Ocean equipment underwater communication system and method based on distributed underwater networking

Abstract

The invention relates to the technical field of underwater communication, and discloses an ocean equipment underwater communication system and method based on distributed underwater networking. The method comprises the following steps: intelligently segmenting an underwater communication network of the ocean equipment to obtain a plurality of communication segments; and the user terminal issues an initial communication task instruction and controls the underwater equipment to start the task. When an initial task is executed, initial communication parameters of each communication section are collected, historical communication fault records are called, the fault level and the importance level of each communication section are determined accordingly, and a customized communication path is formulated according to the two levels. When executing a task according to a customized path, the underwater equipment collects own real-time position information and interference data of an interference source in a communication segment, determines whether the underwater equipment enters an interference area and records position coordinates, and generates an adjustment instruction if the underwater equipment judges that the underwater equipment deviates from the path; meanwhile, real-time communication signals are collected and analyzed, and when abnormity is detected, abnormal position coordinates and corresponding signals are obtained for a user terminal to process.

Description

Technical Field

[0001] This invention relates to the field of underwater communication technology, specifically to an underwater communication system and method for marine equipment based on distributed underwater networking. Background Technology

[0002] With the increasing intensity of marine development, marine equipment is being used more and more widely in fields such as resource exploration, environmental monitoring, and national defense. Underwater communication, as the core link for data transmission and command interaction of marine equipment, directly affects the operational effectiveness of marine equipment due to its stability and efficiency. Currently, underwater communication mainly relies on distributed networking technology to build communication networks. However, traditional distributed underwater networking still has many shortcomings in practical applications and is difficult to meet the needs of complex operational scenarios of marine equipment.

[0003] Traditional underwater communication networks lack proper segmentation of their network structure, operating under a unified management model. When the network covers a wide area and connects a large number of marine equipment, resource allocation becomes unbalanced, with some areas experiencing excessive resource consumption while others suffer from resource scarcity. This leads to increased communication latency, unstable data transmission rates, and even localized congestion, impacting overall communication efficiency. Furthermore, under this unified management model, a failure in one node can easily spread to surrounding nodes, causing wider communication outages. Fault localization is difficult, and troubleshooting and repair are time-consuming, further reducing the network's availability.

[0004] Traditional underwater communication path planning is mostly based on pre-set fixed paths, failing to fully integrate the real-time status and historical operational data of the communication network. The path planning process only considers basic factors such as distance and signal strength, neglecting the failure risk and importance of each communication segment. For example, some communication segments have a history of frequent failures, but the path planning fails to avoid or strengthen the protection of such areas, resulting in underwater equipment having a higher probability of passing through high-failure-risk communication segments when performing communication tasks, increasing the likelihood of communication failures. Furthermore, critical communication segments undertaking key data transmission tasks are not given priority in the path planning, easily leading to delays or loss of critical data transmission due to insufficient resource allocation, affecting the timeliness of marine equipment operational decisions.

[0005] The underwater environment is complex and variable, with various interference sources such as ocean currents, water temperature changes, underwater biological activity, and human interference. These sources can strongly affect underwater communication signals, leading to signal attenuation and distortion. Traditional underwater communication methods lack real-time monitoring and dynamic response mechanisms for interference sources, making it impossible to promptly detect whether underwater equipment has entered an interference zone. When underwater equipment mistakenly enters an interference zone, it cannot quickly adjust its communication path and continues to transmit data along the original path, easily leading to increased interference and problems such as data transmission errors and communication interruptions. Furthermore, traditional methods are not timely in detecting and handling communication anomalies. Problems are usually only discovered after obvious errors or interruptions in data transmission occur, and it is difficult to quickly locate the location of the anomaly or obtain real-time communication signal data at the time of the anomaly. This makes it impossible for user terminals to accurately determine the cause of the anomaly, and subsequent troubleshooting and repair work lacks effective basis, further prolonging communication recovery time.

[0006] In traditional underwater communication methods, the position monitoring and communication path adjustment of underwater equipment are independent, lacking a coordinated mechanism. When underwater equipment deviates from the predetermined communication path due to factors such as water current impact and fluctuations in its own propulsion system, the position monitoring system, while detecting the position shift, cannot promptly coordinate with the communication path adjustment module. This results in a delay in generating path adjustment commands, allowing the underwater equipment to continue communicating while off-path. This not only increases the instability of the communication signal but may also cause the underwater equipment to deviate from the operational area, affecting the overall operational progress. These problems make traditional underwater communication methods ill-suited to the complex and ever-changing underwater environment, unable to provide stable and reliable communication support for marine equipment, and hindering further improvements in the operational capabilities of marine equipment. Summary of the Invention

[0007] The purpose of this invention is to provide an underwater communication system and method for marine equipment based on distributed underwater networking, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides an underwater communication method for marine equipment based on distributed underwater networking, the method comprising: The underwater communication network of marine equipment is intelligently segmented into multiple communication segments. The user terminal issues an initial communication task command, controlling the underwater equipment to initiate the communication task upon receiving the command. During the execution of the initial communication task, initial communication parameters for each communication segment are collected, and stored historical communication fault records are retrieved. Based on the initial communication parameters and the historical communication fault records, the fault level and importance level of each communication segment are determined. A customized communication path is then developed for the underwater equipment based on the importance level and the fault level. During the execution of communication tasks according to the customized communication path, the underwater equipment collects real-time position information and acquires interference data corresponding to interference sources in the communication segment; confirms whether the underwater equipment has entered the interference area, and records the real-time position coordinates of the underwater equipment within the interference area when an offset detection signal is generated; determines whether the underwater equipment has deviated from the predetermined communication path within the interference area based on the real-time position coordinates, and generates a path adjustment command if it has deviated; collects real-time communication signals of the communication segment and analyzes the real-time communication signals in real time; when a communication anomaly is detected, acquires the abnormal position coordinates and the corresponding real-time communication signals for processing by the user terminal.

[0009] Preferably, the initial communication parameters include the available bandwidth of the communication segment and the data transmission error rate; the historical communication fault record includes the number of historical faults in the communication segment and the average interruption duration for each fault.

[0010] Preferably, the process of determining the fault level and importance level of each communication segment specifically includes: Obtain the historical number of faults for each communication segment, and query the average interruption duration for each fault in each communication segment. Multiply the historical number of faults by the average interruption duration to obtain the fault index for each communication segment. The fault indicators are compared with preset fault thresholds, and the fault level of the communication segment is classified into high fault level, medium fault level or low fault level based on the comparison results. At the same time, the available bandwidth and data transmission error rate of each communication segment are obtained, and the importance index of each communication segment is obtained by dividing the available bandwidth by the data transmission error rate. The importance index is compared with the preset importance threshold, and the importance level of the communication segment is divided into high importance level, medium importance level or low importance level according to the comparison result.

[0011] Preferably, the process of determining the customized communication path for underwater equipment communication specifically includes: The underwater equipment starts from its initial position and prioritizes communication segments with high importance. When multiple communication segments have the same importance level, underwater equipment selects the communication segment with the higher failure level for communication. When the importance level and the fault level are the same, the underwater equipment selects the communication segment closest to its current location for communication. When underwater equipment encounters a network node during communication, it checks the status of the communication segment connected to the node. If a node connects to multiple communication segments, the underwater equipment processes the communication segments in descending order of importance. Once all communication segments have been completed, the underwater equipment returns to its starting position. Underwater equipment uses different transmission power for data transmission in communication segments of different importance levels.

[0012] Preferably, the interference data includes the geographical coordinates of the interference source, the maximum value of the interference signal strength, and the duration of the interference.

[0013] Preferably, the process of confirming whether the underwater equipment has entered the interference zone specifically includes: Real-time monitoring of signal strength around underwater equipment; When the signal strength exceeds a preset strength threshold, it is determined that the underwater equipment has entered the interference zone; Record the real-time position coordinates and current timestamp of the underwater equipment to generate an offset detection signal.

[0014] Preferably, the process of determining whether the underwater equipment has deviated from the predetermined communication path within the interference area based on the real-time position coordinates specifically includes: Compare the real-time position of the underwater equipment with the expected position along the predetermined path; Calculate the Euclidean distance between the real-time location and the desired location; When the Euclidean distance exceeds the allowable deviation value, a path adjustment command is generated; the path adjustment command includes new heading angle and speed values.

[0015] Preferably, the process of real-time analysis of the real-time communication signal specifically includes: The received real-time communication signals are noise-reduced by using digital filters to remove high-frequency noise. Extract the time-domain features of real-time communication signals, including the mean and variance of amplitude; Extract the frequency domain features of real-time communication signals, including the main frequency components and bandwidth; The time-domain and frequency-domain features are matched with the feature library of normal communication modes; when the feature matching degree is lower than the preset threshold, the signal is marked as abnormal, and the occurrence time and location coordinates of the abnormal signal are recorded.

[0016] Preferably, the method further includes: After completing the real-time communication signal analysis, the abnormal signal data is stored in the historical database; Based on anomaly records in the historical database, dynamically adjust the generation rules for customized communication paths.

[0017] Preferably, the present invention also includes an underwater communication system for marine equipment based on distributed underwater networking. The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the underwater communication method for marine equipment based on distributed underwater networking as described above.

[0018] Compared with the prior art, the beneficial effects of the present invention are: By intelligently segmenting the underwater communication network, the limitations of the traditional unified management model are broken, enabling the network to form multiple independent yet collaborative communication segments. This segmentation method allows for refined allocation of network resources. Based on the actual situation of each communication segment, such as the number of equipment and transmission requirements, resources such as communication bandwidth and power are rationally allocated, avoiding resource imbalance, reducing communication delays and congestion, and improving overall communication efficiency. Simultaneously, segmented management makes each communication segment a relatively independent operating unit. When a fault occurs in one communication segment, the fault is confined to that segment, making it less likely to spread to other segments and reducing the risk of large-scale communication outages. Furthermore, fault location only needs to be performed within a single communication segment, simplifying the fault diagnosis process, shortening fault repair time, and improving the availability and stability of the communication network.

[0019] In terms of communication path planning, this method combines initial communication parameters with historical communication failure records to determine the fault level and importance level of each communication segment, providing a comprehensive and accurate basis for path planning. Based on the fault level, communication segments with frequent historical failures and high current failure risk can be prioritized and avoided during path planning, or paths passing through such communication segments can be optimized for protection, reducing the probability of underwater equipment encountering failures during communication. Based on the importance level, important communication segments undertaking critical data transmission tasks can be given priority resource protection, ensuring that critical data can be transmitted quickly and stably, meeting the command interaction and data feedback needs of key operational links of marine equipment. Compared with traditional fixed path planning, this customized path planning method is more adaptable to the actual operating conditions of underwater communication networks, improving the rationality and reliability of communication paths.

[0020] To address complex underwater interference environments, this method establishes a real-time monitoring and dynamic response mechanism. By collecting real-time location information of underwater equipment and interference data from sources within the communication segment, it can promptly detect whether underwater equipment has entered an interference zone. When underwater equipment is detected entering an interference zone and a deviation detection signal is generated, the real-time position coordinates are recorded to accurately determine the equipment's positional changes within the interference zone, thereby quickly identifying whether it has deviated from the predetermined communication path. Once a deviation is detected, a path adjustment command is immediately generated to guide the underwater equipment to avoid the interference zone or adjust to a path with less signal interference, reducing the impact of interference sources on the communication signal, ensuring the continuity and accuracy of data transmission, and preventing communication interruptions or data loss due to interference.

[0021] This method enables timely detection of communication anomalies by real-time acquisition and analysis of communication signals within the communication segment. Upon detection of an anomaly, the system rapidly acquires the anomaly's location coordinates and corresponding real-time communication signal, synchronizing this information to the user terminal. This allows the user terminal to quickly grasp the specific location and status of the anomaly, providing direct reference for determining its cause. This timely anomaly feedback and information provision helps the user terminal quickly formulate response strategies, shorten anomaly handling time, and reduce the impact of communication anomalies on marine equipment operations. Furthermore, the coordinated operation of location monitoring and path adjustment, signal analysis, and anomaly feedback creates a closed-loop management system for the entire underwater communication process, further enhancing the adaptability, stability, and reliability of underwater communication. This better meets the communication needs of marine equipment in complex underwater environments, providing strong support for efficient marine equipment operations. Attached Figure Description

[0022] Figure 1 This is a schematic diagram illustrating the working principle of the marine equipment underwater communication method based on distributed underwater networking as described in this invention. Figure 2 A flowchart for determining the fault level and importance level of each communication segment; Figure 3 A flowchart for determining whether underwater equipment deviates from the predetermined communication path within the interference area. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1This invention provides an underwater communication method for marine equipment based on a distributed underwater network. The method includes: intelligently segmenting the underwater communication network of the marine equipment into multiple communication segments; a user terminal issuing an initial communication task command; and controlling the underwater equipment to initiate a communication task upon receiving the initial communication task command. During the execution of the initial communication task, initial communication parameters for each communication segment are collected, and stored historical communication fault records are retrieved. Based on the initial communication parameters and historical communication fault records, the fault level and importance level of each communication segment are determined. A customized communication path is then formulated based on the importance level and fault level for underwater equipment communication. During the execution of the initial communication task, the underwater equipment first traverses each communication segment through a built-in parameter acquisition module, collecting the available bandwidth and data transmission error rate of each communication segment in real time. These two types of data together constitute the initial communication parameters. Simultaneously, the underwater equipment accesses the system database through a communication interface to retrieve historical communication fault records for each communication segment, specifically including the number of historical faults and the average interruption duration corresponding to each fault. After data acquisition, the processing module first calculates the fault indicators for each communication segment, multiplying the historical fault occurrence count by the average interruption duration, and then comparing the fault indicators with preset fault thresholds to classify them into high, medium, and low fault levels. Simultaneously, it calculates the importance indicators, dividing the available bandwidth by the data transmission error rate and combining this with preset importance thresholds to classify them into high, medium, and low importance levels. After level determination, the path planning engine calls preset decision rules, prioritizing importance level, followed by fault level, and then distance, to select suitable communication segments. These segments are then logically concatenated to form a customized communication path for the underwater equipment. The path data is synchronously stored in the equipment's local storage unit and fed back to the user terminal. When the underwater equipment executes communication tasks according to the customized communication path, it continuously collects real-time location information and acquires interference data corresponding to interference sources within the communication segment. By confirming whether the underwater equipment has entered the interference area, it records the real-time position coordinates of the underwater equipment within the interference area when generating an offset detection signal. Based on the real-time position coordinates, it determines whether the underwater equipment has deviated from the predetermined communication path within the interference area, and generates a path adjustment command if deviation occurs. Simultaneously, real-time communication signals of the communication segment are collected and analyzed in real time. When an anomaly is detected during analysis, the coordinates of the anomaly location and the corresponding real-time communication signal are obtained for the user terminal to perform subsequent processing.

[0025] Example 1: See Figure 2After intelligent segmentation, the underwater communication network of marine equipment forms multiple logically independent communication segments, each constituting a basic communication unit in the network. Initial communication parameters are crucial indicators for evaluating the basic performance of a communication segment, including its available bandwidth and data transmission error rate. Available bandwidth reflects the theoretical data transmission capacity of the communication segment per unit time, while the data transmission error rate characterizes the reliability level of data transmission. Historical communication fault records provide objective data on the past operating status of the communication segments. Specifically, these records show the number of historical faults occurring for each communication segment within a set historical period, as well as the average interruption duration corresponding to each fault event. The number of historical faults records the frequency of communication segment failures, and the average interruption duration quantifies the sustained impact of each fault on communication services. Determining the fault level of each communication segment requires establishing a quantitative evaluation model, obtaining the number of historical faults occurring for each communication segment within the historical period, and querying the database to obtain the average interruption duration data corresponding to each fault event. The fault index of a communication segment is calculated using a multiplicative model, multiplying the number of historical faults of the communication segment by the average of the average interruption durations of all fault events to obtain a comprehensive fault index value. The calculation formula is as follows: in, This represents the total number of communication segment failures within a specified historical period. This represents the total time from occurrence to recovery of all failure events divided by the number of failures.

[0026] If a communication segment has a historical fault occurrence count within a 30-day historical period, The interruption durations for the five faults were 2 hours, 3 hours, 2.5 hours, 4 hours, and 3.5 hours, respectively. What is the average interruption duration for all fault events? Hours, substituting into the formula, yield the fault index. .

[0027] The higher the value of this fault indicator, the worse the historical reliability of the communication segment. The preset fault threshold is a pre-defined baseline value, which may include multiple threshold levels to divide different fault ranges. The calculated fault indicator is compared with the preset fault threshold. Based on the threshold range in which the fault indicator falls, the communication segment's fault level is classified into three levels: high fault level, medium fault level, or low fault level. A high fault level means the communication segment has a higher probability of failure and a longer history of service interruptions, while a low fault level indicates that the communication segment's historical operating status is relatively stable.

[0028] The importance assessment of communication segments focuses on their current inherent communication capabilities, obtaining real-time initial communication parameters for each segment, including available bandwidth and data transmission error rate. The importance index of a communication segment is calculated using a ratio method, dividing the available bandwidth by the data transmission error rate to obtain a value characterizing the overall level of communication efficiency and quality. The calculation formula is as follows: in, This represents the maximum data capacity that a communication segment can transmit per unit of time. This represents the proportion of erroneous data during transmission to the total amount of data transmitted.

[0029] If the available bandwidth of a certain communication segment (kilobits per second), data transmission error rate (i.e., an error rate of one in a thousand), substituting these values ​​into the formula yields the importance index. . A higher importance index value means that the communication segment can theoretically support higher-speed and more reliable data transmission. The preset importance threshold is also a predefined grading benchmark. By comparing the calculated importance index with the preset importance threshold, the communication segment's importance level is classified as high importance, medium importance, or low importance based on the threshold range in which the importance index falls. High importance identifies high-quality communication segments with ample bandwidth resources and high transmission quality; these segments are ideal for carrying critical data transmission tasks.

[0030] The classification of fault levels and importance levels is performed in parallel, with the two assessment systems characterizing the communication segment's features from different dimensions. Fault levels are based on historical performance data of the communication segment, representing a backward-looking reliability assessment. Importance levels are based on current capability parameters of the communication segment, representing a forward-looking performance potential assessment. The specific values ​​of preset fault thresholds and preset importance thresholds need to be initialized during system deployment based on network scale, business requirements, and historical data statistical analysis, and can be dynamically optimized and adjusted during system operation based on actual operating conditions. The statistics of historical fault occurrences need to define a clear time window, such as the past thirty days or the past year, and the calculation of average outage duration needs to cover the complete time cycle from fault occurrence to fault repair. Available bandwidth needs to be collected in real-time using network probing tools, and the acquisition of data transmission error rate relies on the error rate statistics function of the receiving end. The fault index calculation model for the communication segment combines the impact of fault frequency and fault duration; a communication segment with frequent faults and long durations of each fault will obtain extremely high fault index values. The importance index calculation model for communication segments balances the sometimes mutually restrictive factors of bandwidth and quality. A communication segment with high bandwidth but also a high bit error rate may have a lower importance index than a communication segment with moderate bandwidth but an extremely low bit error rate. The output of fault level classification directly reflects the historical stability of the communication segment, while the output of importance level classification reveals the current availability value of the communication segment. The algorithm for generating customized communication paths simultaneously receives fault level and importance level as key input parameters. Communication segments with high importance levels are given priority for inclusion in the communication path, while communication segments with high fault levels are avoided as much as possible. This level evaluation mechanism provides a data-driven decision-making basis for intelligent path planning of underwater equipment, enabling the selection of communication paths to consider not only geographical distance but also network link quality and reliability factors more deeply.

[0031] The division of communication segments is dynamic. As the network topology changes or nodes are added or removed, the definition and scope of communication segments may change. Therefore, the initial collection of communication parameters and the assessment of fault level importance need to be periodic or event-triggered. Records of historical fault occurrences must be accurate to avoid counting errors caused by false alarms or brief fluctuations. The calculation of average outage duration requires precise timestamp records. Measurement of available bandwidth needs to consider the impact of network background traffic, and the statistics of data transmission error rate need to be based on a sufficient number of data packets to ensure statistical significance. The setting of preset fault thresholds needs to refer to the overall distribution of fault indicators across all communication segments in the entire network, while the setting of preset importance thresholds needs to be combined with the actual bandwidth and error rate requirements of specific applications. High-fault-level communication segments indicate that network maintenance personnel need to pay attention to potential problems in that link, while high-importance communication segments enjoy higher priority in resource allocation and routing strategies. A three-level classification method is used for fault level division. This classification provides sufficient granularity to distinguish the reliability differences of communication segments while avoiding the decision-making complexity caused by overly complex multi-level classifications. Importance level division also uses a three-level classification to maintain the consistency of the assessment system. The fault index is calculated using multiplication, which amplifies the negative impact of the combination of high fault frequency and long fault duration, aligning with the intuitive logic of communication reliability assessment. The importance index is calculated using division, highlighting the combined advantages of high bandwidth and low bit error rate. Two preset fault thresholds divide the fault index value range into three consecutive intervals, corresponding to high, medium, and low fault levels. Two preset importance thresholds work in the same manner, mapping the importance index value range to three importance levels. The entire assessment process is automatically executed by the system's data processing module without manual intervention, and the assessment results are written to the database for querying by the path planning module. The communication segment's identifier is associated with its corresponding fault level and importance level information, forming a real-time updated network status view.

[0032] Before initiating a communication mission, the underwater equipment's path planning engine queries the database for the latest fault and importance levels of all relevant communication segments. The definition of a communication segment covers all possible network paths the underwater equipment might traverse from its origin to its destination. The historical fault record database persistently stores detailed logs of each fault event, including fault start time, fault end time, and fault type identifier. The available bandwidth in the initial communication parameters may be a dynamically changing value; the path planning engine can obtain its instantaneous value or its average value over a period of time. Within one hour, the instantaneous available bandwidth of the communication segment at different times is 95... 102 98 105 99 The average available bandwidth during that period is The data transmission error rate is usually calculated within a statistical time window. In a 10-minute statistical time window, if the total transmitted data volume is 100,000 bits, and the erroneous data volume is 50 bits, then the data transmission error rate is... Multiplicative and ratio models are among the many feasible mathematical models available, offering advantages such as computational simplicity and clear meaning. The classification of fault levels and importance levels is ultimately translated into labels or weights that can be processed by the path decision algorithm. High-importance communication segments may be assigned negative cost weights in the path cost function to attract water flow equipment selection, while high-fault-level communication segments are assigned positive cost weights to increase their likelihood of being avoided.

[0033] Example 2: Developing a customized communication path for underwater equipment is a dynamic process based on multi-objective decision-making. The underwater equipment starts from the initial position specified by the user terminal, and the path planning engine generates an initial route based on the importance and fault levels of communication segments. After the path planning engine starts, it first loads the coordinates of the initial position specified by the user terminal, the location information of the target communication nodes, and the importance and fault level data of each communication segment to construct an initial network topology model. Using importance level as the core sorting criterion, communication segments with higher importance levels are prioritized for inclusion in the candidate path set. When multiple communication segments have the same importance level, communication segments with lower fault levels are prioritized to reduce the risk of failure. If both importance and fault levels are the same, the straight-line distance between the endpoints of each communication segment and the current equipment position is calculated, and the closest communication segment is selected to join the path. The path planning engine also checks the status of the connection nodes between communication segments to ensure that the communication segments in the candidate path are continuously connected through valid nodes, avoiding path breaks. After the initial route is generated, the engine performs smooth optimization, eliminating unreasonable turns or sharp angles to form an initial route that conforms to the underwater equipment's motion characteristics. Route data includes the coordinate range of each path segment, estimated travel time, and the location of key nodes. The logic for generating customized communication paths assigns the highest priority to communication segments based on their importance level. Underwater equipment always prioritizes communication segments with higher importance levels from among the available paths, as these segments signify superior communication capabilities, ensuring high data transmission rates and high reliability. When multiple communication segments with the same importance level exist ahead of the underwater equipment, the decision-making logic introduces fault level as a secondary criterion. The underwater equipment selects the communication segment with the highest fault level for communication. Although communication segments with higher fault levels have historically lower stability, they may connect to key nodes or possess unique network value. Including them in path planning when importance levels are equal can serve as a risk-reward balancing strategy. If multiple communication segments have the same importance level and the same fault level, the distance optimization principle is used. The underwater equipment selects the communication segment with the closest spatial geometric distance from the current position as the next hop. This principle helps to reduce travel time and energy consumption.

[0034] During communication, underwater equipment moves along a customized communication path and encounters various nodes in the network. Network nodes are the intersections or relay points of multiple communication segments. When the underwater equipment encounters a network node, a node processing routine is triggered to check the real-time status of all communication segments connected to the node. The communication segment status includes the real-time connectivity of the link, the current load, and the latest channel quality indicators. If the node connects to multiple communication segments, and these segments are all available and active, the underwater equipment needs to determine the order in which to process these communication segments. The processing order strictly follows the importance level of the communication segments from highest to lowest, with higher-importance communication segments being accessed and data exchanged first. This sequential processing mechanism ensures that the most important communication tasks are served first, and core communication tasks are guaranteed even if the underwater equipment's stay time is limited or the network status changes. If all communication segments connected to the node have completed the preset communication tasks, such as data acquisition, command reception, or information forwarding, the underwater equipment's task at this node is considered complete. The underwater equipment returns to the starting position preset by the user terminal. The return path can be either the original route or a new optimal path recalculated by the path planning engine. Underwater equipment employs differentiated transmission power for data transmission in communication segments of varying importance. Adjusting transmission power is a crucial component of customized communication path strategies. For high-importance communication segments, underwater equipment is configured with relatively high transmission power. Stronger signal transmission power helps improve the signal-to-noise ratio, counteracts underwater channel attenuation, and ensures the integrity of critical data transmission over high-quality links. For medium-importance communication segments, underwater equipment uses standard transmission power, striking a balance between communication quality and equipment power consumption. In low-importance communication segments, underwater equipment uses lower transmission power. Lower power settings conserve the equipment's limited energy and reduce electromagnetic interference to the entire cyberspace. Dynamic adjustment of transmission power relies on the underwater equipment's built-in power control module. This module receives instructions from the path planning engine, which include the importance level information of the current communication segment. The power control module automatically adjusts the output power of the RF front-end or acoustic transducer according to a predefined power level mapping table.

[0035] The power control module integrates a microprocessor, signal conversion unit, and power drive circuit. A predefined power level mapping table is stored in the module's local flash memory, clearly associating high, medium, and low importance levels with their corresponding output power reference values. When underwater equipment enters a communication segment, the path planning engine sends a command to the power control module via the internal bus, carrying the importance level identifier of that communication segment. Upon receiving the command, the power control module's microprocessor parses the importance level information, retrieves the predefined power level mapping table, and determines the corresponding target output power value. The signal conversion unit converts the target power value into an analog control signal, which is transmitted to the power drive circuit. The drive circuit adjusts the supply voltage or current according to the control signal, thereby changing the operating power of the RF front-end or acoustic transducer to achieve precise matching and adjustment of the output power. During the adjustment process, the module's built-in power detection element provides real-time feedback on the actual output power, comparing and calibrating it with the target value to ensure that the power output remains stable within the set range.

[0036] The generation of customized communication paths is not a one-time static planning, but a dynamic adjustment process that runs throughout the communication mission. Real-time location information of underwater equipment, remaining energy status, and real-time changes in network topology are all fed back into the path planning engine. The decision-making algorithm built into the path planning engine comprehensively considers multiple factors such as the importance level of communication segments, the fault level of communication segments, real-time distance, node load, and the underwater equipment's own status to generate globally optimized movement commands. The decision-making algorithm built into the path planning engine adopts a multi-factor weighted decision-making mechanism. First, weight coefficients are assigned to the importance level, fault level, real-time distance, node load, and the underwater equipment's own status. These weight coefficients are pre-configured based on the priority requirements of underwater communication. During path calculation, the algorithm first extracts the importance level and fault level data of each candidate communication segment and converts them into basic decision scores according to their weights. Simultaneously, it obtains the real-time distance between the equipment and each communication segment through distance sensors, and combines this with the node data transmission pressure fed back by the node load monitoring module to convert distance and load into auxiliary decision scores. Finally, it collects the underwater equipment's remaining energy, current speed, and other status data, converting them into constraint decision scores. The algorithm comprehensively accumulates various scores to obtain a total score for each candidate path, and prioritizes the path with the highest total score as the recommended path. During the decision-making process, the algorithm also verifies the connectivity and feasibility of the path, excluding paths with node failures, communication interruptions, or those exceeding the equipment's movement capabilities. Finally, it generates a globally optimized travel instruction, which includes the path node sequence, turning timing, and the estimated time to traverse each segment.

[0037] Network node status checks include handshake protocols and link quality detection to ensure the accuracy and timeliness of communication segment status information acquired by underwater equipment. The descending order of communication segment processing is an application of a greedy algorithm, prioritizing the processing of the most valuable communication segments at each local selection step to achieve optimal global communication efficiency. The logic of returning to the starting position allows underwater equipment to return to a known and controllable location after completing its mission, facilitating retrieval or receiving the next mission command. Differentiated transmission power configuration reflects the principle of on-demand resource allocation, prioritizing valuable energy resources for the most important communication links and optimizing the overall system energy efficiency. The entire customized communication path execution process demonstrates the adaptability and intelligence of the underwater mobile communication network. Underwater equipment no longer simply moves along a fixed route but can intelligently select paths and adjust behavior based on network status and mission requirements, ultimately achieving efficient and reliable underwater communication.

[0038] The starting position of underwater equipment is typically a pre-defined coordinate point on an underwater docking station or within the mission area. The path planning engine can run on the user terminal's control system or distributed within the underwater equipment's own computing unit. Checking the communication segment status of node connections requires exchanging control signaling between the underwater equipment and the nodes, carrying link status request and response information. The importance and fault level information of communication segments is stored in a database at the network center or distributed across various network nodes for the underwater equipment to query during decision-making. Distance calculation is usually based on the three-dimensional spatial coordinates of the underwater equipment, network nodes, and communication segment endpoints, using the Euclidean distance formula. A transmission power level mapping table defines the correspondence between importance level enumeration values ​​and specific power values. This mapping table can be remotely configured and updated via a ground station. The transmission power level mapping table is a data table stored in the underwater equipment control system. The table uses the importance level enumeration values ​​of the communication segment (high importance, medium importance, low importance) as index entries, with each index entry corresponding to a unique specific power value. This value is pre-set based on the underwater communication signal transmission requirements, channel characteristics, and equipment energy consumption standards. The ground station establishes a remote connection with the underwater equipment via an underwater acoustic communication link. Operators can view the current mapping table configuration data on the ground station's control interface. Based on actual communication mission requirements, changes in the marine environment, or adjustments to equipment performance, they can modify the power values ​​corresponding to each importance level, and also add or delete mapping relationships. After modification, the ground station packages and transmits the updated mapping table data to the underwater equipment. Upon receiving the data, the equipment overwrites the original stored mapping table data, ensuring that subsequent power adjustments are executed according to the latest configuration, achieving flexible adaptation of the power control strategy. Node processing routines ensure that the underwater equipment can complete communication tasks across multiple links in an orderly and efficient manner at complex network intersections. Return path calculations may consider new network conditions, selecting a different path than the incoming path to avoid newly emerging congestion or faults. Dynamic power control not only saves energy but also helps extend the underwater equipment's endurance and has a positive impact on the electromagnetic compatibility of the underwater communication environment. The final form of a customized communication path is a sequence of network nodes and communication segments. This path is initially generated before the communication task begins and is continuously fine-tuned during the task execution to adapt to the dynamic changes in the underwater acoustic channel and network topology.

[0039] Example 3: The interference data consists of the geographic coordinates of the interference source, the maximum value of the interference signal strength, and the interference duration. The geographic coordinates of the interference source define the origin of the interference energy radiation in three-dimensional space, and its numerical representation is usually longitude, latitude, and depth relative to a reference plane in a geodetic coordinate system. The maximum value of the interference signal strength reflects the maximum radiated power density that the interference source transmitter can produce under ideal conditions, while the interference duration describes the length of the complete working period from activation to deactivation of the interference source. The process of confirming whether underwater equipment has entered the interference zone relies on continuous measurement of the electromagnetic or acoustic field strength around the underwater equipment. Real-time monitoring of the signal strength around the underwater equipment is accomplished by a broadband sensor array integrated on the equipment itself. The sensor array scans the target frequency band at a constant sampling period, quantifying and recording the signal energy distribution in the environment. When the real-time monitored signal strength value continuously exceeds a preset strength threshold, the state machine inside the system transitions, and the logic judgment unit determines that the underwater equipment has entered the interference zone. The preset strength threshold is a threshold value determined based on historical channel measurement data and the sensitivity of the communication system, used to identify harmful artificial interference signals in complex marine background noise. The real-time position coordinates of the underwater equipment and the time information of its entry into the interference area are captured and recorded synchronously. The real-time position coordinate data comes from the combined navigation system that integrates an inertial measurement unit and a Doppler log. The precise timestamp is generated by a timing circuit synchronized with the system's master clock. The offset detection signal is sent to the subsequent processing module as the output command triggered by this event.

[0040] The geographic coordinate database of interference sources needs to be maintained and updated regularly to adapt to changes in the underwater environment or to cope with changes in the trajectory of mobile interference sources. The nominal value of the maximum interference signal strength helps the system predict impact and plan avoidance paths before interference occurs. Prior knowledge of the interference duration is valuable for handling periodically occurring interference patterns, allowing the system to schedule communication silence or switch to anti-interference mode within a time window. The signal strength value obtained from real-time monitoring is a stochastic process that fluctuates with time and space; its statistical characteristics are influenced by underwater multipath effects, seawater temperature and salinity profiles, and the relative motion between the equipment and the interference source. Setting the preset strength threshold involves a trade-off between false alarm probability and detection probability. An overly conservative threshold reduces the system's ability to perceive real threats, while an overly sensitive threshold leads to frequent misjudgments and disrupts normal communication processes. The decision to determine if underwater equipment has entered the interference zone marks a change in the system's operating state; communication strategies and control logic will be adjusted accordingly to maintain link reliability. The precise recording of real-time location coordinates and timestamps forms the data foundation for post-event analysis and system optimization, enabling each interference event to be accurately reproduced in the spatiotemporal dimension. In addition to basic event identifiers, the offset detection signal can also contain preliminary estimates of interference intensity, spectral feature summaries, and other information, providing shared situational information for collaborative anti-interference in distributed networks.

[0041] The boundary of the interference zone is not fixed; its spatial shape is jointly shaped by the radiation pattern of the interference source, the signal frequency, and the propagation loss characteristics of the water medium. The algorithm for confirming underwater equipment entering the interference zone can employ statistical signal processing methods to enhance robustness. For example, a moving average of the signal strength over multiple consecutive sampling periods can be used; only when the average exceeds a threshold and remains there for a period is a state change confirmed. This effectively suppresses false triggers caused by instantaneous noise spikes. The accuracy of real-time position coordinates directly determines the accuracy of the system's tracking of the underwater equipment's trajectory within the interference zone. Therefore, the filter design of the integrated navigation system must fully consider the special disturbance factors of the underwater environment. The synchronization accuracy of timestamps is particularly important in distributed networking applications, as it is key to associating observation events from different nodes and constructing a unified situational awareness map. The offset detection signal generation mechanism should be configurable, allowing adjustment of the stringency of the criteria according to mission requirements. For example, a more sensitive setting can be used when performing high-priority tasks to minimize risk. Dynamic updates to the interference source database can be achieved through periodic scanning or receiving broadcast information from external intelligence data chains. The maximum strength of interference signals may exhibit directional non-uniformity in real-world environments, meaning the interference source antenna possesses directional gain. The accuracy of interference duration prediction depends on the depth of understanding of the interference source's operating mode; prediction becomes extremely difficult for intelligent interference employing complex transition or burst patterns. Real-time monitoring channels may require automatic gain control to handle large dynamic range variations in signal strength, preventing receiver saturation or the drowning out of small signals. Preset strength thresholds can be designed to adapt to ambient noise levels, dynamically fluctuating with changes in background noise to maintain constant detection performance. Hysteresis characteristics of the decision logic can be achieved by setting different "entry thresholds" and "exit thresholds," with the exit threshold slightly lower than the entry threshold to prevent frequent oscillations in boundary regions. The data format for real-time position coordinates should be standardized, including coordinate system definitions, accuracy metrics, and other information to ensure data universality. Timestamp acquisition requires hardware support to provide sufficient accuracy and stability. The transmission channel for offset detection signals should have high priority to ensure reliable reception under harsh underwater channel conditions.

[0042] To quantify the degree of interference threat rather than simply making a binary judgment of area entry and exit, a mathematical model is needed that comprehensively reflects interference intensity, distance attenuation, and time effects. Interference Area Impact Index The calculation formula is defined as follows: in: This represents the maximum value of the interference signal strength. It is a reference power constant; This represents the Euclidean distance from the underwater equipment to the geographic coordinates of the interference source. It is a very small positive number used to avoid division by zero errors. It is a reference distance constant; It is the path loss index, the value of which is determined by the actual underwater acoustic or electromagnetic wave propagation environment. Represents the remaining duration of the interference, i.e. , This is a reference time constant. Interference area impact index. It is a dimensionless value, and the larger the value, the higher the potential threat level of the current interference to the communication of underwater equipment.

[0043] like Take 48dBμV / m, Take 10 dBμV / m, Take 210 meters, Take 1 meter, Take 100 meters, Take 2.3, Take 38 minutes. Take 60 minutes. First, go through... Calculate the normalized value of the interference intensity and obtain First, quantify the intensity level of the interference source itself; then calculate the distance attenuation factor. ,That The power is This demonstrates the principle that interference attenuation becomes more significant with increasing distance; next, the time influence factor is calculated. This reflects the impact of the remaining interference time on the threat persistence risk. The distance attenuation factor is then multiplied by the time influence factor to obtain the denominator comprehensive factor. Finally, by dividing the numerator by the denominator, the influence index of the interference area is obtained. The effect of this index is reflected in: This indicates that the current interference threat is at a low to moderate level, not reaching the high threat threshold requiring urgent path adjustments. Example 4: See Figure 3The process of determining whether underwater equipment has deviated from the predetermined communication path within an interference area based on real-time position coordinates relies on precise spatial positioning and path tracking algorithms. Comparing the underwater equipment's real-time position with the expected position along the predetermined path requires first obtaining the equipment's current three-dimensional spatial coordinates from the integrated navigation system. The underwater equipment's integrated navigation system integrates data from the inertial measurement unit, Doppler log, and underwater acoustic positioning module, continuously outputting the equipment's current three-dimensional spatial coordinates, including longitude, latitude, and depth information. This coordinate data is updated periodically and synchronized to the path tracking module. The path tracking module pre-stores the complete coordinate sequence of the predetermined communication path, including the three-dimensional coordinates of all key path points and the connection relationships of path segments. During the determination process, the path tracking module first extracts the real-time three-dimensional coordinates output by the integrated navigation system, and then, based on the equipment's speed and the time of the last position update, calculates the expected three-dimensional coordinates of the equipment on the predetermined path at the current moment using a linear interpolation algorithm. The module compares the real-time three-dimensional coordinates with the expected three-dimensional coordinates dimension by dimension, clarifying the spatial differences between the two, providing accurate data support for subsequent determination of whether the equipment has deviated from the path. The calculation of the desired location relies on a mathematical model of the predetermined communication path. This model typically consists of a series of ordered path point coordinates and line segments or curve functions connecting these path points. Based on the underwater equipment's speed and the timestamp of its most recent position update, the system uses an interpolation algorithm to calculate the theoretically desired location the equipment should reach at the current moment. If a linear interpolation algorithm is used, let the coordinates of the underwater equipment at its most recent position update be... The corresponding timestamp is The current time is The underwater equipment moves at a speed of (The direction of velocity is along the predetermined path from) Point to the next path point First, calculate the time difference from the most recent position update to the current time. Then calculate the distance the equipment should move along the predetermined path during that time period. Next, calculate the path points. and Total distance between Finally, the desired position at the current time is calculated using a linear interpolation formula. The formula is: in, This represents the three-dimensional coordinates of the underwater equipment at the time of its most recent position update. Represents the timestamp (in seconds) of the most recent location update. Represents the current time (in seconds) for calculating the desired position. Represents the speed at which underwater equipment moves along a predetermined path (unit: meters per second). Represents the time difference (unit: seconds). Represents the planned distance to travel (unit: meters). In the pre-defined communication path, The three-dimensional coordinates (in meters) of the next ordered path point. Representing path points and Total distance between them (unit: meters) The three-dimensional coordinates (in meters) represent the desired position at the current moment.

[0044] The Euclidean distance between the real-time position and the desired position is calculated using a standard geometric method. The sum of the squares of the coordinate differences between the two points in three-dimensional space is then taken as the square root, yielding a scalar distance value. When the calculated Euclidean distance exceeds the system's preset allowable deviation value, the path planning module generates a path adjustment command. This command includes a new motion direction angle and a recommended speed value. The direction angle is used to correct the heading, and the recommended speed value is used to adjust the rate of approach to the desired path.

[0045] Assume the real-time position coordinates of the underwater equipment are (Where 1650 meters is the longitude coordinate, 2980 meters is the latitude coordinate, and 365 meters is the water depth coordinate; the desired location coordinates of the planned path are...) The specific calculation process is as follows: First, calculate the difference in each dimension of the three-dimensional coordinates and square it. The square of the difference in the longitude direction is... The square of the difference in latitude is The square of the difference in water depth is Next, calculate the sum of the squared differences in the three dimensions, i.e. Finally, the square root of the sum of squares is taken to obtain the Euclidean distance. rice.

[0046] Real-time analysis of real-time communication signals involves a complex signal processing chain. The first step is noise reduction of the received real-time communication signal. Digital filters are used to remove high-frequency noise and interference in specific frequency bands. The design of these digital filters is based on the characteristics of the underwater acoustic channel and may employ finite-length unit impulse response (FIR) or infinite-length unit impulse response (ITR) filter structures. Extracting the time-domain features of the real-time communication signal involves calculating the signal's mean and variance. The mean amplitude reflects the average energy level of the signal, while the variance characterizes the fluctuations in signal amplitude. These features are calculated within a sliding time window to capture dynamic changes in signal characteristics. Extracting the frequency-domain features involves transforming the time-domain signal to the frequency domain and analyzing its dominant frequency components and bandwidth. The dominant frequency components refer to the main frequency points where signal energy is concentrated, while the bandwidth describes the effective width of the signal spectrum. The extracted time-domain and frequency-domain features are then matched against a pre-established feature library of normal communication modes. This feature library stores typical feature vectors of communication signals under various normal operating conditions. When the matching degree between the characteristics of the real-time signal and the normal patterns in the feature library is lower than the preset matching degree threshold, the system marks the signal as an abnormal communication signal and records the exact time when the abnormal signal was detected and the position coordinates of the underwater equipment at that time.

[0047] The accuracy of path deviation determination is affected by multiple factors. The positioning error of the integrated navigation system is directly transmitted to the accuracy of the real-time position coordinates, and the accuracy of the mathematical model of the predetermined communication path determines the reliability of the expected position calculation. Setting the allowable deviation value is a critical parameter; setting it too small will cause the system to be overly sensitive to slight path fluctuations, resulting in unnecessary frequent adjustments; setting it too large may cause underwater equipment to deviate from the effective communication range without timely correction. The new heading angle in the path adjustment command needs to be calculated comprehensively based on the real-time position, the expected position, and information on possible obstacles. The recommended speed value needs to consider the magnitude of the adjustment, the maneuverability of the underwater equipment, and the timeliness requirements of the current communication mission. The performance of the digital filter determines the effectiveness of the noise reduction processing, and its parameters need to match the modulation method and channel characteristics of the communication system. The extraction algorithms for time-domain and frequency-domain features need to balance computational complexity and feature representation capability to ensure that real-time requirements are met. The establishment of a normal communication mode feature library requires training and learning from a large amount of historical normal communication data; the dimension and structure of its feature vectors need to be carefully designed to effectively distinguish between normal and abnormal states. The setting of the matching degree threshold affects the sensitivity of anomaly detection, and a balance between false alarm rate and false negative rate needs to be achieved through experiments.

[0048] The comparison between real-time location coordinates and desired location is an ongoing process, with the system performing comparisons and decisions at fixed control cycles. While the calculation of Euclidean distance is intuitive, nonlinear path cost functions may need to be considered in some application scenarios. The logic for generating path adjustment commands can incorporate the concept of a proportional-integral-derivative controller, considering not only the current deviation distance but also historical trends and rates of change in deviation. Noise reduction processing for real-time communication signals may employ adaptive filtering techniques, with filter coefficients dynamically adjusted according to changes in background noise. The mean amplitude in time-domain features is easily affected by overall channel attenuation, while the amplitude variance better reflects the stability of the signal itself. Frequency-domain feature analysis typically uses the Fast Fourier Transform algorithm for efficient computation, and the identification of the dominant frequency component helps detect unexpected frequency shifts or interference. A normal communication mode feature library may need to distinguish different communication modes (such as commands, voice, and data streams) and establish independent feature templates for each mode. Anomaly marking mechanisms typically trigger multi-level responses, ranging from simple logging to high-level alarms and even automatic switching of communication links.

[0049] The results of path deviation determination and communication signal analysis need to be correlated to distinguish whether the deviation is a simple navigation error or a communication anomaly caused by external interference. Table 1 illustrates a possible correlation between the degree of path deviation and the type of communication signal anomaly, which can help determine the cause of the anomaly and guide the generation of appropriate path adjustment instructions.

[0050] Table 1: Correlation Mapping Table Between Path Deviation Degree and Communication Signal Anomaly Type Path deviation levels are categorized based on a comparison of the calculated Euclidean distance with a preset threshold. Minor deviations may be primarily caused by multipath effects or slight navigation errors, requiring mild, small-amplitude heading and speed adjustments. Moderate deviations indicate significantly deteriorated channel quality, possibly related to entering a strong interference zone or a substantial departure from the main communication beam; more decisive path adjustment commands are needed, potentially involving moderate course changes and speed adjustments. Severe deviations signify that the underwater equipment has strayed far from the intended path, and the communication link may be on the verge of being interrupted. Path adjustment commands generated at this level have the highest priority, typically including significant turning maneuvers and possible speed increases to facilitate the equipment's rapid return to the effective communication area. This correlation mapping combines geometric position information with communication signal quality information, providing a more comprehensive basis for path adjustment decisions and making the system response more intelligent and targeted.

[0051] Example 5: After completing real-time communication signal analysis, abnormal signal data is stored in a historical database, forming a core component of system knowledge accumulation. The historical database employs a distributed architecture, deployed in a hybrid storage mode combining the surface control center and underwater relay nodes. The abnormal signal data packet includes a complete time-domain waveform segment of the abnormal signal, extracted time-domain and frequency-domain feature vectors, a precise timestamp of the anomaly trigger moment, real-time location coordinates of the underwater equipment, a signal anomaly type classification code, and an initial interference area impact index Z-value. The historical database's storage logic uses multi-level indexing based on task number, time interval, and geographical region to ensure efficient data retrieval and related queries. Based on the abnormal records in the historical database, the generation rules for customized communication paths are dynamically adjusted, reflecting the self-learning and adaptive capabilities of the path planning engine. The path planning engine periodically performs statistical analysis on the abnormal records in the historical database, identifying the distribution patterns and clustering patterns of abnormal events in the time and spatial dimensions.

[0052] Taking a specific seabed topographic mapping mission as an example, the autonomous underwater vehicle (AUV-07) performed a detailed 3D scan of an unknown seamount. The mission required AUV-07 to continuously navigate along a pre-set zigzag survey line and transmit sonar signals. During the mission, the real-time communication signal analysis module detected multiple communication anomalies in communication segment CS-12, located on the southern slope of the seamount. The anomalies were characterized by periodic attenuation of the time-domain amplitude of the sonar echo signal, and frequency-domain analysis showed a shift in the center frequency. These anomaly signal data were immediately packaged and transmitted to the historical database on the surface mother ship via the underwater acoustic communication link for storage. The data packets recorded the precise latitude and longitude, water depth, and corresponding acoustic environment parameters of the anomaly occurrence. After the mission, seventeen new anomaly records related to communication segment CS-12 were added to the historical database. During the path planning phase before the next mission of AUV-07, the path planning engine calls the query interface of the historical database to retrieve all anomaly records near the mission area within the past four weeks. The statistical analysis module revealed a clear spatial clustering of anomalies in communication segment CS-12. Anomaly locations were concentrated within a single depth range (150-250 meters) on the southern slope of the seamount. While there was no fixed temporal pattern, these anomalies occurred most frequently during the afternoon when seawater temperature stratification was significant. Based on these findings, the path planning engine dynamically adjusted the rules for generating customized communication paths. The new rules explicitly state that when planning a path through communication segment CS-12, the 150-250 meter depth range on the southern slope should be actively avoided, and the travel cost weight for this area is increased by an order of magnitude in the path preference settings. For AUV-07, which is about to undertake a new round of seabed resource exploration, the customized communication path generated by the path planning engine no longer requires it to navigate close to the southern slope of the seamount to obtain the highest resolution data. Instead, an alternative path is generated, slightly away from the seamount and located in a 300-meter depth area. Although this path slightly increases the travel distance, it is predicted based on historical data to significantly reduce the risk of communication interruption.

[0053] The dynamic adjustment of communication path generation rules is not only reflected in spatial avoidance, but also in the ability of historical database anomaly records to reveal the activity patterns of specific interference sources. For example, the historical database records multiple instances of broadband burst noise interference occurring at night on the specific communication segment CS-08. The spectral characteristics preserved in the anomalous signal data highly match the acoustic signature characteristics of previously recorded civilian vessels. After analyzing these records, the path planning engine adjusted the generation rules, adding a time constraint: when planning communication tasks passing through communication segment CS-08 at night, priority is given to communication segments far from known shipping corridors. If avoidance is not possible, the task scheduling system is advised to adjust the passage time of communication segment CS-08 to a less disruptive daytime period. This adaptive adjustment based on time patterns makes communication resource allocation more intelligent. The storage structure design of the historical database supports efficient data mining, with each anomaly record associated with a specific environmental context. The dynamic adjustment capability of the path planning engine can therefore become more refined; for example, analysis may reveal that the probability of a certain type of communication anomaly occurring within a specific ocean current speed range is significantly increased. The generation rules were accordingly supplemented: when marine environmental forecast data shows that the ocean current velocity in the mission area exceeds a threshold, communication segments with more stable underwater acoustic channel conditions should be prioritized when planning the path for underwater equipment, even if the geographical distance between these communication segments may be slightly longer. This environmental correlation adjustment further enhances the ability to cope with the uncertainties of complex underwater environments.

[0054] The long-term accumulation of anomalous signal data enables historical databases to identify slowly changing trend risks. By comparing anomalous records from the same sea area in different years, the path planning engine may discover that the incidence of anomalous events in a traditionally reliable communication segment, CS-25, shows a slow upward trend year by year. This trend triggers an early warning mechanism, adding a "reliability decline" label to the communication segment in the generation rules and introducing a decay factor during path planning to gradually reduce its selection priority. Simultaneously, this trend information prompts system maintenance personnel to conduct focused inspections of the communication segment, potentially identifying potential problems such as equipment aging or environmental changes in advance. Dynamically adjusting the generation rules for customized communication paths is a closed-loop feedback process; new data generated after the new rules are applied to subsequent tasks is fed back into the historical database. The path planning engine continuously evaluates the effectiveness of the adjusted rules; for example, it compares whether the incidence of communication anomalies in AUV-07 in the area has decreased significantly as expected after adopting a new path that avoids the southern slope of communication segment CS-12. If the evaluation shows positive results, the rule will be reinforced and potentially extended to areas with similar geographical features. If the results are unsatisfactory, the path planning engine will analyze the reasons, whether the rule is too conservative leading to efficiency losses or whether the judgment of the root cause of the anomaly is incorrect, and then iteratively optimize the generated rule. This continuous self-learning and optimization mechanism enables the marine equipment underwater communication system based on distributed underwater networking to continuously adapt to the changing marine environment and gradually improve the overall reliability and efficiency of communication tasks.

[0055] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for underwater communication of marine equipment based on distributed underwater networking, characterized in that, Includes the following steps: The underwater communication network of marine equipment is intelligently segmented to obtain multiple communication segments; The user terminal issues an initial communication task command, controlling the underwater equipment to start the communication task upon receiving the initial communication task command; during the execution of the initial communication task, the initial communication parameters of each communication segment are collected, and the stored historical communication fault records are obtained; based on the initial communication parameters and the historical communication fault records, the fault level and importance level of each communication segment are determined; based on the importance level and the fault level, a customized communication path is formulated for the underwater equipment to communicate. During the execution of communication tasks according to the customized communication path, the underwater equipment collects real-time position information and acquires interference data corresponding to interference sources in the communication segment; confirms whether the underwater equipment has entered the interference area, and records the real-time position coordinates of the underwater equipment within the interference area when an offset detection signal is generated; determines whether the underwater equipment has deviated from the predetermined communication path within the interference area based on the real-time position coordinates, and generates a path adjustment command if it has deviated; collects real-time communication signals of the communication segment and analyzes the real-time communication signals in real time; when a communication anomaly is detected, acquires the abnormal position coordinates and the corresponding real-time communication signals for processing by the user terminal.

2. The underwater communication method for marine equipment based on distributed underwater networking according to claim 1, characterized in that, The initial communication parameters include the available bandwidth of the communication segment and the data transmission error rate; the historical communication fault record is the number of historical faults that occurred in the communication segment and the average interruption duration for each fault.

3. The underwater communication method for marine equipment based on distributed underwater networking according to claim 2, characterized in that, The process of determining the fault level and importance level of each communication segment specifically includes: Obtain the historical number of faults for each communication segment, and query the average interruption duration for each fault in each communication segment. Multiply the historical number of faults by the average interruption duration to obtain the fault index for each communication segment. The fault indicators are compared with preset fault thresholds, and the fault level of the communication segment is classified into high fault level, medium fault level or low fault level based on the comparison results. At the same time, the available bandwidth and data transmission error rate of each communication segment are obtained, and the importance index of each communication segment is obtained by dividing the available bandwidth by the data transmission error rate. The importance index is compared with the preset importance threshold, and the importance level of the communication segment is divided into high importance level, medium importance level or low importance level according to the comparison result.

4. The underwater communication method for marine equipment based on distributed underwater networking according to claim 3, characterized in that, The process of developing a customized communication path for underwater equipment communication specifically includes: The underwater equipment starts from its initial position and prioritizes communication segments with high importance. When multiple communication segments have the same importance level, underwater equipment selects the communication segment with the higher failure level for communication. When the importance level and the fault level are the same, the underwater equipment selects the communication segment closest to its current location for communication. When underwater equipment encounters a network node during communication, it checks the status of the communication segment connected to the node. If a node connects to multiple communication segments, the underwater equipment processes the communication segments in descending order of importance. Once all communication segments have been completed, the underwater equipment returns to its starting position. Underwater equipment uses different transmission power for data transmission in communication segments of different importance levels.

5. The underwater communication method for marine equipment based on distributed underwater networking according to claim 1, characterized in that, The interference data includes the geographic coordinates of the interference source, the maximum value of the interference signal strength, and the duration of the interference.

6. The underwater communication method for marine equipment based on distributed underwater networking according to claim 5, characterized in that, The process of confirming whether underwater equipment has entered the interference zone specifically includes: Real-time monitoring of signal strength around underwater equipment; When the signal strength exceeds a preset strength threshold, it is determined that the underwater equipment has entered the interference zone; Record the real-time position coordinates and current timestamp of the underwater equipment to generate an offset detection signal.

7. The underwater communication method for marine equipment based on distributed underwater networking according to claim 6, characterized in that, The process of determining whether the underwater equipment has deviated from the predetermined communication path within the interference area based on the real-time position coordinates specifically includes: Compare the real-time position of the underwater equipment with the expected position along the predetermined path; Calculate the Euclidean distance between the real-time location and the desired location; When the Euclidean distance exceeds the allowable deviation value, a path adjustment command is generated; the path adjustment command includes new heading angle and speed values.

8. The underwater communication method for marine equipment based on distributed underwater networking according to claim 1, characterized in that, The process of real-time analysis of the real-time communication signal specifically includes: The received real-time communication signals are noise-reduced by using digital filters to remove high-frequency noise. Extract the time-domain features of real-time communication signals, including the mean and variance of amplitude; Extract the frequency domain features of real-time communication signals, including the main frequency components and bandwidth; The time-domain and frequency-domain features are matched with the feature library of normal communication modes; when the feature matching degree is lower than the preset threshold, the signal is marked as abnormal, and the occurrence time and location coordinates of the abnormal signal are recorded.

9. A method for underwater communication of marine equipment based on distributed underwater networking as described in claim 1, characterized in that, The method further includes: After completing the real-time communication signal analysis, the abnormal signal data is stored in the historical database; Based on anomaly records in the historical database, dynamically adjust the generation rules for customized communication paths.

10. A marine equipment underwater communication system based on distributed underwater networking, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the underwater communication method for marine equipment based on distributed underwater networking as described in any one of claims 1 to 9.

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