Layered topology control and routing maintenance method suitable for high dynamic ship network

Abstract

The application discloses a layered topology control and route maintenance method suitable for a high dynamic ship network, and comprises the following steps: for a super short wave heterogeneous transmission channel set composed of at least three types of transmission channels including a meteor trail communication, an ionosphere scattering communication and a ground wave diffraction communication, a preset channel evaluation model is used to calculate a channel state parameter of transmission quality of each transmission channel in real time; based on the channel state parameter, and a priority and a quality of service requirement of a current to-be-transmitted service, the quality of service requirement including a requirement for at least one of transmission delay, bandwidth and reliability, a preset channel selection strategy is used to dynamically select a current optimal transmission channel from the super short wave heterogeneous transmission channel set; and according to the current optimal transmission channel, corresponding physical layer configuration parameters and link control signals are generated, so as to obtain network layer control instructions used for coordinating route discovery, maintenance and data forwarding behaviors between a master node and a user node in the high dynamic ship network.

Description

Technical Field

[0001] This invention relates to the field of wireless communication network technology, and in particular to a hierarchical topology control and routing maintenance method suitable for highly dynamic ship networks. Background Technology

[0002] Existing ship-to-ship (STOV) information transmission and networking technologies primarily rely on three methods: shore-based mobile communication, satellite communication, and dedicated maritime wireless communication. Shore-based mobile communication technologies, especially 4G / 5G networks, can provide high-bandwidth, low-latency communication services to near-shore vessels using coastal base stations. However, their coverage range typically does not exceed 7 nautical miles, heavily relying on infrastructure and failing to achieve beyond-line-of-sight coverage in the open ocean, making it difficult to build a large-scale, seamless STOVV network. Satellite communication is the core means of achieving global ocean communication. However, geostationary orbit satellites suffer from high transmission latency, are significantly affected by weather factors such as rain attenuation, and cannot guarantee all-weather communication. Furthermore, high-cost terminals limit their widespread adoption among a large number of small and medium-sized vessels. While emerging low-Earth orbit (LEO) satellite constellations can provide low-latency, high-bandwidth services, their terminals and service costs remain expensive. In terms of dedicated wireless communication technology at sea, the widely used Automatic Identification System (AIS) mainly serves ship safety monitoring, periodically transmitting a small amount of critical data via broadcast. This system suffers from problems such as extremely low bandwidth, time slot conflicts in high-density areas, and insufficient reliability, and cannot support the transmission of routine services such as voice and images. Its evolution technology, the VHF data exchange system, aims to improve data communication capabilities, but it is still in the early stages of development.

[0003] Therefore, existing technologies have significant limitations in achieving all-weather, beyond-line-of-sight ship-to-ship (STS) information transmission: shore-based network coverage is insufficient, satellite communication is costly and weather-dependent, while dedicated systems have limited bandwidth and require improved reliability. In terms of networking, existing systems mostly rely on centrally located network architectures such as star or chain structures, exhibiting high dependence on central nodes like satellites and ground stations, making communication links prone to interruption and resulting in poor network resilience. Furthermore, existing STS systems generally have weak anti-interference measures, often employing common commercial encryption technologies, which face challenges in resisting interference, interception, and intrusion in complex marine electromagnetic environments. These shortcomings collectively restrict the development and application of large-scale, highly reliable, all-weather STS technology. Summary of the Invention

[0004] The purpose of this invention is to provide a hierarchical topology control and routing maintenance method suitable for highly dynamic ship networks. By constructing a transmission mechanism based on heterogeneous channel intelligent evaluation and dynamic selection and a hierarchical centerless networking method, the method improves the all-weather reliable transmission and network resilience of ship networks under beyond-line-of-sight conditions, and solves the problems of single transmission means, reliance on central nodes and insufficient anti-interference capabilities in the prior art.

[0005] To address the aforementioned technical problems, a first aspect of this invention provides a hierarchical topology control and routing maintenance method suitable for highly dynamic ship networks, comprising the following steps: For a set of heterogeneous UHF transmission channels consisting of at least three types of transmission channels, including meteor trail communication, ionospheric scattering communication and ground wave diffraction communication, the channel state parameters of the transmission quality of each transmission channel are calculated in real time using a preset channel evaluation model. Based on the channel state parameters, as well as the priority and quality of service requirements of the current service to be transmitted, the quality of service requirements include requirements for at least one of transmission delay, bandwidth and reliability. The optimal transmission channel is dynamically selected from the set of ultra-shortwave heterogeneous transmission channels through a preset channel selection strategy. Based on the current optimal transmission channel, corresponding physical layer configuration parameters and link control signals are generated to obtain network layer control instructions for coordinating route discovery, maintenance, and data forwarding behaviors between the master control node and user nodes in the highly dynamic ship network.

[0006] Furthermore, the step of using a preset channel evaluation model to calculate the channel state parameters of the transmission quality of each transmission channel in real time includes: Obtain the channel type of the transmission channel; For meteor trail channels, obtain their channel availability probability, average burst duration, and raw measurement parameters; For the ionospheric scattering channel, we obtain its signal level fading standard deviation, Doppler frequency shift, signal fading depth, and raw measurement parameters; For the ground wave diffraction channel, obtain its path propagation loss and raw measurement parameters; Based on the corresponding parameters obtained for different channel types, channel state parameters characterizing the overall transmission quality of the transmission channel are calculated using the channel quality evaluation function corresponding to the channel type.

[0007] Further, the calculation of channel state parameters characterizing the overall transmission quality of the transmission channel using a channel quality evaluation function corresponding to the channel type includes: The parameters obtained for the channel type are normalized and converted into dimensionless normalized parameter values. Based on the inherent transmission characteristics of the channel type and the service quality requirements of the current service to be transmitted, the preset weight mapping relationship is queried to obtain the dynamic weight coefficient corresponding to each of the normalized parameter values. Based on the dynamic weighting coefficient, the normalized parameter values ​​are weighted and synthesized to generate a scalar channel state parameter, wherein the value of the channel state parameter directly corresponds to the overall quality level of the transmission channel supporting the current service to be transmitted.

[0008] Furthermore, the step of dynamically selecting the optimal transmission channel from the set of heterogeneous UHF transmission channels based on the channel state parameters and the priority and quality of service requirements of the current service to be transmitted, through a preset channel selection strategy, includes: Based on the quality of service requirements of the current services to be transmitted, determine the comprehensive evaluation criteria for channel sequencing; Based on the comprehensive evaluation criteria and combined with the priority of the current service to be transmitted, the utility of the channel state parameters of each optional transmission channel is calculated to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted. The channel utility value is a quantitative evaluation value that characterizes the degree of contribution of the optional transmission channel to meeting the service quality requirements. All the available transmission channels are sorted according to the channel utility value to generate a channel selection sequence; The current optimal transmission channel is determined based on the channel selection sequence and the real-time availability status of each transmission channel in the ultra-shortwave heterogeneous transmission channel set.

[0009] Further, based on the comprehensive evaluation criteria and in conjunction with the priority of the current service to be transmitted, the utility calculation of the channel state parameters of each optional transmission channel is performed to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted, including: Based on the comprehensive evaluation criteria, the service quality requirements of the current service to be transmitted are decoupled into the demand intensity for different channel characteristic dimensions, forming a demand feature vector; The priority of the current service to be transmitted is mapped to a global correction factor on the demand feature vector to obtain the priority correction factor; Based on the demand feature vector, the multiple channel characteristic values ​​represented by the channel state parameters of the optional transmission channel are normalized to obtain normalized channel characteristic values. The channel utility value is calculated by weighting the demand feature vector using the priority correction factor and then matching it with the normalized channel characteristic value.

[0010] Further, the step of weighting the demand feature vector using the priority correction factor and then performing a matching operation with the normalized channel characteristic value to calculate the channel utility value includes: Based on the normalized channel characteristic value, calculate the degree of satisfaction of the optional transmission channel with each independent dimension of the quality of service requirement; Using the demand intensity of the corresponding dimension in the demand feature vector as the weight, the satisfaction of all the dimensions is weighted and aggregated to obtain the initial business quality evaluation value. The initial service quality evaluation value is fused with the channel robustness coefficient, which reflects the temporal stability of the selectable transmission channel within a preset time period, to obtain the channel utility value.

[0011] Furthermore, the network layer control instructions obtained for coordinating route discovery, maintenance, and data forwarding behaviors between the master control node and user nodes in the highly dynamic ship network include: Perform network initialization operations and check the status of the preset control channel; When the control channel is detected as idle, a neighbor node probe signal is transmitted, and a response signal from the neighbor node is received; Based on the response signal, establish or update the routing table between the master node and the user node; Based on the ship network service data to be sent and the changes in the routing table, a message to be sent through the control channel is generated and the sending operation is performed. The message includes a data frame and / or a routing update message.

[0012] Furthermore, the physical layer configuration parameters include multi-level orthogonal spread spectrum modulation parameters; The generation of the corresponding physical layer configuration parameters includes: Based on the available bandwidth of the current optimal transmission channel and the quality of service requirements of the current service to be transmitted, the number M of the multi-ary orthogonal spread spectrum and the corresponding orthogonal spread spectrum code are determined.

[0013] Furthermore, the generation of the corresponding physical layer configuration parameters and link control signals also includes the configuration process of the multi-level orthogonal spread spectrum modulator, including: The field-programmable gate array (FPGA) performs mapping and encoding of multi-level information and corresponding pseudo-random codes according to the transmit enable signal and the multi-level orthogonal spread spectrum modulation parameters to generate a digital baseband signal. The digital baseband signal is converted from digital to analog to obtain an analog differential baseband signal; The simulated differential baseband signal is directly modulated onto the radio frequency carrier; The field-programmable gate array (FPGA) controls the digitally controlled attenuator to control the power of the modulated radio frequency signal.

[0014] Furthermore, the highly dynamic ship network adopts a hierarchical architecture, including master control nodes with network addressing capabilities and user nodes without network addressing capabilities; the master control nodes constitute a decentralized, variable topology backbone network, and the user nodes access the backbone network through roaming or communicate directly with adjacent nodes.

[0015] Accordingly, a second aspect of the present invention provides an electronic device, including: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the above-described hierarchical topology control and routing maintenance method applicable to highly dynamic ship networks.

[0016] Accordingly, a third aspect of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-described hierarchical topology control and routing maintenance method applicable to highly dynamic ship networks.

[0017] The above-described technical solutions of the embodiments of the present invention have the following beneficial technical effects: 1. By unifying the modeling and intelligent optimization of three types of ultra-shortwave channels with distinct physical characteristics—meteor trails, ionospheric scattering, and ground wave diffraction—the system can dynamically select the optimal transmission path based on real-time channel conditions and service requirements. This enables all-weather, beyond-line-of-sight reliable coverage of vast sea areas without relying on expensive satellites or dense shore-based facilities, fundamentally solving the inherent limitations of single transmission methods in terms of coverage, all-weather capability, or cost. 2. By adopting a decentralized hierarchical variable topology network architecture that strictly limits the number of backbone nodes and allows user nodes to access, and in conjunction with neighbor node discovery and route self-maintenance mechanisms, the network can effectively suppress broadcast storms when nodes change frequently and dynamically, and can achieve rapid self-healing and reconstruction when local nodes fail. This significantly improves the network's node capacity, topology adaptability and overall resilience in a highly dynamic ship environment, overcoming the single point of failure risk and scalability bottleneck of traditional centralized networks. 3. By deeply adapting multi-level orthogonal spread spectrum technology to VHF narrowband channels and dynamically configuring modulation parameters according to service requirements and channel conditions, the anti-co-channel interference capability and low interception probability of communication signals are significantly improved without increasing the radio frequency bandwidth. This enhances the transmission security and concealment of ship-to-ship networks in complex electromagnetic environments and effectively compensates for the shortcomings of existing systems, such as weak anti-interference measures and easy detection. Attached Figure Description

[0018] Figure 1This is a flowchart of a hierarchical topology control and routing maintenance method for highly dynamic ship networks provided in an embodiment of the present invention; Figure 2 This is a diagram of the ship network information transmission and networking technology architecture provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0020] Please refer to Figure 1 and Figure 2 The first aspect of this invention provides a hierarchical topology control and routing maintenance method suitable for highly dynamic ship networks, comprising the following steps: Step S100: For a set of heterogeneous UHF transmission channels consisting of at least three types of transmission channels, including meteor trail communication, ionospheric scattering communication and ground wave diffraction communication, the channel state parameters of the transmission quality of each transmission channel are calculated in real time using a preset channel evaluation model.

[0021] When ships are navigating in open seas or complex weather regions, shore-based mobile network signals may be unavailable, and satellite links may be unable to provide stable service due to rain attenuation or cost limitations. In such situations, shipboard communication equipment equipped with this method comes into play. First, it detects and evaluates a set of currently available heterogeneous UHF transmission channels, which includes at least three types of channels with distinct physical mechanisms and transmission characteristics: meteor trail communication, ionospheric scattering communication, and ground wave diffraction communication. Using a built-in preset channel evaluation model, each channel is monitored and analyzed in real time. The model comprehensively considers key parameters such as the burst availability probability and average duration of meteor trail channels, the signal fading depth and Doppler shift of ionospheric scattering channels, and the path propagation loss of ground wave diffraction channels, and outputs a normalized channel state parameter characterizing its overall transmission quality.

[0022] Step S200: Based on the channel state parameters and the priority and quality of service requirements of the current service to be transmitted, the quality of service requirements include requirements for at least one of transmission delay, bandwidth and reliability. The optimal transmission channel is dynamically selected from the set of heterogeneous UHF transmission channels through a preset channel selection strategy.

[0023] After obtaining the state parameters of each channel, the dynamic channel selection phase begins. This phase must consider both the objective conditions of communication and the subjective needs of the upper-layer application. Objective conditions refer to the aforementioned channel state parameters, while subjective needs are reflected in the priority of the current service to be transmitted and its specific quality of service requirements. For example, security alarm services require extremely low latency and extremely high reliability, while file update services may prioritize bandwidth. The core algorithm of the preset channel selection strategy fuses these two dimensions of input. Its internal logic may involve constructing a utility function that matches the service requirements. This function assigns dynamic weights to different channel state parameters, ultimately calculating the "utility value" of each available channel for the current service. It doesn't simply select the channel with the best instantaneous quality, but rather the channel that best meets the core needs of the current service, thus achieving the optimal match between resources and requirements.

[0024] Step S300: Based on the current optimal transmission channel, generate the corresponding physical layer configuration parameters and link control signals to obtain network layer control instructions for coordinating route discovery, maintenance, and data forwarding behaviors between the master control node and user nodes in a highly dynamic ship network.

[0025] After selecting the optimal transmission channel, corresponding reconfiguration needs to be performed at the physical and link layers to establish or switch to that channel for communication. This includes generating physical layer configuration parameters that match the channel characteristics, such as operating frequency, modulation scheme, transmit power, and anti-interference parameters (e.g., the number of bases and spreading code when using multi-level orthogonal spread spectrum). Simultaneously, corresponding link control signals are generated. These parameters and signals together form the basis of network layer control commands. The core function of these control commands is to coordinate the behavior of master nodes and user nodes within the network, guiding them to perform route discovery, maintain neighbor tables, update routing information, and perform data forwarding based on the newly selected optimal channel, thereby maintaining one or more stable and efficient data transmission paths in the dynamically changing ship network topology. The entire process, from channel awareness and intelligent decision-making to protocol stack control, forms a closed loop, enabling ship-to-ship networks to adaptively maintain beyond-line-of-sight communication capabilities in marine environments lacking fixed infrastructure.

[0026] This invention, through the construction of a complete method encompassing unified heterogeneous channel evaluation, service-aware dynamic channel selection, and cross-layer collaborative control, achieves reliable information transmission and networking of ship-to-ship networks in beyond-line-of-sight and highly dynamic environments. It comprehensively utilizes the complementary characteristics of various UHF channels to overcome the shortcomings of single transmission methods in terms of coverage, cost, or all-weather capability, achieving broader reliable coverage. Simultaneously, intelligent channel selection based on service requirements optimizes network resource allocation and enhances the transmission guarantee capability of critical services. Finally, through the coordinated control of the physical and network layers, the adaptability and resilience of the entire ship's self-organizing network are enhanced, providing effective communication network support for large-scale, all-weather marine information applications.

[0027] Specifically, step S100, which involves using a preset channel evaluation model to calculate the channel state parameters of the transmission quality of each transmission channel in real time, includes: Step S110: Obtain the channel type of the transmission channel.

[0028] In marine communication scenarios, shipborne equipment must first identify the specific type of the currently available physical channel. This judgment is based on the understanding of the physical mechanisms of different channels and the detection of signal characteristics. For example, by analyzing the time-varying characteristics, Doppler broadening, and propagation delay of the received signal, it is possible to distinguish between meteor trail channels with brief burst patterns, ionospheric scattering channels with significant ionospheric refraction characteristics and relatively stable signals, and ground wave channels that mainly rely on surface diffraction and are significantly affected by terrain and curvature. This type identification is the foundation for subsequent acquisition and evaluation of differentiated parameters.

[0029] Step S120: For the meteor trail channel, obtain its channel availability probability, average burst duration, and raw measurement parameters.

[0030] For identified meteor trail channels, the focus will be on evaluating their availability as burst channels. This includes statistically calculating the probability of a valid meteor trail event occurring within a specific time window, i.e., the channel availability probability. Simultaneously, the average duration for which each burst can maintain effective communication will be measured. Furthermore, direct raw measurement parameters for the channel, such as the signal-to-noise ratio and bit error rate of the received signal, need to be obtained. These parameters collectively describe the core characteristics of the channel: "when it is available" and "how long it is available," providing a basis for utilizing it for intermittent data transmission.

[0031] Step S130: For the ionospheric scattering channel, obtain its signal level fading standard deviation, Doppler frequency shift, signal fading depth, and original measurement parameters.

[0032] For ionospheric scattering channels, the evaluation focuses on signal stability and time-varying characteristics. Fading depth and fluctuations are quantified by calculating the statistical standard deviation of the received signal level over a period of time. Simultaneously, the Doppler shift caused by ionospheric motion and the ship's own movement is precisely measured. Measurements of signal fading depth further reveal the severity of signal attenuation. Combined with raw measurement parameters such as signal-to-noise ratio and delay, these indicators comprehensively reflect the link quality and phase stability of the channel in beyond-line-of-sight transmission, making it suitable for services with high continuity requirements.

[0033] Step S140: For the ground wave diffraction channel, obtain its path propagation loss and original measurement parameters.

[0034] For ground wave diffraction channels, transmission quality is primarily limited by path propagation loss increasing with distance. This path loss is calculated using known transmit power and measured receive power, or by employing propagation models based on frequency, distance, and terrain factors. Simultaneously, real-time raw measurement parameters of the channel, such as signal-to-noise ratio, are obtained. Path propagation loss directly determines the effective communication distance and signal coverage strength of this mode, and is crucial for evaluating its applicability in line-of-sight and beyond-line-of-sight edge regions.

[0035] Step S150: Based on the corresponding parameters obtained for different channel types, channel state parameters characterizing the overall transmission quality of the transmission channel are calculated using the channel quality evaluation function corresponding to the channel type.

[0036] After acquiring the targeted parameters, the evaluation function pre-bound to the channel type is invoked for calculation. This function first normalizes the various parameters (including statistical parameters and raw measurement parameters) acquired in steps S120 to S140, eliminating dimensional differences. Then, based on the inherent properties of each channel type (such as the burstiness of meteor trails and the time-varying nature of ionospheric channels) and current service requirements, it queries a pre-set mapping table and assigns corresponding dynamic weights to each normalized parameter. Finally, a scalar-form channel state parameter is output through a weighted fusion algorithm. This parameter value intuitively represents the overall quality level of service transmission supported by the transmission channel in the current scenario, achieving unified quantification and comparable evaluation of the three heterogeneous channel types.

[0037] Further, in step S150, the channel state parameters characterizing the overall transmission quality of the transmission channel are calculated using a channel quality evaluation function corresponding to the channel type, including: Step S151 involves normalizing the parameters obtained for the channel type, converting them into dimensionless normalized parameter values.

[0038] After obtaining the raw parameters (such as probability, time, decibel value, etc.) for a specific channel type, they need to be normalized to eliminate dimensional differences. For example, parameters such as the availability probability (0-1) of the meteor trail channel, the average burst duration (milliseconds), and the fading depth (decibels) of the ionospheric scattering channel can be uniformly transformed to a dimensionless numerical range between zero and one through a preset linear or nonlinear mapping function.

[0039] Step S152: Based on the inherent transmission characteristics of the channel type and the service quality requirements of the current service to be transmitted, query the preset weight mapping relationship to obtain the dynamic weight coefficient corresponding to each normalized parameter value.

[0040] After normalization, appropriate weights need to be assigned to each parameter to reflect their varying importance. Based on the inherent transmission characteristics of the current channel (e.g., when evaluating a meteor trail channel, the weight of the "burst availability" parameter is greater than that of the "average burst duration"; when evaluating an ionospheric scattering channel, the weight of "Doppler shift" may be higher) and the quality of service requirements of the current service to be transmitted (e.g., if the service requires low latency, the weight of parameters related to propagation delay is increased), a pre-defined weight mapping table is consulted. This table defines the dynamic weight coefficients corresponding to each normalized parameter under different combinations of service types and channel types, thereby ensuring that the evaluation criteria match the specific transmission scenario and service objectives.

[0041] Step S153: Based on the dynamic weighting coefficient, perform a weighted comprehensive operation on the normalized parameter values ​​to generate a scalar channel state parameter, wherein the value of the channel state parameter directly corresponds to the overall quality level of the transmission channel supporting the current service to be transmitted.

[0042] After obtaining the normalized parameter values ​​and their corresponding dynamic weighting coefficients, a weighted summation operation is performed. Specifically, each normalized parameter value is multiplied by its weighting coefficient and then summed to generate a single scalar value, namely the channel state parameter. This value directly quantifies the overall transmission quality level that the transmission channel can provide under the current service requirements. The higher the value, the better the channel can meet the current service transmission requirements, providing an objective and quantitative decision-making basis for subsequent channel optimization.

[0043] Furthermore, in step S200, based on channel state parameters and the priority and quality of service requirements of the current service to be transmitted, the optimal transmission channel is dynamically selected from the set of heterogeneous UHF transmission channels using a preset channel selection strategy, including: Step S210: Determine the comprehensive evaluation criteria for channel sequencing based on the service quality requirements of the current service to be transmitted.

[0044] The process of determining comprehensive evaluation criteria involves translating upper-layer service requirements into specific quantitative standards for channel ranking. For example, when the service to be transmitted is an emergency security alarm, its quality of service requirements emphasize extremely low transmission latency and extremely high reliability. The determined comprehensive evaluation criteria will assign higher ranking weights to channel state parameters that are highly correlated with transmission latency and link stability. Conversely, for bandwidth-sensitive services such as ship electronic chart updates, the evaluation criteria will focus on the channel's potential effective bandwidth capacity. Based on the service quality requirements of the service, corresponding evaluation criteria are matched from a pre-set policy library or dynamically generated. These criteria clarify how to weigh different dimensions of channel state parameters in subsequent utility calculations.

[0045] Step S220: Based on the comprehensive evaluation criteria and combined with the priority of the current service to be transmitted, the utility of the channel state parameters of each optional transmission channel is calculated to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted. The channel utility value is a quantitative evaluation value that characterizes the degree of contribution of the optional transmission channel to meeting the service quality requirements.

[0046] After clarifying the comprehensive evaluation criteria, utility calculation is performed for each optional transmission channel. This calculation is based on the channel state parameters generated in step S150, which quantify the overall quality of the channel. The core of the utility calculation lies in mapping the channel through a preset utility function, based on the evaluation criteria determined in step S210 and combined with the priority of the current service (e.g., high-priority services can receive a higher utility bonus for channel characteristics that meet their core needs). This function takes the channel state parameters and service priority as input and outputs a channel utility value. This utility value is a quantitative evaluation value that characterizes the degree to which the optional transmission channel contributes to meeting specific service requirements and priority settings, thus allowing the comparison between different channels to transcend absolute physical quality and enter the dimension of adaptation to service objectives.

[0047] Step S230: Sort all available transmission channels according to the channel utility value to generate a channel selection sequence.

[0048] After calculating the utility of all available channels, the calculated channel utility values ​​are sorted in descending order to generate an ordered channel selection sequence. In this sequence, the channel ranked first represents the transmission path that, at the current moment and for the specific service, theoretically best meets its quality of service requirements. The significance of generating this sequence is to simplify the complex multi-objective decision-making results into a clear and actionable priority list, providing a direct basis for the final channel selection decision and also preparing for the selection of alternative solutions.

[0049] Step S240: Determine the current optimal transmission channel based on the channel selection sequence and the real-time availability status of each transmission channel in the VHF heterogeneous transmission channel set.

[0050] The channel selection sequence reflects the theoretically optimal order, but the final determination of the current optimal transmission channel also requires consideration of the network's real-time dynamics. The real-time availability status of the top-ranked channels in the sequence (usually the preferred ones) is checked. This real-time status may include transient interference at the physical layer, link-layer occupancy, or node reachability at the network layer. If the preferred channel is available in real-time, it is determined as the current optimal transmission channel, and a connection is immediately attempted to be established. If the preferred channel is temporarily unavailable for any reason, the next best channel in the sequence is automatically checked until a channel that meets the real-time availability criteria is found. This mechanism ensures that the channel selection strategy possesses both intelligent optimization capabilities based on service requirements and robustness in response to transient network changes.

[0051] Further, in step S220, based on the comprehensive evaluation criteria and combined with the priority of the current service to be transmitted, the channel state parameters of each optional transmission channel are calculated to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted, including: Step S221: Based on the comprehensive evaluation criteria, the service quality requirements of the current service to be transmitted are decoupled into the demand intensity for different channel characteristic dimensions, forming a demand feature vector.

[0052] The comprehensive evaluation criteria provide a logical connection between service requirements and technical indicators. Specifically, it resolves the quality of service requirements of the current service to be transmitted (e.g., an emphasis on low latency, high bandwidth, or high reliability) into a set of intensity requirements for specific channel characteristic dimensions (corresponding to propagation delay, effective bandwidth, bit error rate, or signal stability, respectively). For example, for ship collision avoidance safety information, its requirement feature vector might be characterized by assigning extremely high intensity values ​​to the "latency" dimension, high intensity values ​​to the "reliability" dimension, and relatively low intensity requirements to the "bandwidth" dimension. This vectorized expression lays the foundation for subsequent accurate calculation of the matching degree between the channel and service requirements.

[0053] Step S222: Map the priority of the current service to be transmitted to a global correction factor on the demand feature vector to obtain the priority correction factor.

[0054] Service priority is used to adjust the influence of demand intensity on the final decision. The "priority" parameter, a management-level parameter, is quantified as a global correction factor acting on the demand feature vector. High-priority services (such as distress alarms) have a correction factor greater than 1, which proportionally amplifies the intensity values ​​of each dimension in the demand feature vector. Therefore, in utility calculations, channels that better meet these enhanced demands receive significantly higher utility evaluation values. Conversely, low-priority services may have a correction factor equal to or less than 1, thus reducing the weight of their demand in channel contention.

[0055] Step S223: Based on the demand feature vector, normalize the multiple channel characteristic values ​​represented by the channel state parameters of the selectable transmission channel to obtain normalized channel characteristic values.

[0056] To achieve a quantitative match between demand and capability, the actual capability of the channel needs to be quantified on the same scale. This step normalizes multiple channel characteristic values ​​reflected by the channel state parameters of each selectable transmission channel (such as delay estimates, bandwidth potential, and stability metrics derived from channel type assessment). The purpose of this normalization is to eliminate differences in the dimensions and numerical ranges of different characteristic values, mapping them to a unified scale (e.g., between 0 and 1), thereby obtaining a set of normalized channel characteristic values. This set of values ​​characterizes the degree to which the channel achieves its optimal possible values ​​across each characteristic dimension.

[0057] Step S224: The demand feature vector is weighted using a priority correction factor and then matched with the normalized channel characteristic value to calculate the channel utility value.

[0058] After obtaining the quantified demand-side description (weighted demand feature vector) and the channel capability-side description (normalized channel characteristic value), the channel utility value is calculated through a matching operation. The core of the operation is to measure the degree of fit between the two in a multi-dimensional space. A typical implementation is to calculate the dot product or cosine similarity between the weighted demand feature vector and the normalized channel characteristic value. The demand vector, after being weighted by a priority correction factor, has each dimension value representing the "degree of importance" and "demand intensity" of the service for that dimension of channel characteristics, while the normalized channel characteristic value represents the channel's "supply capacity" in that dimension. The result of the matching operation (i.e., the channel utility value) is a comprehensive scalar that quantifies the degree to which the channel capability meets the current weighted service demand; the higher the value, the better the matching degree.

[0059] Further, in step S224, the demand feature vector is weighted using a priority correction factor, and then matched with the normalized channel characteristic value to calculate the channel utility value, including: Step S2241: Based on the normalized channel characteristic values, calculate the dimensional satisfaction of each independent dimension requirement in the quality of service requirements for the optional transmission channel.

[0060] Normalized channel characteristic values ​​(such as latency, bandwidth potential, stability, and other quantitative indicators) are mapped to the degree of direct satisfaction of each independent dimension of service quality requirements. The satisfaction level of the channel in each specific dimension, such as latency, bandwidth, and reliability, is calculated through a preset mapping function or threshold comparison. For example, a channel with a low normalized latency characteristic value (indicating low actual latency) will have a high satisfaction level in the "low latency" requirement dimension; conversely, if its normalized bandwidth characteristic value is also high, its satisfaction level in the "high bandwidth" dimension may be low.

[0061] Step S2242: Using the demand intensity of the corresponding dimension in the demand feature vector as the weight, the satisfaction of all dimensions is weighted and aggregated to obtain the initial business quality evaluation value.

[0062] After obtaining the satisfaction levels for each dimension, it is necessary to synthesize them based on the emphasis of the business requirements themselves. The values ​​of each dimension of the demand feature vector formed in step S221 (i.e., demand intensity) are used as weights to perform a weighted sum of the satisfaction levels of all dimensions calculated in step S2241. The result is an initial service quality evaluation value. For example, if the current service has an extremely high demand intensity for "low latency" (with a large weight), then a channel with an extremely high satisfaction level in the latency dimension may obtain a very high initial evaluation value even if its satisfaction level in the bandwidth dimension is average.

[0063] Step S2243: The initial service quality evaluation value is fused with the channel robustness coefficient, which reflects the temporal stability of the selectable transmission channel within a preset time period, to obtain the channel utility value.

[0064] The initial service quality assessment value is mainly based on the current or recent instantaneous or average characteristics of the channel. To improve the long-term robustness of the selection, it is necessary to further integrate the historical stability information of the channel. A channel robustness coefficient is introduced, which is obtained by statistically analyzing the fluctuation (such as variance, standard deviation) or degradation probability of the channel state parameters (or key characteristic values) within a preset historical time period (such as the previous few minutes or hours). Finally, through weighted averaging or other fusion rules, the initial service quality assessment value is combined with the channel robustness coefficient to generate the final channel utility value. This allows a channel with moderate current quality but long-term stability to potentially outperform a channel with excellent current quality but drastic fluctuations.

[0065] Furthermore, the network layer control instructions obtained in step S300 for coordinating route discovery, maintenance, and data forwarding behavior between the master node and user nodes in a highly dynamic ship network include: Step S310: Perform network initialization operation and perform status detection on the preset control channel.

[0066] When a ship node powers on or joins the network, it first performs network initialization operations, including loading the network identifier, configuring initial communication parameters, and performing status checks on the preset common control channel. This check typically involves monitoring the received signal strength or carrier sensing to determine whether the control channel is occupied by other nodes. This step ensures the network protocol stack is ready and prepares an idle channel environment for subsequent orderly neighbor discovery and signaling interaction to avoid message collisions; it is the starting point of the network self-organization process.

[0067] Step S320: When the control channel is detected as idle, transmit a neighbor node probe signal and receive a response signal from the neighbor node.

[0068] Once the control channel is confirmed to be idle, the node broadcasts a neighbor probe signal on that channel, containing its own identifier and capabilities. Other nodes within the communication coverage area (neighboring nodes) receive this probe signal and reply with a response signal containing their own network state information within a pre-agreed timeframe. Through this question-and-answer interaction, the node can discover other neighboring nodes within its single-hop communication range and obtain their basic reachability and state information. This is the direct data source for constructing the local network topology and subsequent route calculations.

[0069] Step S330: Based on the response signal, establish or update the routing table between the master node and the user node.

[0070] Based on the received response signals from neighboring nodes, each node extracts key information (such as neighboring node identifiers, link quality, and geographical location) to establish or update its internally maintained routing table. This routing table records the next-hop node and path metric information for reaching a known network destination (which may be another ship node or a shore-based gateway). The routing table is dynamically updated when a new neighboring node is discovered or when the link status of an existing neighboring node changes.

[0071] Step S340: Based on the ship network service data to be sent and the changes in the routing table, generate a message to be sent through the control channel and execute the sending operation. The message includes a data frame and / or a routing update message.

[0072] Based on the received response signals from neighboring nodes, each node extracts key information (such as neighboring node identifiers, link quality, and geographical location) to establish or update its internally maintained routing table. This routing table records the next-hop node and path metric information for reaching a known network destination (which may be another ship node or a shore-based gateway). The routing table is dynamically updated when a new neighboring node is discovered or when the link status of an existing neighboring node changes.

[0073] Furthermore, the physical layer configuration parameters include multi-level orthogonal spread spectrum modulation parameters. Accordingly, the corresponding physical layer configuration parameters are generated, including: determining the number of levels M and the corresponding orthogonal spread spectrum code for the multi-level orthogonal spread spectrum based on the available bandwidth of the current optimal transmission channel and the service quality requirements of the current service to be transmitted.

[0074] After selecting the optimal transmission channel, matching physical layer signal waveform parameters need to be generated to ensure reliable transmission. Given the complex and potentially interfering environment of shipborne VHF communication, this invention employs multi-level orthogonal spread spectrum as the core anti-interference modulation technique. Two core parameters of this technique need to be adaptively determined: the radix M and the orthogonal spread spectrum code used. The determination process mainly relies on two factors: first, the measured or theoretically available bandwidth of the selected channel, which constitutes the spectral constraint of the transmitted signal; and second, the quality of service requirements of the current service to be transmitted, particularly its requirements for transmission rate, anti-interference level, and real-time performance. Through a pre-defined mapping relationship or algorithm, under the premise of satisfying channel bandwidth limitations, a higher radix M is selected for services with high real-time performance but small data volume (such as security signaling) to obtain stronger anti-interference capabilities and lower bandwidth expansion; while for high-bandwidth services (such as image transmission), a lower M value may be selected to ensure sufficient effective information transmission rate. Meanwhile, from a set of spreading codes with good orthogonality, specific orthogonal spreading codes are selected based on the number of users in the network, interference environment, or security level requirements to distinguish different users or enhance anti-collision capabilities.

[0075] Furthermore, the generation of corresponding physical layer configuration parameters and link control signals in step S300 also includes the configuration process of the multi-level orthogonal spread spectrum modulator, including: In step S351, the field-programmable gate array performs mapping encoding of multi-level information and corresponding pseudo-random codes according to the transmit enable signal and multi-level orthogonal spread spectrum modulation parameters to generate a digital baseband signal.

[0076] Upon receiving the transmit enable signal, the Field-Programmable Gate Array (FPGA) initiates the baseband signal generation process based on the determined multi-ary orthogonal spread spectrum modulation parameters (specifically, the ary number M and the selected orthogonal spread spectrum code). Its internal logic first groups the binary data stream to be transmitted into log2(M) bits, mapping it to an M-ary symbol sequence. Subsequently, each symbol triggers the selection of a corresponding long pseudo-random code sequence with good autocorrelation and cross-correlation properties from the orthogonal spread spectrum code set. By digitally synthesizing the pseudo-random code sequences mapped from the symbols, the final baseband digital signal stream is generated.

[0077] Step S352: Convert the digital baseband signal to an analog signal to obtain an analog differential baseband signal.

[0078] The digital baseband signal generated by the field-programmable gate array (FPGA) is a discrete digital quantity and needs to be converted into a continuous analog signal for subsequent radio frequency (RF) processing. This digital signal is fed into a high-speed digital-to-analog converter (DAC), which restores the digital sequence to an analog voltage waveform according to the system clock. To further improve common-mode interference immunity, this analog waveform is usually processed into a pair of differential signals with equal amplitude and opposite phase, namely analog differential baseband I-channel and Q-channel signals, preparing for subsequent quadrature modulation.

[0079] Step S353: The simulated differential baseband signal is directly modulated onto the radio frequency carrier.

[0080] The obtained analog differential baseband signal needs to be shifted to an radio frequency (RF) frequency for antenna radiation. This step is performed by an RF modulator (usually a quadrature modulator). The modulator receives an RF local oscillator signal generated by a frequency synthesis unit, with the frequency corresponding to the selected optimal channel operating frequency. The analog differential baseband I and Q signals are modulated onto two mutually orthogonal carriers, and then synthesized into a modulated RF signal within the modulator. This direct modulation method can efficiently shift the baseband spectrum to the target RF frequency.

[0081] In step S354, the field programmable gate array (FPGA) controls the digitally controlled attenuator to control the power of the modulated radio frequency signal.

[0082] The transmit power of the modulated RF signal needs precise control to adapt to changes in communication distance, overcome path loss, and reduce interference with other stations. The field-programmable gate array (FPGA) outputs a corresponding digital control word to the digitally controlled attenuator (DCA) based on upper-layer control commands or its built-in power control algorithm. As an adjustable element in the RF channel, the DCA adjusts its attenuation in real time according to this control word, thereby achieving fine-tuning of the RF signal power ultimately output to the power amplifier and ensuring that the transmitted signal strength remains within an appropriate range.

[0083] Furthermore, the highly dynamic ship network adopts a hierarchical architecture, including master control nodes with network addressing capabilities and user nodes without network addressing capabilities. The master control nodes form a decentralized, variable topology backbone network, while user nodes access the backbone network through roaming or communicate directly with adjacent nodes.

[0084] In highly dynamic ship network environments, traditional centralized or completely flat homogeneous network structures face challenges in scalability, reliability, and control overhead. To address this, this invention employs a layered network architecture that distinguishes network nodes into two logical roles: master control nodes and user nodes. Master control nodes are typically vessels with strong communication capabilities, high stability, or special missions within the network. They possess complete network layer functions, maintaining routing tables and performing network addressing and packet forwarding. These master control nodes are dynamically interconnected via wireless links, forming a distributed, decentralized backbone network whose topology adapts to changes in the relative positions of the vessels. On the other hand, numerous user nodes (usually small to medium-sized vessels) are designed as simplified terminals, lacking complex network layer addressing and routing capabilities. User nodes can roam and access the backbone network composed of master control nodes based on signal strength and link quality, relaying their data through the accessed master control nodes to achieve remote communication. Simultaneously, when the communication distance allows and direct communication conditions are met, user nodes can also exchange data directly without traversing the backbone network.

[0085] This architecture, which separates the "backbone" from the "access", effectively controls the flooding of control signaling caused by topology changes by limiting the number of nodes (master nodes) participating in global routing maintenance. At the same time, it allows a large number of user nodes to flexibly access the network, thereby significantly improving the overall node capacity and adaptability to dynamics of the system while ensuring network manageability and stability.

[0086] Accordingly, a second aspect of the present invention provides an electronic device, including: at least one processor and a memory connected to the at least one processor. The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, cause the at least one processor to perform the aforementioned hierarchical topology control and routing maintenance method applicable to highly dynamic ship networks.

[0087] Accordingly, a third aspect of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-described hierarchical topology control and routing maintenance method applicable to highly dynamic ship networks.

[0088] The embodiments of the present invention aim to protect a hierarchical topology control and routing maintenance method suitable for highly dynamic ship networks, which has the following effects: 1. By unifying the modeling and intelligent optimization of three types of ultra-shortwave channels with distinct physical characteristics—meteor trails, ionospheric scattering, and ground wave diffraction—the system can dynamically select the optimal transmission path based on real-time channel conditions and service requirements. This enables all-weather, beyond-line-of-sight reliable coverage of vast sea areas without relying on expensive satellites or dense shore-based facilities, fundamentally solving the inherent limitations of single transmission methods in terms of coverage, all-weather capability, or cost. 2. By adopting a decentralized hierarchical variable topology network architecture that strictly limits the number of backbone nodes and allows user nodes to access, and in conjunction with neighbor node discovery and route self-maintenance mechanisms, the network can effectively suppress broadcast storms when nodes change frequently and dynamically, and can achieve rapid self-healing and reconstruction when local nodes fail. This significantly improves the network's node capacity, topology adaptability and overall resilience in a highly dynamic ship environment, overcoming the single point of failure risk and scalability bottleneck of traditional centralized networks. 3. By deeply adapting multi-level orthogonal spread spectrum technology to VHF narrowband channels and dynamically configuring modulation parameters according to service requirements and channel conditions, the anti-co-channel interference capability and low interception probability of communication signals are significantly improved without increasing the radio frequency bandwidth. This enhances the transmission security and concealment of ship-to-ship networks in complex electromagnetic environments and effectively compensates for the shortcomings of existing systems, such as weak anti-interference measures and easy detection.

[0089] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A hierarchical topology control and route maintenance method suitable for highly dynamic ship networks, characterized in that, Includes the following steps: For a set of heterogeneous UHF transmission channels consisting of at least three types of transmission channels, including meteor trail communication, ionospheric scattering communication and ground wave diffraction communication, the channel state parameters of the transmission quality of each transmission channel are calculated in real time using a preset channel evaluation model. Based on the channel state parameters, as well as the priority and quality of service requirements of the current service to be transmitted, the quality of service requirements include requirements for at least one of transmission delay, bandwidth and reliability. The optimal transmission channel is dynamically selected from the set of ultra-shortwave heterogeneous transmission channels through a preset channel selection strategy. Based on the current optimal transmission channel, corresponding physical layer configuration parameters and link control signals are generated to obtain network layer control instructions for coordinating route discovery, maintenance, and data forwarding behaviors between the master control node and user nodes in the highly dynamic ship network.

2. The hierarchical topology control and routing maintenance method for highly dynamic ship networks according to claim 1, characterized in that, The method of calculating the channel state parameters of the transmission quality of each transmission channel in real time using a preset channel evaluation model includes: Obtain the channel type of the transmission channel; For meteor trail channels, obtain their channel availability probability, average burst duration, and raw measurement parameters; For the ionospheric scattering channel, we obtain its signal level fading standard deviation, Doppler frequency shift, signal fading depth, and raw measurement parameters; For the ground wave diffraction channel, obtain its path propagation loss and raw measurement parameters; Based on the corresponding parameters obtained for different channel types, channel state parameters characterizing the overall transmission quality of the transmission channel are calculated using the channel quality evaluation function corresponding to the channel type.

3. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 2, characterized in that, The calculation of channel state parameters characterizing the overall transmission quality of the transmission channel using a channel quality evaluation function corresponding to the channel type includes: The parameters obtained for the channel type are normalized and converted into dimensionless normalized parameter values. Based on the inherent transmission characteristics of the channel type and the service quality requirements of the current service to be transmitted, the preset weight mapping relationship is queried to obtain the dynamic weight coefficient corresponding to each of the normalized parameter values. Based on the dynamic weighting coefficient, the normalized parameter values ​​are weighted and synthesized to generate a scalar channel state parameter, wherein the value of the channel state parameter directly corresponds to the overall quality level of the transmission channel supporting the current service to be transmitted.

4. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 1, characterized in that, The step of dynamically selecting the optimal transmission channel from the set of heterogeneous UHF transmission channels based on the channel state parameters and the priority and quality of service requirements of the current service to be transmitted, through a preset channel selection strategy, includes: Based on the quality of service requirements of the current services to be transmitted, determine the comprehensive evaluation criteria for channel sequencing; Based on the comprehensive evaluation criteria and combined with the priority of the current service to be transmitted, the utility of the channel state parameters of each optional transmission channel is calculated to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted. The channel utility value is a quantitative evaluation value that characterizes the degree of contribution of the optional transmission channel to meeting the service quality requirements. All the available transmission channels are sorted according to the channel utility value to generate a channel selection sequence; The current optimal transmission channel is determined based on the channel selection sequence and the real-time availability status of each transmission channel in the ultra-shortwave heterogeneous transmission channel set.

5. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 4, characterized in that, Based on the comprehensive evaluation criteria and in conjunction with the priority of the current service to be transmitted, the utility of the channel state parameters of each optional transmission channel is calculated to obtain the channel utility value of each optional transmission channel supporting the current service to be transmitted, including: Based on the comprehensive evaluation criteria, the service quality requirements of the current service to be transmitted are decoupled into the demand intensity for different channel characteristic dimensions, forming a demand feature vector; The priority of the current service to be transmitted is mapped to a global correction factor on the demand feature vector to obtain the priority correction factor; Based on the demand feature vector, the multiple channel characteristic values ​​represented by the channel state parameters of the optional transmission channel are normalized to obtain normalized channel characteristic values. The channel utility value is calculated by weighting the demand feature vector using the priority correction factor and then matching it with the normalized channel characteristic value.

6. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 5, characterized in that, The process of weighting the demand feature vector using the priority correction factor and then performing a matching operation with the normalized channel characteristic value to calculate the channel utility value includes: Based on the normalized channel characteristic value, calculate the degree of satisfaction of the optional transmission channel with each independent dimension of the quality of service requirement; Using the demand intensity of the corresponding dimension in the demand feature vector as the weight, the satisfaction of all the dimensions is weighted and aggregated to obtain the initial business quality evaluation value. The initial service quality evaluation value is fused with the channel robustness coefficient, which reflects the temporal stability of the selectable transmission channel within a preset time period, to obtain the channel utility value.

7. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 1, characterized in that, The network layer control instructions obtained for coordinating route discovery, maintenance, and data forwarding behaviors between the master control node and user nodes in the highly dynamic ship network include: Perform network initialization operations and check the status of the preset control channel; When the control channel is detected as idle, a neighbor node probe signal is transmitted, and a response signal from the neighbor node is received; Based on the response signal, establish or update the routing table between the master node and the user node; Based on the ship network service data to be sent and the changes in the routing table, a message to be sent through the control channel is generated and the sending operation is performed. The message includes a data frame and / or a routing update message.

8. The hierarchical topology control and routing maintenance method for highly dynamic ship networks according to any one of claims 1-7, characterized in that, The physical layer configuration parameters include multi-level orthogonal spread spectrum modulation parameters; The generation of the corresponding physical layer configuration parameters includes: Based on the available bandwidth of the current optimal transmission channel and the quality of service requirements of the current service to be transmitted, the number M of the multi-ary orthogonal spread spectrum and the corresponding orthogonal spread spectrum code are determined.

9. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to claim 8, characterized in that, The generation of corresponding physical layer configuration parameters and link control signals also includes the configuration process of the multi-level orthogonal spread spectrum modulator, including: The field-programmable gate array (FPGA) performs mapping and encoding of multi-level information and corresponding pseudo-random codes according to the transmit enable signal and the multi-level orthogonal spread spectrum modulation parameters to generate a digital baseband signal. The digital baseband signal is converted from digital to analog to obtain an analog differential baseband signal; The simulated differential baseband signal is directly modulated onto the radio frequency carrier; The field-programmable gate array (FPGA) controls the digitally controlled attenuator to control the power of the modulated radio frequency signal.

10. The hierarchical topology control and route maintenance method for highly dynamic ship networks according to any one of claims 1-7, characterized in that, The highly dynamic ship network adopts a hierarchical architecture, including master control nodes with network addressing capabilities and user nodes without network addressing capabilities. The master control nodes form a decentralized, variable topology backbone network, and the user nodes access the backbone network through roaming or communicate directly with adjacent nodes.

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