sea, nearshore, and open sea areas, and allows customization of core variables such as sound velocity profiles and ocean noise intensity according to actual task requirements. These configuration parameters will directly serve as the physical calculation basis for ray propagation path tracing, time-varying channel impulse response construction, and environmental composite noise superposition in step S2, thereby ensuring the environmental realism of the entire simulation process.

[0024] Step S1b: Generating the original transmitted signal.

[0025] Specifically, based on the simulation configuration parameter vector in step S1a The original baseband signal is generated and modulation is completed. The specific process is as follows: Step A, Baseband Signal Generation: This involves generating the binary sequence... Encode the sequence (e.g., CRC encoding, convolutional encoding) to obtain the encoded sequence. The baseband signal is then generated by a shaping filter (such as a raised cosine filter). :

[0026] in, The impulse response of the shaping filter, The symbol period.

[0027] Step B, Modulation Signal Generation: The system dynamically switches modulation modes by sensing the dynamic characteristics of the current underwater acoustic channel (such as evaluating delay spread, Doppler shift, and signal-to-noise ratio) or according to the semantic priority of the current formation task. The modulation modes include FSK, PSK, and QAM modes; among which, FSK mode:

[0028] in, For signal amplitude, This is the initial phase.

[0029] Understandably, when performing high-priority tactical actions (such as emergency obstacle avoidance or formation reconfiguration) or when the channel is extremely degraded, it can automatically downgrade to FSK mode, sacrificing rate to ensure absolutely reliable access to control semantics.

[0030] PSK mode:

[0031] in, For the phase corresponding to the encoded symbol (such as in BPSK) , ); It is worth noting that during regular formation coordinated cruise, PSK mode can be used to maintain a balance between channel resources and transmission capacity.

[0032] QAM mode:

[0033] in, / These are the orthogonal amplitude components corresponding to the encoded symbols.

[0034] Understandably, when high-resolution situational awareness data sharing is being carried out in the target area and channel conditions are good, QAM mode can be activated to achieve high-speed data throughput.

[0035] Step S2: Construct an underwater acoustic channel model and use the underwater acoustic channel model to simulate the channel transmission of the original transmitted signal to obtain the original received signal.

[0036] Specifically, the channel transmission simulation includes: constructing an underwater acoustic channel transmission response model characterizing the physical propagation characteristics of the channel based on simulation configuration parameters, and using the underwater acoustic channel transmission response model to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal.

[0037] Understandably, underwater acoustic channel transmission simulation is the core of simulation fidelity. It uses a multi-physics coupling model to strictly simulate the signal transmission process underwater according to the physical causality law, thereby generating the original signal at the receiving end.

[0038] In some specific embodiments, step S2 above includes: Step S2a: Calculate the sound wave propagation path and sound ray parameters based on the simulation configuration parameters.

[0039] Specifically, based on the sound velocity profile in the simulation configuration parameters input in step S1, a layered calculation method is used to obtain the sound velocity distribution at different depths. Combined with the geometric boundary of the underwater environment, ray theory is used to trace the propagation path of the sound wave to obtain the sound ray parameters.

[0040] It should be noted that the propagation path tracing process directly derives the number of effective multipath sound rays reaching the receiver. L And accurately calculate the first p Time-varying propagation delay of a single sound ray And the time-varying amplitude is affected by both propagation spread loss and medium absorption attenuation. .

[0041] Step S2b: Construct a linear time-varying impulse response model for the underwater acoustic channel based on the acoustic ray parameters, and perform convolution operation between the original transmitted signal and the linear time-varying impulse model.

[0042] Specifically, a linear time-varying impulse response model for the underwater acoustic channel is constructed using the acoustic ray parameters derived from ray theory. The impulse response function is expressed as:

[0043] in, The Dirac function is used to independently acquire the original transmitted signal generated in step one. Then, the simulation system will transmit the original signal. With the constructed time-varying multipath impulse response Convolution operations are performed to accurately reproduce the physical distortion process of the signal in an underwater multipath time-varying environment.

[0044] Step S2c: Add environmental composite noise to the convolutionally distorted signal to obtain the original received signal.

[0045] Specifically, to reproduce the true reception state, the system superimposes integrated noise consistent with the actual marine environment onto the signal after convolutional distortion. .

[0046] In some preferred embodiments, the environmental composite noise It is composed of ship radiated noise, marine biological noise and turbulent noise, and its overall power spectral density is a linear superposition of the power spectral densities of each independent noise component.

[0047] It is understandable that environmental composite noise This application explicitly covers three major marine noise sources: ships, organisms, and turbulence. This makes the noise spectrum characteristics in the simulation environment closer to the real marine environment, avoiding optimistic biases in simulation results caused by a single noise model. By simulating the characteristics of different noise sources, this application can evaluate the adaptability of communication systems under different noise-dominant environments, enhancing the practical guiding significance of simulation evaluation.

[0048] Finally, after the transmitted signal passes through the channel and is superimposed with noise, the mathematical expression of the original signal at the receiving end is:

[0049] in, This represents the convolution operation, thereby enabling high-fidelity physical reproduction of the entire process from signal transmission, channel multipath transmission to noise coupling.

[0050] Step S3, Dynamic Visualization of Channel Transmission Process: Extract intermediate parameters that characterize the physical propagation state of the channel during the channel transmission simulation process, and generate visualization data that characterizes the channel transmission process based on the intermediate parameters.

[0051] Step S3 above includes: Step S3a: Dynamically draw the trajectory of each sound ray based on the sound wave propagation path and sound ray parameters.

[0052] Specifically, based on the core parameters such as propagation path and attenuation coefficient derived from the ray theory in step S2, the trajectory of each sound ray is dynamically drawn in the three-dimensional marine environment model.

[0053] Understandably, this visualization process not only presents the underwater sound field distribution intuitively, but also helps technicians effectively identify complex acoustic blind spots, thereby providing an intuitive engineering decision-making basis for the deployment depth and communication array optimization of underwater communication nodes (such as unmanned formations).

[0054] Step S3b: Extract the time-varying amplitude and delay parameters from the acoustic parameters, and plot the dynamic curve of the channel impulse response over time based on the time-varying amplitude and delay parameters.

[0055] Specifically, the time-varying amplitude and time delay parameters in the acoustic parameters generated in step S2 are directly extracted and displayed in real time as dynamic curves to show the evolution of the channel impulse response over time (the horizontal axis is time delay and the vertical axis is amplitude).

[0056] It is worth noting that this dynamic display reveals the number and span of multipath components, providing technicians with precise physical-level parameter references for optimizing receiver anti-multipath algorithms (such as setting the guard interval of orthogonal frequency division multiplexing or the tap length of the time domain equalizer).

[0057] Step S3c: Calculate the dynamic signal-to-noise ratio within the sliding time window based on the acoustic parameters, and present the signal-to-noise ratio change through a line graph.

[0058] Specifically, the sliding time window is calculated using the instantaneous effective signal power obtained in step S2 and the superimposed ocean noise power. W The dynamic signal-to-noise ratio within the range is mathematically expressed as:

[0059] Meanwhile, the signal-to-noise ratio trend is displayed in real time through a line graph.

[0060] Understandably, presenting the signal-to-noise ratio (SNR) trend in real time through a line graph can help technicians accurately pinpoint the transient physical causes of sudden signal errors or communication interruptions, and provide the most direct data support for performing multi-mode adaptive modulation switching (such as adaptive switching between FSK, PSK, and QAM based on dynamic SNR evaluation), thus comprehensively improving the traceability of signal-level simulation and the efficiency of system optimization.

[0061] Step S4: Process the original received signal to recover the demodulated data.

[0062] Understandably, this step aims to process the raw receiver signal output from step two, which includes time-varying multipath fading and broadband ocean noise. Cascaded processing is performed to overcome the physical distortion of the underwater acoustic channel and recover valid baseband information.

[0063] Specifically, step S4 includes: Step S4a: Perform automatic gain control on the original received signal to output an equalized received signal.

[0064] Specifically, to address the drastic fluctuations in signal amplitude caused by the multipath effect, the system implements automatic gain control (AGC). This step tracks the original received signal in real time. The envelope fluctuations are controlled, and the amplifier gain is dynamically adjusted to stabilize the signal amplitude within the linear processing range of subsequent modules in the receiver, thereby outputting a balanced received signal with uniform amplitude.

[0065] Step S4b: Filter out noise in the equalized received signal using a bandpass filter module to obtain a filtered signal.

[0066] Specifically, the equalized received signal is fed into the bandpass filter module as input for subsequent processing. This module employs an FIR filter that is precisely matched to the bandwidth of the transmitter's baseband signal to accurately filter out broadband environmental noise in the out-of-band frequency band and output a filtered signal with a high signal-to-noise ratio.

[0067] Step S4c: Perform multi-level synchronization processing on the filtered signal to obtain a synchronization signal.

[0068] Specifically, multi-level synchronous processing is performed on the filtered signal obtained in step S4b.

[0069] In one specific embodiment, in order to overcome underwater Doppler frequency shift and phase jitter, the system uses a phase-locked loop (PLL) to perform carrier phase tracking compensation on the filtered signal, and supplements it with a timing recovery algorithm to accurately anchor the optimal sampling time of the symbol, and finally extracts the synchronization signal from the filtered signal to achieve strict alignment between the symbol and the frame level.

[0070] Step S4d: Demodulate and decode the synchronization signal, and output the binary received content as the demodulated data.

[0071] Specifically, after receiving the fully aligned synchronization signal, the corresponding baseband demodulation algorithm is invoked according to the dynamically configured modulation scheme to restore it to the baseband coded sequence. Further, the sequence is decoded and error-tolerant through corresponding error correction mechanisms such as Cyclic Redundancy Check (CRC) and convolutional decoding, ultimately outputting accurate binary received content as demodulated data.

[0072] It is worth noting that this continuous and rigorous data flow process not only completes the high-fidelity restoration of the physical layer signal, but also closes the loop of the entire link communication physical process, providing the final basis for evaluating the system's bit error rate and communication reliability.

[0073] In some preferred embodiments, step S4, after data demodulation, further includes: Step S4e: Visualize the received signal.

[0074] It is worth noting that step S4e aims to provide a multi-dimensional graphical representation of the signals before and after the received cascade processing. Its core purpose is not only to intuitively present the evolution of the physical characteristics of the signal, but also to provide an intuitive engineering diagnostic basis for those skilled in the art to evaluate underwater acoustic channel impairments and verify the performance of the receiving algorithm.

[0075] The above step S4e includes: Step A: Analyze the original received signal using time-frequency analysis methods to generate a time-frequency diagram.

[0076] Specifically, the Short Time Fourier Transform (STFT) is used to process the original received signal. Perform joint time-frequency analysis to generate a time-frequency plot. The calculation formula can be expressed as:

[0077] in, The window function is used. The two-dimensional energy distribution presented as a heatmap can help engineers intuitively understand the complex frequency-selective fading characteristics and dynamic Doppler frequency shift trajectories underwater, thereby guiding the reasonable avoidance of communication frequency bands and the design of anti-frequency-selective fading algorithms.

[0078] Step B: Draw a scatter plot of the baseband constellation based on the demodulated data.

[0079] Specifically, for the demodulated baseband signal, the system extracts its orthogonal I-path and Q-path components to draw a scatter plot of the baseband constellation.

[0080] Understandably, in underwater acoustic communication, the rotational drift and divergence of the scattered clusters on the constellation diagram can very effectively expose the residual carrier phase jitter and signal-to-noise ratio degradation to technicians. This provides the most intuitive data support for directly guiding the fine-tuning of the phase-locked loop (PLL) tracking parameters at the receiver and the convergence optimization of the adaptive equalizer tap weights.

[0081] Step C: Output time-domain waveforms containing the original transmitted signal, the original received signal, and the demodulated data in parallel on the same time axis.

[0082] It should be noted that time-domain waveforms are output in parallel on the same time axis, synchronously displaying the ideal transmitted signal. The original received signal containing time-varying distortion And the processed signal after cascaded compensation (such as the synchronization signal). This end-to-end waveform comparison and visualization mechanism enables practitioners to intuitively assess the deep fading destructive power of multipath effects on the signal envelope on a macro scale, and visually verify the actual compensation efficiency of the front-end automatic gain control (AGC) and filtering and noise reduction modules, thereby completing the performance closed-loop evaluation of the entire high-fidelity underwater acoustic communication physical layer simulation.

[0083] Step S5: Perform a multi-dimensional evaluation of communication performance based on demodulated data, raw received signals, and raw transmitted signals.

[0084] It is worth noting that, in response to the limitations of existing conventional underwater acoustic simulation technologies that typically isolate single mathematical indicators for black-box testing and lack in-depth physical correlation, this step constructs a cross-dimensional "physical-channel-signal" joint mapping system to quantitatively bind the distortion of the underlying marine physical environment with the degradation of the top-level communication quality.

[0085] In some specific embodiments, step S5 includes: Step S5a: In terms of signal distortion, the system not only performs conventional comparisons, but also jointly calculates the mean square error of the received synchronization signal and the transmitted signal.

[0086] And signal distortion ratio:

[0087] Understandably, by calculating the mean square error and the signal distortion ratio, the degree of waveform energy dissipation and transient distortion caused by the underwater acoustic physical channel can be precisely quantified.

[0088] Step S5b: Dynamically extract the multipath component parameters derived from the multiphysics coupling in step S2, and rigorously calculate the multipath delay spread:

[0089] in, and For the amplitude of the multipath components, and the time delay and channel fading depth:

[0090] This allows the macroscopic sound velocity gradient and boundary reflection to be directly converted into a quantitative indicator of the spatial dispersion intensity of the physical link.

[0091] Step S5c: Propagate the aforementioned underlying physical channel parameters upwards to the communication quality dimension, and calculate the bit error rate by rigorously comparing the transmitted and received baseband bit sequences:

[0092] in, Total number of bits and For the corresponding bits and effective transmission rate, an evaluation system including signal distortion, channel characteristics, and communication quality is established based on signal distortion ratio, channel fading depth, and bit error rate.

[0093] Understandably, through this continuous calculation of multi-dimensional parameter coupling, a rigorous mathematical mapping between the changes in the underlying acoustic physical parameters and the top-level communication errors is established. This provides the ability to trace the physical causes across the entire link, which is lacking in traditional single-result tests, and provides substantial closed-loop diagnostic basis for the adaptive optimization of communication systems in complex marine environments.

[0094] In one specific embodiment of the underwater acoustic communication signal level simulation evaluation method of this application, the underwater acoustic communication signal level simulation evaluation method includes: Step S1: Input simulation parameter configuration.

[0095] The core simulation parameters are set as shown in Table 1: Table 1 Simulation Parameter Configuration Table

[0096] Step S2: Generate the transmission signal.

[0097] Specifically, the text content is converted into a binary sequence (192 bits in total), encoded by CRC, and then passed through a raised cosine shaping filter to generate a baseband signal. This baseband signal is then modulated using 16QAM to generate the transmitted signal, and its time-domain waveform is shown below. Figure 2 As shown.

[0098] Step S3: Transmission simulation and visualization processing.

[0099] Specifically, 12 main acoustic ray trajectories were calculated based on ray theory, and the visualization results of the acoustic ray trajectories are as follows: Figure 3 As shown, the propagation path, transmission / reception angle, and propagation time of the sound ray can be clearly observed; the channel impulse response changes over time as shown... Figure 4 As shown, multipath delay spread; signal-to-noise ratio dynamic changes are as follows: Figure 5 As shown, the average.

[0100] Step S4: Signal Processing and Visualization.

[0101] Specifically, the received raw signal is processed by AGC gain adjustment, 5kHz bandpass filtering, and synchronization processing to generate a synchronization signal. STFT time-frequency analysis is then performed on this signal to obtain the time-frequency diagram as shown below. Figure 6 As shown, the energy distribution of the signal near the 5kHz carrier frequency can be clearly observed; the constellation diagram after 16QAM demodulation is as follows. Figure 7 As shown, the symbol points are concentrated in 16 preset positions, resulting in minimal distortion.

[0102] Step S5: Performance evaluation results.

[0103] The core indicators obtained through the multi-dimensional evaluation system are shown in Table 2: Table 2 Performance Evaluation Table

[0104] Step S6: Result Verification.

[0105] Simulation results show that the time-frequency diagram clearly presents the frequency distribution characteristics of the 16QAM signal, the symbol point distortion of the constellation diagram is small, and the bit error rate is low, which meets the communication requirements. The visualization results of the acoustic ray trajectory and channel impulse response are consistent with the theoretical analysis. The multi-dimensional evaluation indicators meet the expected performance of 16QAM communication at a distance of 500m in shallow sea, verifying that the method of this invention can complete the underwater acoustic communication signal-level simulation with high fidelity and visualization.

[0106] In summary, this invention constructs a full-process simulation method for underwater acoustic communication that integrates signal generation, channel simulation, reception processing, and multi-dimensional visualization. Its beneficial effects are significant: First, by integrating a multi-factor coupled underwater acoustic channel model, it accurately simulates key physical processes such as multipath effects, sound velocity gradients, and ocean noise, making the statistical characteristics of the simulated signal more than 90% similar to those of real underwater communication signals, significantly improving simulation fidelity and providing precise support for algorithm optimization. Second, it constructs a multi-dimensional visualization framework of "transmission process + reception result," enabling dynamic display of key parameters such as acoustic ray trajectories, channel impulse response, and signal-to-noise ratio changes, enhancing the traceability of the simulation process and facilitating problem localization. Third, the modular parameter configuration system supports flexible customization of transmission content, equipment parameters, modulation methods, and channel scenarios, greatly enhancing configuration flexibility to adapt to diverse simulation needs. Finally, it establishes a multi-dimensional evaluation system including signal distortion, channel characteristics, and communication quality, quantifying key indicators such as bit error rate and delay spread, achieving comprehensive and accurate performance evaluation. Furthermore, this invention can generate high-fidelity simulation data and visualization results without relying on on-site sea trials, significantly reducing the R&D cost and cycle of underwater acoustic communication systems, and providing efficient support for scientific research, engineering applications and teaching in related fields.

[0107] Secondly, embodiments of this application also provide an underwater acoustic communication signal-level simulation and evaluation device, which includes: a signal generation module, a channel simulation module, a process visualization module, a receiving and processing module, and a performance evaluation module; wherein, The system comprises the following modules: a signal generation module for acquiring simulation configuration parameters and generating an original transmitted signal based on these parameters; a channel simulation module for constructing an underwater acoustic channel model and simulating channel transmission of the original transmitted signal using the underwater acoustic channel model to obtain an original received signal; wherein the channel transmission simulation includes: constructing an underwater acoustic channel transmission response model characterizing the physical propagation characteristics of the channel based on the simulation configuration parameters, performing channel simulation processing on the original transmitted signal using the underwater acoustic channel transmission response model, and superimposing environmental composite noise; a process visualization module for extracting intermediate parameters characterizing the physical propagation state of the channel during the channel transmission simulation, and generating visualization data characterizing the channel transmission process based on the intermediate parameters; a receiving processing module for receiving and processing the original received signal to recover demodulated data; and a performance evaluation module for performing multi-dimensional evaluation of communication performance based on the demodulated data, the original received signal, and the original transmitted signal.

[0108] The functions of each module in the above-mentioned underwater acoustic communication signal level simulation and evaluation device correspond to the steps in the above-mentioned underwater acoustic communication signal level simulation and evaluation method embodiment, and their functions and implementation processes will not be described in detail here.

[0109] Thirdly, embodiments of this application provide an underwater acoustic communication signal level simulation and evaluation device, which can be a personal computer (PC), laptop computer, server, or other device with data processing capabilities.

[0110] Reference Figure 9 , Figure 9 This is a schematic diagram of the hardware structure of the underwater acoustic communication signal level simulation and evaluation device involved in the embodiments of this application. In this embodiment, the underwater acoustic communication signal level simulation and evaluation device may include a processor, a memory, a communication interface, and a communication bus.

[0111] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0112] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting internal components of the underwater acoustic communication signal-level simulation and evaluation equipment, as well as interfaces used for interconnecting the underwater acoustic communication signal-level simulation and evaluation equipment with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0113] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0114] The processor can be a general-purpose processor, which can call the underwater acoustic communication signal level simulation and evaluation program stored in the memory and execute the underwater acoustic communication signal level simulation and evaluation method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the underwater acoustic communication signal level simulation and evaluation program is called can refer to the various embodiments of the underwater acoustic communication signal level simulation and evaluation method of this application, and will not be repeated here.

[0115] Those skilled in the art will understand that Figure 9 The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0116] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0117] The present application stores an underwater acoustic communication signal level simulation evaluation program on a computer-readable storage medium, wherein when the underwater acoustic communication signal level simulation evaluation program is executed by a processor, it implements the steps of the underwater acoustic communication signal level simulation evaluation method as described above.

[0118] The method implemented when the underwater acoustic communication signal level simulation evaluation program is executed can be referred to in various embodiments of the underwater acoustic communication signal level simulation evaluation method of this application, and will not be repeated here.

[0119] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0120] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0121] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0122] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0123] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0124] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0125] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for simulating and evaluating underwater acoustic communication signal levels, characterized in that, The underwater acoustic communication signal level simulation evaluation method includes: Obtain the simulation configuration parameters and generate the original transmission signal based on the simulation configuration parameters; Based on the simulation configuration parameters, an underwater acoustic channel transmission response model characterizing the physical propagation characteristics of the channel is constructed. The underwater acoustic channel transmission response model is then used to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal. Intermediate parameters characterizing the physical propagation state of the channel are extracted during the channel transmission simulation, and visual data characterizing the channel transmission process are generated based on the intermediate parameters. The original received signal is processed to recover the demodulated data; Communication performance is evaluated based on demodulated data, raw received signals, and raw transmitted signals.

2. The underwater acoustic communication signal level simulation and evaluation method as described in claim 1, characterized in that, The process involves constructing an underwater acoustic channel transmission response model based on simulation configuration parameters to characterize the physical propagation characteristics of the channel, and then using this model to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal. This includes: Calculate the sound wave propagation path and acoustic parameters based on the simulation configuration parameters; A linear time-varying impulse response model for the underwater acoustic channel is constructed based on the acoustic ray parameters. The original transmitted signal is convolved with a linear time-varying impulse response model, and environmental composite noise is superimposed on the convolved and distorted signal to obtain the original received signal.

3. The underwater acoustic communication signal level simulation and evaluation method as described in claim 2, characterized in that, The calculation of the sound wave propagation path and acoustic parameters based on the simulation configuration parameters includes: The sound velocity distribution at different depths is obtained by using a layered calculation method based on the sound velocity profile in the simulation configuration parameters. Sound wave propagation path tracing is performed using ray theory and sound velocity distribution to obtain sound ray parameters.

4. The underwater acoustic communication signal level simulation and evaluation method as described in claim 2, characterized in that, The process of extracting intermediate parameters characterizing the physical propagation state of the channel during channel transmission simulation and generating visual data characterizing the channel transmission process based on these intermediate parameters includes: The trajectory of each ray is dynamically drawn based on the sound wave propagation path and ray parameters; Extract the time-varying amplitude and delay parameters from the acoustic parameters, and plot the dynamic curve of the channel impulse response over time based on the time-varying amplitude and delay parameters; The dynamic signal-to-noise ratio (SNR) within the sliding time window is calculated based on the acoustic parameters, and the SNR change is presented through a line graph.

5. The underwater acoustic communication signal level simulation and evaluation method as described in claim 1, characterized in that, The process of receiving and processing the original received signal to recover the demodulated data includes: Automatic gain control is performed on the original received signal to output an equalized received signal; The noise in the equalized received signal is filtered out by a bandpass filter module to obtain the filtered signal. The filtered signal is subjected to multi-stage synchronization processing to obtain a synchronization signal; The synchronization signal is demodulated and decoded, and the binary received content is output as the demodulated data.

6. The underwater acoustic communication signal level simulation evaluation method as described in claim 5, characterized in that, After processing the original received signal to recover the demodulated data, the process further includes: The original received signal is analyzed using time-frequency analysis methods to generate a time-frequency diagram; Based on the demodulated data, a scatter plot of the baseband constellation is drawn, and time-domain waveforms containing the original transmitted signal, the original received signal, and the demodulated data are output in parallel on the same time axis.

7. The underwater acoustic communication signal level simulation and evaluation method as described in claim 1, characterized in that, The communication performance evaluation based on demodulated data, raw received signal, and raw transmitted signal includes: Calculate the signal distortion ratio, channel fading depth, and bit error rate based on the demodulated data, the original received signal, and the original transmitted signal. The evaluation results for signal distortion, channel characteristics, and communication quality are generated based on the signal distortion ratio, channel fading depth, and bit error rate.

8. The underwater acoustic communication signal level simulation and evaluation method as described in claim 1, characterized in that, The environmental composite noise includes: ship radiation noise, marine biological noise, and turbulence noise.

9. A simulation and evaluation device for underwater acoustic communication signals, characterized in that, The underwater acoustic communication signal level simulation and evaluation device includes: A signal generation module is used to acquire simulation configuration parameters and generate an original transmission signal based on the simulation configuration parameters; The channel simulation module is used to construct an underwater acoustic channel transmission response model that characterizes the physical propagation characteristics of the channel based on simulation configuration parameters, and to use the underwater acoustic channel transmission response model to perform channel simulation processing on the original transmitted signal and superimpose environmental composite noise to obtain the original received signal. The process visualization module is used to extract intermediate parameters that characterize the physical propagation state of the channel during the channel transmission simulation process, and generate visualization data characterizing the channel transmission process based on the intermediate parameters. The receiving and processing module is used to process the original received signal and recover the demodulated data. A performance evaluation module is used to evaluate communication performance based on the demodulated data, the original received signal, and the original transmitted signal.

10. A simulation and evaluation device for underwater acoustic communication signals, characterized in that, The underwater acoustic communication signal level simulation and evaluation device includes a processor, a memory, and an underwater acoustic communication signal level simulation and evaluation program stored in the memory and executable by the processor, wherein when the underwater acoustic communication signal level simulation and evaluation program is executed by the processor, it implements the steps of the underwater acoustic communication signal level simulation and evaluation method as described in any one of claims 1 to 8.

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