Communication and positioning integrated sonar system

Abstract

The invention provides a communication and positioning integrated sonar system, and relates to the technical field of communication, and the system comprises a communication module which is used for determining a communication algorithm according to an obtained communication distance and the signal-to-noise ratio of an original communication signal, carrying out the modulation and coding of the original communication signal through the communication algorithm, and transmitting the modulated and coded original communication signal to a communication module. Generating a communication code stream; the communication and positioning integrated module is used for embedding a preset original positioning signal into the communication code stream to generate a fusion signal through a coding multiplexing technology; and the positioning module is used for determining a positioning algorithm according to the signal-to-noise ratio and the coherent interference coefficient of the fused signal, and generating corresponding position information through the positioning algorithm according to the positioning information in the fused signal. According to the invention, the information transmission efficiency of the sonar system can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a communication and positioning integrated sonar system. Background Art

[0002] Sonar systems play a key role in modern ocean development and exploration. In marine resource development, they can accurately measure the distribution of seabed minerals, providing crucial data support for mining operations and improving resource exploration efficiency. In underwater exploration, they play an irreplaceable role in mapping underwater topography and salvaging shipwrecks. Furthermore, in marine scientific research, sonar can be used to detect the activity patterns of marine life and changes in the marine environment, providing a wealth of data and information for scientific research and promoting the in-depth development of marine science.

[0003] In related technologies, existing sonar systems mostly adopt a discrete design, in which communication and positioning signals are transmitted independently. During the signal transmission process, problems such as delays and packet loss may occur, making information processing more difficult and affecting the efficiency of information transmission. Summary of the Invention

[0004] The problem solved by the present invention is how to improve the efficiency of information transmission of a sonar system.

[0005] In order to solve the above problems, the present invention provides a communication and positioning integrated sonar system.

[0006] In a first aspect, the present invention provides a communication and positioning integrated sonar system, comprising:

[0007] a communication module, configured to determine a communication algorithm based on the acquired communication distance and the signal-to-noise ratio of the original communication signal, modulate and encode the original communication signal using the communication algorithm to generate a communication code stream, wherein the communication algorithm includes an orthogonal frequency division multiplexing algorithm, a multi-ary frequency shift keying algorithm, or an orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm;

[0008] The communication and positioning integration module is used to embed the preset original positioning signal into the communication code stream to generate a fusion signal through code multiplexing technology;

[0009] A positioning module is used to determine a positioning algorithm based on the signal-to-noise ratio and coherent interference coefficient of the fused signal, and generate corresponding position information through the positioning algorithm based on the positioning information in the fused signal, wherein the positioning algorithm includes an acoustic energy flow method, a conventional beamforming algorithm, a minimum variance distortionless response algorithm or a multi-signal classification algorithm.

[0010] Optionally, determining the communication algorithm according to the acquired communication distance and the signal-to-noise ratio of the original communication signal includes:

[0011] Obtaining a communication switching index through a preset communication switching index relationship according to the communication distance and the signal-to-noise ratio of the original communication signal;

[0012] The communication algorithm is determined according to a comparison result between the communication switching indicator and a preset communication switching threshold.

[0013] Optionally, the communication switching threshold includes a first communication switching threshold and a second communication switching threshold, wherein the first communication switching threshold is less than the second communication switching threshold; and determining the communication algorithm according to a comparison result between the switching indicator and a preset communication switching threshold includes:

[0014] When the switching indicator is less than or equal to the first communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing algorithm;

[0015] When the switching index is greater than the first communication switching threshold and less than the second communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm;

[0016] When the switching index is greater than or equal to the second communication switching threshold, the communication algorithm is switched to a multi-ary frequency shift keying algorithm.

[0017] Optionally, the communication switching indicator relationship satisfies:

[0018]

[0019] Among them, R is the communication switching index, SNR is the signal-to-noise ratio of the original communication signal, D is the communication distance, K1 is the first switching coefficient, and K2 is the second switching coefficient.

[0020] Optionally, determining a positioning algorithm according to a signal-to-noise ratio and a coherent interference coefficient of the fused signal includes:

[0021] When the coherent interference coefficient is greater than a preset coherent interference threshold, switching the positioning algorithm to a multi-signal classification algorithm;

[0022] When the coherent interference coefficient is less than or equal to the coherent interference threshold, the positioning algorithm is determined according to a comparison result of the signal-to-noise ratio of the fused signal and a preset fusion signal-to-noise ratio threshold.

[0023] Optionally, the fused signal-to-noise ratio threshold includes a first fused signal-to-noise ratio threshold and a second fused signal-to-noise ratio threshold, wherein the first fused signal-to-noise ratio threshold is less than the second fused signal-to-noise ratio threshold; and determining the positioning algorithm according to the signal-to-noise ratio of the fused signal includes:

[0024] When the signal-to-noise ratio of the fusion signal is less than or equal to a preset first fusion signal-to-noise ratio threshold, switching the positioning algorithm to the minimum variance distortionless response algorithm;

[0025] When the signal-to-noise ratio of the fused signal is greater than the first fusion signal-to-noise ratio threshold and less than the second fusion signal-to-noise ratio threshold, switching the positioning algorithm to the conventional beamforming algorithm;

[0026] When the signal-to-noise ratio of the fusion signal is greater than the second fusion signal-to-noise ratio threshold, the positioning algorithm is switched to the acoustic energy flow method.

[0027] Optionally, the coherent interference coefficient satisfies:

[0028]

[0029] Wherein, γ is the coherent interference coefficient, x is the fusion signal, and E is the mathematical expectation operation.

[0030] Optionally, the system also includes an interaction module for performing human-computer interaction according to a preset mode, wherein the preset mode includes a communication mode, a positioning mode and a joint mode. The communication mode is used to perform human-computer interaction through a human-computer interaction interface, the positioning mode is used to display the location information of the target object through a full-screen map view, and the joint mode is used to display the communication interface and the map view separately through split screen.

[0031] Optionally, the system further comprises a vector hydrophone, a preamplifier module, an A / D acquisition module, a signal processing module, a power amplifier module and a transmitting transducer;

[0032] The vector hydrophone is used to obtain the fusion signal, and the signal processing module is used to send the fusion signal received after being processed by the pre-processing method module and the A / D acquisition module to the positioning module to implement the signal reception process;

[0033] The signal processing module is used to send the fusion signal to the power amplification module, and the power amplification module amplifies the received fusion signal and sends it to the transmitting transducer. The transmitting transducer is used to transmit the received amplified fusion signal to realize the signal sending process.

[0034] Optionally, the system also includes a power supply module, which includes a first-stage step-down module and a second-stage step-down module, the first-stage step-down module is used to convert the battery voltage into a first voltage, and the second-stage step-down module is used to convert the first voltage into a second voltage, wherein the first voltage is greater than the second voltage, and the second voltage is used to power the vector hydrophone, the preamplifier module, the A / D acquisition module, the signal processing module, the power amplification module and the transmitting transducer.

[0035] The beneficial effects of the communication and positioning integrated sonar system of the present invention are as follows: the communication module intelligently determines the communication algorithm based on the communication distance and the signal-to-noise ratio of the original communication signal, modulates and encodes the original communication signal to generate a communication code stream, and selects a suitable communication algorithm from the orthogonal frequency division multiplexing algorithm, the multi-ary frequency shift keying algorithm and the orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm to adapt to different application scenarios, thereby improving the communication efficiency of the sonar system; the communication and positioning integrated module uses the coding multiplexing technology to embed the original positioning signal into the communication code stream to generate a fused signal, avoiding the extra bandwidth and time consumption brought by the separate transmission of the positioning signal, and further optimizing the information transmission efficiency; the positioning module determines the positioning algorithm based on the signal-to-noise ratio and coherent interference coefficient of the fused signal, and generates position information based on the positioning information in the fused signal. The selection of the positioning algorithm can adapt to different environments, reduce the redundancy of the positioning signal transmission, and thus comprehensively improve the information transmission efficiency of the sonar system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a schematic structural diagram of a communication and positioning integrated sonar system according to an embodiment of the present invention;

[0037] Figure 2 Schematic diagram of the hardware structure of the sonar system according to an embodiment of the present invention;

[0038] Figure 3 Schematic diagram of the structure of the power supply module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0040] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0041] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to"; the term "based on" means "based at least in part on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "optional embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc. mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0042] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0043] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0044] Existing sonar systems suffer from numerous shortcomings that severely limit their effectiveness in complex underwater environments. Regarding communications technology, the traditional Multiple Frequency-Shift Keying (MFSK) algorithm suffers from low spectral efficiency, making it difficult to meet the growing demand for high-speed communications. While Orthogonal Frequency Division Multiplexing (OFDM) offers high bandwidth utilization, it is sensitive to frequency offset and phase noise, requiring complex equalization algorithms in multipath channels. This makes hardware implementation challenging, increasing system cost and complexity. Regarding positioning technology, traditional algorithms such as Conventional Beamforming (CBF) and Minimum Variance Distortionless Response (MVDR) exhibit significant performance differences under varying signal-to-noise ratio (SNR) or interference conditions. The MVDR algorithm is prone to instability at low SNRs, while the accuracy of the Multi-Signal Classification (MUSIC) algorithm plummets under high coherent interference. Furthermore, the algorithm lacks an adaptive switching mechanism for dynamic environments, resulting in uncertain positioning accuracy and reliability. From the perspective of system integration, existing sonar systems mostly adopt a discrete design, with communication and positioning signals transmitted independently, resulting in hardware redundancy, increased energy consumption, and difficulty in achieving coordinated optimization of signal resources, which reduces the overall performance of the system and hinders the efficient development of underwater detection, marine engineering and other fields.

[0045] In response to the problems existing in the above-mentioned related technologies, an embodiment of the present invention provides an integrated communication and positioning sonar system.

[0046] like Figure 1 As shown, an embodiment of the present invention provides a communication and positioning integrated sonar system, comprising:

[0047] A communication module is used to determine a communication algorithm based on the acquired communication distance and the signal-to-noise ratio of the original communication signal, modulate and encode the original communication signal through the communication algorithm, and generate a communication code stream, wherein the communication algorithm includes an orthogonal frequency division multiplexing algorithm, a multi-level frequency shift keying algorithm, or an orthogonal frequency division multiplexing-multi-level frequency shift keying algorithm.

[0048] Specifically, the communication module determines the appropriate communication algorithm based on the acquired communication distance and the signal-to-noise ratio (SNR) of the original communication signal. The original communication signal is the unfused communication signal originally generated by the communication system and focuses on information transmission, such as voice and data. Communication distance and SNR are important indicators of communication environment quality, and different distance and SNR combinations indicate different signal transmission conditions. Orthogonal frequency division multiplexing (OFDM) divides a broadband channel into multiple orthogonal sub-channels, allowing signals to be transmitted in parallel. This algorithm features high bandwidth utilization and strong resistance to inter-symbol interference (ISI), making it suitable for high-speed, short-range communications. Signal attenuation is minimal at closer communication distances, allowing it to fully leverage its high-speed transmission advantages. In the multi-level frequency shift keying (MFSK) algorithm, each symbol corresponds to a specific frequency. This algorithm offers strong anti-interference capabilities but suffers from low spectral efficiency, large bandwidth requirements, and low complexity, making it suitable for simple receiver designs. However, in long-distance communications, such as underwater, its frequency offset resistance makes it suitable for low-frequency, low-speed, long-distance communications due to high signal attenuation and narrow bandwidth. Orthogonal frequency division multiplexing-multi-level frequency shift keying (OFDM-MFSK) combines the advantages of OFDM's multipath resistance and MFSK's frequency offset resistance, offering moderate spectral efficiency and complexity. It can adapt to different channel conditions by adjusting the number of subcarriers and the number of bases, making it suitable for medium-speed, medium-to-long-distance communications. The communication module selects a suitable communication algorithm from these three algorithms based on the real-time communication distance and signal-to-noise ratio, and uses the selected communication algorithm to modulate and encode the original communication signal, ultimately generating a communication code stream that can be stably and reliably transmitted in a specific communication environment.

[0049] Orthogonal frequency division multiplexing (OFDM) is a highly efficient communication algorithm that divides a wideband channel into multiple orthogonal narrowband sub-channels and transmits data streams in parallel across these sub-channels. Because the sub-channels are orthogonal and their spectra can overlap, OFDM achieves high bandwidth utilization. Furthermore, it performs channel equalization in the frequency domain with relatively low complexity, effectively combating inter-symbol interference (ISI). This algorithm is particularly well-suited for high-speed, short-range communications, where communication distances are short, signal attenuation is relatively minimal, and communication rates are high. Multi-level frequency shift keying (MFSK), in which each symbol corresponds to a specific frequency, offers strong anti-interference capabilities, but suffers from low spectral efficiency and high bandwidth requirements. However, its low complexity makes it suitable for simple receiver designs. In environments such as underwater communications, where communication distances are long, signal attenuation is severe, and bandwidth resources are limited, MFSK's frequency offset robustness makes it highly effective in low-frequency transmission, making it commonly used in low-speed, long-range (low-power) communications. Orthogonal Frequency Division Multiplexing-Multi-Base Frequency Shift Keying (OFDM-MFSK) combines the advantages of both. It uses MFSK modulation on OFDM subcarriers. This algorithm has both the multi-carrier anti-multipath capability and the frequency offset resistance of MFSK. It has a medium spectrum efficiency and relatively high complexity. By flexibly adjusting the number of subcarriers and the base number, it can adapt well to different channel conditions and is suitable for medium-speed and long-distance communication scenarios (taking into account both multipath resistance and frequency offset compensation).

[0050] For example, when conducting underwater detection, the detection personnel need to maintain stable communication with other detection equipment in order to control the operation of the equipment and obtain detection data. The original communication signal is transmitted through the sonar system, using modulation technologies such as OFDM and MFSK, which can adapt to the complex underwater environment. For example, in underwater areas with obvious multipath effects, the anti-multipath fading characteristics of OFDM technology can ensure the stable transmission of communication signals, allowing detection personnel to obtain images, data and other information of underwater archaeological sites in a timely manner, providing strong support for archaeological research.

[0051] The communication and positioning integrated module is used to embed the preset original positioning signal into the communication code stream to generate a fusion signal through coding multiplexing technology.

[0052] Specifically, the communication and positioning integration module uses code multiplexing technology to embed the preset original positioning signal into the communication code stream, and then generate a fusion signal. The code multiplexing technology organically combines the positioning signal and the communication signal without significantly increasing the consumption of communication resources. The preset original positioning signal is a specific signal designed specifically for the positioning function, which contains key information for determining the position. The communication code stream is a signal sequence that carries the communication data after being processed by the communication module. Through code multiplexing technology, the communication and positioning integration module integrates the information of the original positioning signal into the communication code stream, so that the generated fusion signal has the dual functions of communication and positioning. In this way, during the same set of signal transmission processes, it is possible to complete normal communication tasks and realize data transmission and interaction, and to use the information carried by the positioning signal to perform accurate positioning.

[0053] It's important to note that code-multiplexing technology is a highly efficient means of implementing multiple functions within limited resources. This technology allows for the simultaneous processing and transmission of different types of information within the same signal channel without significant mutual interference. Specifically, when embedding the preset original positioning signal into the communication code stream to generate the fused signal, code-multiplexing technology performs special encoding on the original positioning signal and the communication code stream. Based on the characteristics of the communication and positioning signals and system requirements, code-multiplexing technology determines the encoding location and method for the positioning signal and communication data, enabling optimal multiplexing of the two across dimensions such as spectrum, time, or code domain. For example, this can be achieved by using different coding sequences for the positioning signal and communication signal, or by transmitting positioning and communication information separately in different time segments, or by arranging the signal components of both signals across the spectrum. This ensures the proper functioning of communication functions and the accurate transmission of communication data while also fully integrating the positioning signal, achieving the integration of communication and positioning functions. This not only improves the utilization of system resources and reduces the demand and cost of hardware equipment, but also avoids the interference and errors that may be caused by additional signal transmission, providing a stable, reliable and efficient signal foundation for subsequent positioning and communication operations. It is especially suitable for application scenarios with high requirements for resource utilization efficiency and functional integration, such as sonar systems.

[0054] A positioning module is used to determine a positioning algorithm based on the signal-to-noise ratio and coherent interference coefficient of the fused signal, and generate corresponding position information through the positioning algorithm based on the positioning information in the fused signal, wherein the positioning algorithm includes an acoustic energy flow method, a conventional beamforming algorithm, a minimum variance distortionless response algorithm or a multi-signal classification algorithm.

[0055] Specifically, the positioning module determines the appropriate positioning algorithm by combining the signal-to-noise ratio (SNR) and coherent interference coefficient of the fused signal. It then uses the positioning information embedded in the fused signal to generate corresponding position information using the selected positioning algorithm. This position information includes the estimated position of the target object. For example, during underwater detection, the positioning algorithm uses the positioning information embedded in the fused signal to determine the specific position of the target object to be located. The SNR of the fused signal reflects the ratio of effective information to noise in the signal. The higher the SNR, the better the signal quality, which is more conducive to accurately extracting positioning information. The coherent interference coefficient reflects the degree of coherent interference in the signal. The stronger the interference, the greater the impact on positioning accuracy. The positioning module comprehensively considers these two factors and selects the most suitable positioning algorithm from the acoustic energy flow method, conventional beamforming algorithm, minimum variance distortionless response algorithm, or multi-signal classification algorithm. The acoustic energy flow method determines the location of sound sources based on the characteristics of acoustic energy propagation and performs well in certain specific acoustic environments. The conventional beamforming algorithm (CBF) performs a weighted summation of received signals to form a beam that enhances signals in a specific direction, thereby achieving positioning. The minimum variance distortionless response algorithm (MVDR) minimizes output power to resist interference while ensuring the desired signal is output without distortion. The multi-signal classification algorithm utilizes the characteristics of the signal subspace and noise subspace to accurately locate multiple signal sources. Based on the actual signal-to-noise ratio and coherent interference coefficient, the positioning module selects the algorithm that best adapts to the current environment and can most accurately extract positioning information from the fused signal. Ultimately, it generates accurate position information, providing reliable positioning data support for the entire system. It is widely used in many fields such as underwater detection and intelligent navigation.

[0056] In this embodiment, the communication module selects a suitable communication algorithm from the orthogonal frequency division multiplexing algorithm, the multi-level frequency shift keying algorithm, or the orthogonal frequency division multiplexing-multi-level frequency shift keying algorithm based on the communication distance and the signal-to-noise ratio of the original communication signal, and modulates and encodes the original communication signal to generate a communication code stream. This ensures that the communication signal can be transmitted efficiently and stably under different distances and signal-to-noise ratio conditions, reduces errors and losses in signal transmission, and provides a reliable signal foundation for subsequent positioning. The communication and positioning integration module uses coding multiplexing technology to embed the original positioning signal into the communication code stream to generate a fused signal, thereby integrating the communication and positioning functions, avoiding interference and errors caused by additional signal transmission, and the fused signal can simultaneously carry communication and positioning information, improving the efficiency and integrity of information transmission. The positioning module selects an adaptive positioning algorithm from the acoustic energy flow method, conventional beamforming algorithm, minimum variance distortionless response algorithm or multi-signal classification algorithm based on the signal-to-noise ratio and coherent interference coefficient of the fused signal, and generates position information based on the positioning information in the fused signal. It can fully utilize the advantages of different algorithms in different signal environments, effectively resist interference and noise, and accurately extract positioning information, thereby greatly improving the accuracy of sonar system positioning.

[0057] It should be noted that the communication and positioning integrated sonar system of this embodiment has broad application prospects in multiple vertical fields. For example, in the field of marine resource development, the system can assist underwater exploration work. With its precise positioning function, it can accurately explore the location of seabed mineral resources, and the communication function ensures the real-time transmission of exploration data, allowing researchers to obtain and analyze information in a timely manner, thereby improving resource exploration efficiency. In terms of underwater detection, whether it is the search for underwater objects or the study of marine life, the system can determine the target location through high-precision positioning. At the same time, the communication function facilitates the real-time transmission of the detected data, providing strong support for subsequent research. In marine engineering construction, such as the construction and maintenance of offshore wind farms, cross-sea bridges and other projects, the communication and positioning integrated sonar system can accurately measure the underwater terrain, locate the construction location, ensure the precise construction of the project, and realize efficient communication between equipment during the construction and maintenance process to ensure the smooth progress of the project.

[0058] Optionally, determining the communication algorithm according to the acquired communication distance and the signal-to-noise ratio of the original communication signal includes:

[0059] Obtaining a communication switching index through a preset communication switching index relationship according to the communication distance and the signal-to-noise ratio of the original communication signal;

[0060] The communication algorithm is determined according to a comparison result between the communication switching indicator and a preset communication switching threshold.

[0061] Optionally, the communication switching indicator relationship satisfies:

[0062]

[0063] Among them, R is the communication switching index, SNR is the signal-to-noise ratio, D is the communication distance, K1 is the first switching coefficient, K2 is the second switching coefficient, and K1 and K2 are switching coefficients set according to actual conditions.

[0064] In this optional embodiment, a communication switching indicator is determined based on the acquired communication distance and the signal-to-noise ratio of the original communication signal, using a preset communication switching indicator relationship. This preset communication switching indicator relationship can be derived through extensive experimental testing, theoretical analysis, and practical application experience. It can comprehensively reflect the impact of both communication distance and signal-to-noise ratio on communication algorithm selection. After determining the communication switching indicator, it is compared with a preset communication switching threshold. The preset communication switching threshold can also be pre-set based on various factors such as the performance requirements of the communication system and the application scenario. When the communication switching indicator is compared with the preset communication switching threshold, different comparison results are generated. Based on the comparison results, an appropriate communication algorithm is selected from among the orthogonal frequency division multiplexing algorithm, the multi-ary frequency shift keying algorithm, or the orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm. Based on these comparison results, the system can accurately determine the communication algorithm most suitable for the current communication environment, thereby optimizing the performance of the communication system.

[0065] Optionally, the communication switching threshold includes a first communication switching threshold and a second communication switching threshold, wherein the first communication switching threshold is less than the second communication switching threshold; and determining the communication algorithm according to a comparison result between the switching indicator and a preset communication switching threshold includes:

[0066] When the switching indicator is less than or equal to the first communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing algorithm;

[0067] When the switching index is greater than the first communication switching threshold and less than the second communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm;

[0068] When the switching index is greater than or equal to the second communication switching threshold, the communication algorithm is switched to a multi-ary frequency shift keying algorithm.

[0069] Specifically, by continuously monitoring key parameters such as the communication distance and the signal-to-noise ratio of the original communication signal, and calculating the switching index based on the preset communication switching index relationship. When the calculated switching index is less than or equal to the first communication switching threshold, it indicates that the current communication environment has the characteristics of relatively good signal quality and relatively close communication distance. At this time, it is more appropriate to switch the communication algorithm to the orthogonal frequency division multiplexing algorithm. The orthogonal frequency division multiplexing algorithm can divide the broadband channel into multiple mutually orthogonal narrowband sub-channels, so that data can be transmitted in parallel. This feature enables it to have a higher frequency band utilization in this environment, and can also effectively resist inter-symbol interference, thereby achieving high-speed and stable communication. For example, it is very suitable for short-distance high-speed data transmission scenarios in cities.

[0070] If the switching index is greater than the first communication switching threshold and less than the second communication switching threshold, it means that the communication environment is in an intermediate state, and the signal quality and communication distance have changed to a certain extent. In this case, the communication algorithm is switched to the orthogonal frequency division multiplexing-multi-level frequency shift keying algorithm. This algorithm combines the advantages of orthogonal frequency division multiplexing in resisting multipath fading and the characteristics of multi-level frequency shift keying in resisting frequency deviation. By using multi-level frequency shift keying modulation on the subcarriers of orthogonal frequency division multiplexing, it can better adapt to this medium-complexity communication environment. While ensuring a certain communication rate, it takes into account anti-multipath and frequency deviation compensation. For example, in some maritime communication scenarios, when the distance is moderate and there is a certain amount of interference, this algorithm can play a good role.

[0071] When the handover index is greater than or equal to the second communication handover threshold, it indicates a poor communication environment, long communication distance, and poor signal quality. In this case, the MFSK algorithm becomes the preferred choice. Each symbol in the MFSK algorithm corresponds to a specific frequency. While spectrally inefficient, it offers strong interference immunity and low complexity, making it suitable for simple receiver designs. Its frequency offset tolerance excels in low-frequency transmission, ensuring basic communication reliability in low signal-to-noise ratio environments. This can be achieved in remote mountainous areas or deep sea environments where communication distances are long and signals are susceptible to interference.

[0072] For example, the first switching coefficient is set to 1, the second switching coefficient is set to 360, the first communication switching threshold is set to 22, and the second communication switching threshold is set to 24 based on the actual usage environment. When the signal-to-noise ratio (SNR) of the original communication signal is 20 and the communication distance (D) is 4 km, the communication switching index R is calculated to be 22. Since 22 is equal to the first communication switching threshold (22), OFDM is selected as the current communication algorithm. When SNR is 12 and D is 5 km, R is calculated to be 35. Since 35 is between the first communication switching threshold and the second communication switching threshold, OFDM-MFSK is selected as the current communication algorithm. When SNR is 8 and D is 10 km, R is calculated to be 55. Since 55 is greater than the second communication switching threshold (44), long-range MFSK is selected as the current communication algorithm. When SNR is 25 and D is 3 km, R is calculated to be 17.4. Since 17.4 is less than the first communication switching threshold (22), OFDM is selected as the current communication algorithm.

[0073] In this optional embodiment, the communication algorithm is dynamically switched based on the comparison of the switching index with the first and second communication switching thresholds, significantly improving the overall performance and adaptability of the communication system. When the switching index is less than or equal to the first communication switching threshold, indicating a favorable communication environment, such as close distance and low signal interference, the Orthogonal Frequency Division Multiplexing (OFDM) algorithm is employed. This algorithm divides the broadband channel into multiple orthogonal sub-channels for parallel data transmission, offering high bandwidth utilization and strong resistance to inter-symbol interference (ISI). This ensures accurate and high-speed data transmission, avoids transmission errors caused by signal interference or insufficient bandwidth, and thus improves communication accuracy. When the switching index is between the first and second communication switching thresholds, the communication environment is complex, with certain multipath fading and frequency deviation issues. The Orthogonal Frequency Division Multiplexing (OFDM)-Multi-ary Frequency Shift Keying (MFSK) algorithm is employed. This algorithm combines the advantages of OFDM's resistance to multipath fading and MFSK's resistance to frequency deviation, effectively compensating for signal distortion in complex environments, ensuring accurate data reception and interpretation, and reducing bit error rates. When the switching index is greater than or equal to the second communication switching threshold, the communication environment is harsh, the distance is long, and the interference is strong. The multi-level frequency shift keying algorithm, with its strong anti-interference ability, can maintain relatively stable signal transmission in harsh environments, reduce the impact of interference on the signal, and allow the receiving end to more accurately restore the original signal, thereby improving the accuracy of communication.

[0074] Optionally, determining a positioning algorithm according to a signal-to-noise ratio and a coherent interference coefficient of the fused signal includes:

[0075] When the coherent interference coefficient is greater than a preset coherent interference threshold, switching the positioning algorithm to a multi-signal classification algorithm;

[0076] When the coherent interference coefficient is less than or equal to the coherent interference threshold, the positioning algorithm is determined according to a comparison result of the signal-to-noise ratio of the fused signal and a preset fusion signal-to-noise ratio threshold.

[0077] Optionally, the coherent interference coefficient satisfies:

[0078]

[0079] Wherein, γ is the coherent interference coefficient, x is the fusion signal, and E is the mathematical expectation operation.

[0080] In this optional embodiment, during the actual operation of the positioning module, the coherent interference coefficient and the signal-to-noise ratio of the fused signal are two key judgment indicators. The appropriate positioning algorithm can be flexibly selected based on these two indicators to ensure the accuracy and reliability of positioning. When it is detected that the coherent interference coefficient is greater than the preset coherent interference threshold, this indicates that there is relatively serious coherent interference in the current positioning environment. In such a complex interference environment, ordinary positioning algorithms may find it difficult to accurately distinguish the target signal, resulting in a decrease in positioning accuracy. The multi-signal classification algorithm (MUSIC) has excellent anti-interference ability. It can effectively extract the characteristic information of the target signal from the complex interference signal by accurately dividing the signal subspace and the noise subspace, thereby achieving more accurate positioning. Therefore, in this case, the system will switch the positioning algorithm to the multi-signal classification algorithm to cope with severe coherent interference and improve the accuracy of positioning.

[0081] Furthermore, when the coherent interference coefficient is less than or equal to the coherent interference threshold, it indicates that the coherent interference in the current positioning environment is within an acceptable range. At this point, it is necessary to further determine the positioning algorithm based on the comparison result of the signal-to-noise ratio of the fused signal and the preset fusion signal-to-noise ratio threshold. The signal-to-noise ratio of the fused signal reflects the proportional relationship between the effective information and noise in the signal. The higher the signal-to-noise ratio, the better the signal quality, and the more conducive to accurately extracting positioning information. According to different signal-to-noise ratio conditions, the most suitable algorithm is selected from positioning algorithms such as the acoustic energy flow method, conventional beamforming algorithm, and minimum variance distortion-free response algorithm. By flexibly selecting the positioning algorithm based on the coherent interference coefficient and the fusion signal-to-noise ratio, the positioning module can adapt to different positioning environments and give full play to the advantages of various positioning algorithms, thereby achieving more accurate and reliable positioning.

[0082] Optionally, the fused signal-to-noise ratio threshold includes a first fused signal-to-noise ratio threshold and a second fused signal-to-noise ratio threshold, wherein the first fused signal-to-noise ratio threshold is less than the second fused signal-to-noise ratio threshold; and determining the positioning algorithm according to the signal-to-noise ratio of the fused signal includes:

[0083] When the signal-to-noise ratio of the fusion signal is less than or equal to a preset first fusion signal-to-noise ratio threshold, switching the positioning algorithm to the minimum variance distortionless response algorithm;

[0084] When the signal-to-noise ratio of the fused signal is greater than the first fusion signal-to-noise ratio threshold and less than the second fusion signal-to-noise ratio threshold, switching the positioning algorithm to the conventional beamforming algorithm;

[0085] When the signal-to-noise ratio of the fusion signal is greater than the second fusion signal-to-noise ratio threshold, the positioning algorithm is switched to the acoustic energy flow algorithm.

[0086] Specifically, the positioning module flexibly selects the positioning algorithm based on the comparison result of the signal-to-noise ratio of the fusion signal and the preset fusion signal-to-noise ratio threshold to ensure the accuracy and effectiveness of positioning. When the signal-to-noise ratio of the fusion signal is less than or equal to the preset first fusion signal-to-noise ratio threshold, it means that the noise in the signal is large, the effective information is relatively small, and the positioning environment is relatively harsh. At this time, the positioning algorithm is switched to the minimum variance distortion-free response algorithm. This algorithm has adaptive adjustment capabilities. While ensuring the distortion-free output of the expected signal, it can minimize the variance of the output signal, effectively suppress the impact of noise and interference on the positioning results, and even in a low signal-to-noise ratio environment, it can extract the characteristics of the target signal as accurately as possible, thereby achieving more accurate positioning.

[0087] When the signal-to-noise ratio (SNR) of the fused signal is greater than the first fusion SNR threshold and less than the second fusion SNR threshold, the signal quality has improved and is at a moderate level. In this case, the conventional beamforming algorithm is a more appropriate choice. This algorithm is relatively simple to implement and requires minimal computation. By weighted summing the signals received by multiple sensors, it forms a beam pointing in a specific direction. In environments with acceptable signal quality, it can quickly determine the approximate direction of the target, achieving relatively efficient positioning.

[0088] When the signal-to-noise ratio of the fused signal exceeds the second fusion signal-to-noise ratio threshold, it indicates high signal quality and minimal noise impact. Therefore, the acoustic energy flow method enables rapid positioning without complex calculations in situations with minimal signal interference and high signal quality, significantly improving efficiency. Furthermore, the high signal-to-noise ratio ensures stable and predictable acoustic energy flow propagation. This algorithm accurately captures direction, reduces positioning errors, and achieves high-precision positioning.

[0089] In this optional embodiment, during the positioning process, the signal-to-noise ratio (SNR) of the fused signal directly impacts positioning accuracy. Dynamically switching positioning algorithms based on the SNR significantly improves positioning accuracy. When the SNR of the fused signal is less than or equal to a preset first fused SNR threshold, the minimum variance distortionless response (MSDR) algorithm accurately extracts positioning information from noisy signal environments, significantly improving positioning accuracy under low SNR conditions. When the SNR is between the first and second fused SNR thresholds, signal quality improves but still exhibits some interference. Conventional beamforming algorithms can efficiently and accurately determine target direction in such medium SNR environments, ensuring timely and accurate positioning. When the SNR is greater than the second fused SNR threshold, signal quality is excellent. The acoustic energy flow method, utilizing its high-precision signal processing capabilities, further optimizes positioning accuracy in the absence of noise interference, avoids the potential error accumulation associated with other algorithms, and ensures more accurate and reliable positioning results. By intelligently switching algorithms based on the SNR, the advantages of each algorithm can be fully leveraged for different signal quality environments, minimizing positioning errors and comprehensively improving positioning accuracy.

[0090] Optionally, the system also includes an interaction module for performing human-computer interaction according to a preset mode, wherein the preset mode includes a communication mode, a positioning mode and a joint mode, the positioning mode is used to display the location information of the target object through a full-screen map view, and the joint mode is used to display the communication interface and the map view separately through a split screen.

[0091] In this optional embodiment, the system also includes an interaction module, which greatly enhances the communication and collaboration capabilities between users and the system. It performs human-computer interaction according to preset modes, providing users with a rich and flexible user experience. The preset modes include communication mode, positioning mode, and joint mode. In communication mode, users can enter commands on the interface to send or receive communication content, enabling communication with other devices or users. This interface design is intended to facilitate user operation and improve communication efficiency. With the help of the human-computer interaction interface, information interaction with the system can be conveniently carried out. The bubble-style conversation style of the chat window of the chat tool can be borrowed. Through application development software, such as custom drawing and adaptive layout in the list component (QListWidget) of Qt, a cross-platform C++ application development framework, a simple and beautiful chat interface can be implemented. After the user records, the recorded audio and recognition results are displayed in the form of bubbles on the host computer, making it convenient to view the communication content and timestamps during voice testing or debugging. The interface supports displaying sent and received audio information and can also play historical sent and received voice messages, providing a better user experience than traditional walkie-talkie communication systems. Recorded voice can also be converted into text using voice software and added to the chat box. To facilitate voice communication analysis, recorded or received audio files can be uploaded to a cloud server, where the converted text is retrieved and displayed within the interface. For example, upon completion of underwater voice transmission, the host computer automatically calls the recognition interface to evaluate transmission quality and recognition rate, facilitating quick verification of actual performance during debugging and demonstrations. Positioning mode focuses on presenting location information, clearly and intuitively displaying the target's location through a full-screen map view. This allows users to clearly identify the target's location at a glance, facilitating tracking and monitoring operations. This is extremely useful for applications requiring precise positioning, such as navigation and search. Combined mode cleverly integrates communication and positioning functions, displaying both the communication interface and the map view simultaneously in a split-screen format. This means users can monitor the target's location at any time during communication, and can also initiate communication operations when noticing changes in location. This provides a one-stop solution for users who require both communication and real-time positioning, comprehensively enhancing system functionality and user convenience.

[0092] Alternatively, as Figure 2 As shown, the system also includes a vector hydrophone, a preamplifier module, an A / D acquisition module, a signal processing module, a power amplifier module and a transmitting transducer;

[0093] The vector hydrophone is used to obtain the fusion signal, and the signal processing module is used to send the fusion signal received after being processed by the pre-processing method module and the A / D acquisition module to the positioning module to implement the signal reception process;

[0094] The signal processing module is used to send the fusion signal to the power amplification module, and the power amplification module amplifies the received fusion signal and sends it to the transmitting transducer. The transmitting transducer is used to transmit the received amplified fusion signal to realize the signal sending process.

[0095] In this optional embodiment, the system architecture also includes a vector hydrophone (a type of receiving transducer), a preamplifier module, an A / D acquisition module, a signal processing module, a power amplifier module, and a transmitting transducer. The vector hydrophone is an underwater acoustic sensor that can measure vector information such as particle velocity in the sound field, as well as scalar information such as sound pressure. It has many important functions: it can achieve high-precision positioning of underwater targets. By analyzing the directional information of the particle velocity, the target's orientation can be more accurately determined, significantly improving positioning accuracy compared to traditional scalar hydrophones. In complex marine environments, it has strong immunity to isotropic noise, effectively suppressing environmental noise interference, and improving the ability to detect weak signals, thereby more clearly detecting distant targets. It can be used for underwater communications, and by processing vector acoustic signals, it can improve the reliability and confidentiality of communications. It can also play a role in the field of marine environmental monitoring, monitoring the sound propagation characteristics and ocean dynamic environment parameters in the ocean, providing key data support for marine scientific research. During the signal reception process, the vector hydrophone is used to obtain a fused signal, which includes a communication code stream embedded with the positioning signal. The fused signal is then transmitted to the preamplifier module for initial amplification and other processing. After preamplification, it enters the A / D acquisition module, which converts the analog signal into a digital signal, enabling it to be recognized and processed by the computer system. The processed fused signal is then passed to the signal processing module, which further optimizes and analyzes it. The processed fused signal is then sent to the positioning module, providing accurate data support. The positioning module then processes the acquired fused signal to obtain the target's location information.

[0096] During signal transmission, the signal processing module sends the fused signal to the power amplifier module. This module amplifies the received fused signal, boosting its power and ensuring it has sufficient energy for long-distance transmission. The amplified fused signal is then passed to the transmitting transducer, which converts the electrical signal into an acoustic signal and transmits the amplified fused acoustic signal, enabling information transmission for communication with other devices or completing specific tasks.

[0097] Alternatively, as Figure 3As shown, the system also includes a power supply module, which includes a first-stage step-down module and a second-stage step-down module. The first-stage step-down module is used to convert the battery voltage into a first voltage, and the second-stage step-down module is used to convert the first voltage into a second voltage, wherein the first voltage is greater than the second voltage, and the second voltage is used to power the vector hydrophone, the preamplifier module, the A / D acquisition module, the signal processing module, the power amplification module and the transmitting transducer.

[0098] In this optional embodiment, the system also includes a power supply module for powering the entire system. It comprises two key components: a first-stage step-down module and a second-stage step-down module. The first-stage step-down module includes: The system's initial power source is a battery, whose output voltage is typically high and cannot directly meet the operating voltage requirements of the system's various power-consuming components. The first-stage step-down module converts the higher voltage output by the battery into a first voltage. This first voltage is lower than the battery voltage, but still higher than the operating voltage required by some components in the system. The second-stage step-down module further steps down the first voltage to convert it to a second voltage. It should be noted that during the entire step-down process, the first voltage is greater than the second voltage. The second voltage obtained after two stages of step-down can meet the power supply requirements of multiple key components in the system. For example, if the battery is 12V, the first-stage step-down module can use a step-down chip to convert 12V to 5V, 8V, and 10V, respectively. The second-stage step-down module uses two step-down chips to convert the 8V voltage converted by the first-stage step-down module to 5V and -5V, respectively, to power the AD acquisition module. The second-stage step-down module also uses two step-down chips to convert the 10V voltage converted by the first-stage step-down module to 6V and -6V, respectively, to power the preamplifier module. The second-stage step-down module also uses a step-down chip to convert the 5V voltage converted by the first-stage step-down module to 3.3V, which powers the signal processing module. The power amplifier module can also be powered directly from a 12V battery.

[0099] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention, and these changes and modifications will fall within the protection scope of the present invention.

Claims

1. A communication and positioning integrated sonar system, characterized in that: include: a communication module, configured to determine a communication algorithm based on the acquired communication distance and the signal-to-noise ratio of the original communication signal, modulate and encode the original communication signal using the communication algorithm to generate a communication code stream, wherein the communication algorithm includes an orthogonal frequency division multiplexing algorithm, a multi-ary frequency shift keying algorithm, or an orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm; The communication and positioning integration module is used to embed the preset original positioning signal into the communication code stream to generate a fusion signal through code multiplexing technology; A positioning module is used to determine a positioning algorithm based on the signal-to-noise ratio and coherent interference coefficient of the fused signal, and generate corresponding position information through the positioning algorithm based on the positioning information in the fused signal, wherein the positioning algorithm includes an acoustic energy flow method, a conventional beamforming algorithm, a minimum variance distortionless response algorithm or a multi-signal classification algorithm.

2. The communication and positioning integrated sonar system according to claim 1, characterized in that: The determining of the communication algorithm according to the acquired communication distance and the signal-to-noise ratio of the original communication signal includes: Obtaining a communication switching index through a preset communication switching index relationship according to the communication distance and the signal-to-noise ratio of the original communication signal; The communication algorithm is determined according to a comparison result between the communication switching indicator and a preset communication switching threshold.

3. The communication and positioning integrated sonar system according to claim 2, characterized in that: The communication switching threshold includes a first communication switching threshold and a second communication switching threshold, wherein the first communication switching threshold is less than the second communication switching threshold; and determining the communication algorithm according to a comparison result between the switching indicator and a preset communication switching threshold includes: When the switching indicator is less than or equal to the first communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing algorithm; When the switching index is greater than the first communication switching threshold and less than the second communication switching threshold, switching the communication algorithm to an orthogonal frequency division multiplexing-multi-ary frequency shift keying algorithm; When the switching index is greater than or equal to the second communication switching threshold, the communication algorithm is switched to a multi-ary frequency shift keying algorithm.

4. The communication and positioning integrated sonar system according to claim 2, characterized in that: The communication switching indicator relationship satisfies: Among them, R is the communication switching index, SNR is the signal-to-noise ratio of the original communication signal, D is the communication distance, K1 is the first switching coefficient, and K2 is the second switching coefficient.

5. The communication and positioning integrated sonar system according to claim 1, characterized in that: The determining of the positioning algorithm according to the signal-to-noise ratio and the coherent interference coefficient of the fused signal includes: When the coherent interference coefficient is greater than a preset coherent interference threshold, switching the positioning algorithm to a multi-signal classification algorithm; When the coherent interference coefficient is less than or equal to the coherent interference threshold, the positioning algorithm is determined according to a comparison result of the signal-to-noise ratio of the fused signal and a preset fusion signal-to-noise ratio threshold.

6. The communication and positioning integrated sonar system according to claim 5, characterized in that: The fused signal-to-noise ratio threshold includes a first fused signal-to-noise ratio threshold and a second fused signal-to-noise ratio threshold, wherein the first fused signal-to-noise ratio threshold is less than the second fused signal-to-noise ratio threshold; and determining the positioning algorithm according to the signal-to-noise ratio of the fused signal includes: When the signal-to-noise ratio of the fusion signal is less than or equal to a preset first fusion signal-to-noise ratio threshold, switching the positioning algorithm to the minimum variance distortionless response algorithm; When the signal-to-noise ratio of the fused signal is greater than the first fusion signal-to-noise ratio threshold and less than the second fusion signal-to-noise ratio threshold, switching the positioning algorithm to the conventional beamforming algorithm; When the signal-to-noise ratio of the fusion signal is greater than the second fusion signal-to-noise ratio threshold, the positioning algorithm is switched to the acoustic energy flow method.

7. The communication and positioning integrated sonar system according to claim 5, characterized in that: The coherent interference coefficient satisfies: Wherein, γ is the coherent interference coefficient, x is the fusion signal, and E is the mathematical expectation operation.

8. The communication and positioning integrated sonar system according to claim 1, characterized in that: It also includes an interaction module for performing human-computer interaction according to a preset mode, wherein the preset mode includes a communication mode, a positioning mode and a joint mode. The communication mode is used to perform human-computer interaction through a human-computer interaction interface, the positioning mode is used to display the location information of the target object through a full-screen map view, and the joint mode is used to display the communication interface and the map view separately through a split screen.

9. The communication and positioning integrated sonar system according to claim 1, characterized in that: It also includes a vector hydrophone, a preamplifier module, an A / D acquisition module, a signal processing module, a power amplifier module and a transmitting transducer; The vector hydrophone is used to obtain the fusion signal, and the signal processing module is used to send the fusion signal received after being processed by the pre-processing method module and the A / D acquisition module to the positioning module to implement the signal reception process; The signal processing module is used to send the fusion signal to the power amplification module, and the power amplification module amplifies the received fusion signal and sends it to the transmitting transducer. The transmitting transducer is used to transmit the received amplified fusion signal to realize the signal sending process.

10. The communication and positioning integrated sonar system according to claim 9, characterized in that: It also includes a power supply module, which includes a first-stage step-down module and a second-stage step-down module. The first-stage step-down module is used to convert the battery voltage into a first voltage, and the second-stage step-down module is used to convert the first voltage into a second voltage, wherein the first voltage is greater than the second voltage, and the second voltage is used to power the vector hydrophone, the preamplifier module, the A / D acquisition module, the signal processing module, the power amplification module and the transmitting transducer.

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