A marine multi-link fusion communication method and system

Abstract

The present application relates to the technical field of ship communication, and especially relates to a marine multi-link fusion communication method and system. The method comprises the following steps: receiving sailing information broadcast by other ships within a preset range, and performing communication frequency band availability evaluation to generate sea area communication channel state data; obtaining geographic position data of each ship; performing spatial communication link potential analysis according to the geographic position data of each ship and the sea area communication channel state data to generate cross-link spatial communication potential data; constructing a multi-link ad hoc network topology structure according to the cross-link spatial communication potential data; performing task-adaptive communication link allocation based on the multi-link ad hoc network topology structure, and constructing a multi-link fusion transmission strategy to realize real-time communication link safety switching management. The present application realizes real-time communication safety switching and high-reliability transmission of a marine formation based on communication service adaptation and a multi-link fusion transmission strategy.

Description

Technical Field

[0001] This invention relates to the field of marine communication technology, and in particular to a marine multi-link converged communication method and system. Background Technology

[0002] The maritime communication environment is significantly complex and harsh. On the one hand, the electromagnetic environment at sea is complex and variable, with problems such as multipath effects, Doppler shift, and high noise interference. On the other hand, sea conditions change drastically, and rough seas in severe weather cause frequent changes in vessel attitude, leading to instability in antenna pointing and link quality. However, currently widely used marine communication systems are mainly based on single communication technologies or simple backup redundancy mechanisms, which are difficult to adapt to the communication needs of large-scale formations in complex sea conditions. Traditional maritime communication systems typically use time-division multiplexing ad hoc networking technology. When handling multi-hop forwarding scenarios, the total network bandwidth decreases sharply with the number of hops. For example, in a typical time-division multiplexing architecture, two-hop forwarding can cause the network bandwidth to drop to less than 50% of its original level, and three-hop forwarding can drop it to less than 25%. This bandwidth attenuation severely limits the communication efficiency of large-scale formations and cannot meet the real-time high-bandwidth service requirements. The Doppler shift generated by the high-speed movement of multi-hull formations, as well as various interferences from surrounding equipment and the external environment, all contribute to a significant reduction in the reliability of maritime communication links. In severe sea conditions, link interruptions and packet loss occur frequently, making it impossible to guarantee communication quality. Summary of the Invention

[0003] Based on this, the present invention provides a marine multi-link converged communication method and system to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a marine multi-link converged communication method includes the following steps:

[0005] Step S1: Receive navigation information broadcast by other vessels within a preset range to obtain dynamic information of surrounding vessels; classify the communication link quality level based on the dynamic information of surrounding vessels to obtain link quality rating data; acquire current marine meteorological and hydrological data; evaluate the availability of communication frequency bands for the dynamic information of surrounding vessels using the current marine meteorological and hydrological data and the link quality rating data, and generate marine communication channel status data.

[0006] Step S2: Use BeiDou-3 navigation equipment to obtain the geographical location data of each vessel; based on the geographical location data of each vessel and the status data of the sea area communication channels, perform a space communication link potential analysis to generate cross-link space communication potential data;

[0007] Step S3: Divide feasible link communication clusters based on cross-chain spatial communication potential data and construct a multi-link self-organizing network topology;

[0008] Step S4: Based on the multi-link self-organizing network topology, perform task adaptation communication link allocation and generate multi-link communication task adaptation data; execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

[0009] Preferably, the present invention also provides a marine multi-link converged communication system that executes the marine multi-link converged communication method described above. The marine multi-link converged communication system includes:

[0010] The channel status awareness module is used to receive navigation information broadcast by other ships within a preset range to obtain dynamic information of surrounding ships; classify the communication link quality level based on the dynamic information of surrounding ships to obtain link quality rating data; acquire current marine meteorological and hydrological data; and evaluate the availability of communication frequency bands based on the current marine meteorological and hydrological data and link quality rating data to generate marine communication channel status data.

[0011] The link potential analysis module is used to obtain the geographical location data of each vessel using Beidou-3 navigation equipment; and to perform space communication link potential analysis based on the geographical location data of each vessel and the status data of the sea area communication channels, thereby generating cross-link space communication potential data.

[0012] The network topology construction module is used to divide feasible link communication clusters based on cross-chain spatial communication potential data and construct a multi-link self-organizing network topology.

[0013] The link fusion scheduling module is used to allocate communication links for task adaptation based on the multi-link self-organizing network topology, generate multi-link communication task adaptation data, execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

[0014] This invention demonstrates advanced features in multiple aspects of its ship communication system design. During navigation, a reliable, convenient, and resilient self-organizing network is needed to interconnect all vessels within the formation. Furthermore, given the maritime communication environment, an efficient and interference-resistant communication design is required to ensure real-time communication between vessels and between vessels and higher command nodes. Therefore, this solution incorporates targeted designs in three areas: interference resistance, self-organizing network characteristics, and multi-hop relay capabilities. This results in high stability and ease of operation for the ship formation's communication functions in actual combat, showcasing the highly advanced nature of its communication system design.

[0015] (1) Anti-interference capability. Addressing issues such as multipath fading, inter-symbol interference, and Doppler shift caused by high-speed navigation encountered in nighttime maritime communication scenarios, this solution employs frequency hopping technology and a signal processing mode combining Turbo code COFDM technology, AMC technology, and ARQ transmission mechanism. This successfully resolves reliability issues in unstable communication environments. This design not only selects and utilizes sub-channels with high signal-to-noise ratios during modulation to ensure the ship's high-speed data transmission needs, but also automatically selects appropriate modulation methods in low signal-to-noise ratio environments. The data packet detection and retransmission mechanism also ensures the reliability of communication within the formation. This multi-technology integration reflects the advanced thinking behind the ship communication system in addressing the anti-interference requirements of maritime communication.

[0016] (2) Characteristics of self-organizing networks. Wireless broadband self-organizing networks are decentralized self-organizing systems where all nodes are equal, support TDD bidirectional communication, have simple frequency management, and high spectrum utilization. Any node device can be used as an end node, relay node, or command node in the network. Furthermore, when a node in the network fails, the forwarding tasks originally performed through that node will be relayed through other nodes under the guidance of the routing protocol, selecting the optimal transmission path, and the entire network can still self-heal and function normally. This design greatly improves the operability of ship formations in real-world scenarios and simplifies the manual operations required, making the communication system user-friendly, durable, simple, and advanced.

[0017] (3) Multi-hop relay capability. Ship formations need to achieve real-time communication between at least 30 nodes. Traditional wireless ad hoc network communication systems use time-division multiplexing (TDM) for data transmission. To avoid interference, two or more nodes are not allowed to transmit simultaneously in the same time slot; that is, at any given moment, only one node in the ship ad hoc network is transmitting data, while the others are receiving. This traditional networking technology affects the real-time performance and success rate of information exchange and task execution within law enforcement formations, and is not suitable for the actual application scenarios of ship formations. To address this issue, this solution designs a spatial time-division multiplexing technology with optimized multi-hop relay capability. Based on the ad hoc network topology information of the wireless ad hoc network, it fully utilizes the spatial isolation between nodes on the transmission link. While ensuring that transmission and reception do not interfere with each other, it allows two or more nodes to transmit simultaneously in the same time slot, thus enabling the wireless relay channel resources to be reused based on spatial intervals. Compared to the traditional strict time-division multiplexing (TDM) mode, the transmission bandwidth in STDM mode is not continuously consumed by the number of hops, thereby supporting real-time communication by ships at any time.

[0018] This invention utilizes a multi-dimensional sensing and intelligent fusion mechanism to effectively address the key challenges of traditional maritime communication systems in large-scale formations and adverse sea conditions. By comprehensively collecting dynamic information from surrounding vessels and integrating it with marine meteorological and hydrological data, it achieves precise perception and assessment of the marine electromagnetic environment. This enables the system to proactively identify and avoid unfavorable communication conditions, significantly improving communication adaptability in complex sea conditions. Particularly in complex channel environments such as multipath propagation, frequency shift, and strong interference, this method can intelligently select the optimal frequency band, significantly enhancing signal transmission stability. The introduction of the BeiDou-3 navigation system provides high-precision geographic location support. Combined with spatial communication potential analysis based on communication channel status data, the system can fully utilize the spatial distribution characteristics between vessels to achieve optimal communication resource allocation. This link potential analysis mechanism based on spatial characteristics effectively avoids the sharp bandwidth attenuation problem caused by multi-hop forwarding in traditional time-division multiplexing ad hoc networks, providing continuous and stable high-bandwidth communication assurance for large-scale formations. Through intelligent processing of cross-link spatial communication potential data, the system can adaptively divide communication clusters and construct multi-link ad hoc network topologies, achieving dynamic optimization of the network structure. This mechanism effectively alleviates network congestion, improves communication efficiency, and ensures uninterrupted communication links between any nodes within a large formation, guaranteeing real-time transmission of command and control information even in adverse sea conditions. The dynamic communication link allocation strategy based on mission requirements enables the system to intelligently schedule the most suitable communication resources according to the bandwidth, latency, and reliability requirements of different service types, achieving efficient utilization of communication resources. The multi-link parallel transmission mechanism significantly improves the overall transmission capacity of the system through intelligent distribution and reassembly of data streams, while the multi-link fusion transmission strategy ensures the continuity and integrity of data transmission. The real-time communication link secure switching management mechanism provides the system with extremely strong fault tolerance and communication resilience. When a link is interfered with or interrupted, the system can seamlessly switch to a backup link, ensuring uninterrupted communication and greatly improving the safety and success rate of maritime missions. Therefore, the present invention provides a marine multi-link converged communication method that uses AIS broadcasts and marine meteorological and hydrological data to classify the channel quality and assess the frequency band availability of shortwave, ultra-shortwave, and satellite links. It combines the channel state matrix to perform isolation analysis on the spatial potential of each link and divides it into reusable communication clusters. Based on spatial potential and service requirements, a multi-link self-organizing network topology is constructed. An improved graph coloring and time slot weighted allocation algorithm is used to achieve parallel channel partitioning of spatial-time division multiplexed links. Based on service priority and real-time channel snapshots, fuzzy logic control and adaptive frequency hopping and differentiated subcarrier allocation strategies are used to dynamically schedule parallel transmission of each link and perform seamless and secure handover management when link performance degrades. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the steps of a marine multi-link converged communication method according to the present invention.

[0020] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S2.

[0021] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0023] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0024] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0025] To achieve the above objectives, please refer to Figures 1 to 2 This invention provides a marine multi-link converged communication method, comprising the following steps:

[0026] Step S1: Receive navigation information broadcast by other vessels within a preset range to obtain dynamic information of surrounding vessels; classify the communication link quality level based on the dynamic information of surrounding vessels to obtain link quality rating data; acquire current marine meteorological and hydrological data; evaluate the availability of communication frequency bands for the dynamic information of surrounding vessels using the current marine meteorological and hydrological data and the link quality rating data, and generate marine communication channel status data.

[0027] Step S2: Use BeiDou-3 navigation equipment to obtain the geographical location data of each vessel; based on the geographical location data of each vessel and the status data of the sea area communication channels, perform a space communication link potential analysis to generate cross-link space communication potential data;

[0028] Step S3: Divide feasible link communication clusters based on cross-chain spatial communication potential data and construct a multi-link self-organizing network topology;

[0029] Step S4: Based on the multi-link self-organizing network topology, perform task adaptation communication link allocation and generate multi-link communication task adaptation data; execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

[0030] In this embodiment of the invention, the marine multi-link converged communication method includes the following steps:

[0031] Step S1: Receive navigation information broadcast by other vessels within a preset range to obtain dynamic information of surrounding vessels; classify the communication link quality level based on the dynamic information of surrounding vessels to obtain link quality rating data; acquire current marine meteorological and hydrological data; evaluate the availability of communication frequency bands for the dynamic information of surrounding vessels using the current marine meteorological and hydrological data and the link quality rating data, and generate marine communication channel status data.

[0032] In this embodiment of the invention, each ship receives navigation information periodically broadcast by other ships within a preset 50-nautical-mile range via an AIS receiver. This information includes ship identification number, speed, heading, and draft, forming a dynamic information database of surrounding ships. Subsequently, the shipborne communication quality assessment system classifies each link into quality levels: first, by measuring the signal-to-noise ratio, bit error rate, and multipath effect index of each link, a comprehensive quality score is calculated; then, based on the score, the links are divided into four levels: A (excellent), B (good), C (average), and D (poor), and recorded in a link quality rating data table. Simultaneously, meteorological and hydrological data such as wind speed, wind direction, wave height, precipitation intensity, and cloud cover in the current sea area are obtained through shipborne weather radar, marine buoy sensor networks, and the fleet weather broadcasting system. Finally, the availability of different communication frequency bands (shortwave 2-30MHz, VHF 30-300MHz, VHF 300MHz-3GHz) under the current sea state is comprehensively evaluated to generate sea area communication channel status data, including a three-dimensional mapping table of frequency-interference-reliability.

[0033] Step S2: Use BeiDou-3 navigation equipment to obtain the geographical location data of each vessel; based on the geographical location data of each vessel and the status data of the sea area communication channels, perform a space communication link potential analysis to generate cross-link space communication potential data;

[0034] In this embodiment of the invention, real-time precise position data, including latitude and longitude coordinates, altitude, and velocity vector, is acquired through a shipborne BeiDou-3 receiving terminal, with a position accuracy better than 5 meters. The system records the relative positional relationships of all ships in the formation and constructs a three-dimensional spatial distribution model. Subsequently, based on the geographical location data of each ship and the sea area communication channel status data obtained in step S1, a space communication link potential analysis is performed: by calculating the straight-line distance between any two ships, the angle between the connecting line and the sea surface, and the antenna height difference, combined with a free-space propagation loss model, the theoretical communication quality of each link is predicted; then, the influence of environmental factors in the sea area communication channel status data, including wave scattering effects, atmospheric refractive index changes, and ocean evaporation waveguide effects, is superimposed to correct the theoretical communication quality; finally, considering the propagation characteristics of each frequency band, the communication potential level is marked for multiple frequency band links between each pair of ships, generating a cross-link space communication potential data matrix, recording the feasibility, quality expectations, and optimal frequency band selection for establishing communication between all ship nodes.

[0035] Step S3: Divide feasible link communication clusters based on cross-chain spatial communication potential data and construct a multi-link self-organizing network topology;

[0036] In this embodiment of the invention, based on cross-chain spatial communication potential data, a list of potentially available communication links is first identified. The screening criteria are a signal-to-noise ratio exceeding 10 dB and an expected link stabilization time exceeding the task duration. Subsequently, resource reuse is assessed for the potentially available links, calculating the spatial isolation and mutual interference coefficient between any two links. When the spatial isolation is greater than 45 degrees and the mutual interference coefficient is less than -90 dB / mW, it is marked as a spatially reusable feasible link pair. Then, a graph coloring algorithm is used to divide the spatially reusable feasible link pairs into multiple communication clusters, ensuring that there is no spatial reuse feasibility for links within the same communication cluster. Within each communication cluster, an improved time slot allocation algorithm is applied to implement a time-division multiplexing mechanism: the communication cycle is divided into multiple time slots, and time slot resources are allocated to each link according to link priority and bandwidth requirements, ensuring that high-priority links receive priority transmission opportunities. Finally, by integrating spatial multiplexing and time-division multiplexing mechanisms, a multi-link self-organizing network topology is constructed, forming a complete network connection graph that supports flexible multi-link concurrent communication.

[0037] Step S4: Based on the multi-link self-organizing network topology, perform task adaptation communication link allocation and generate multi-link communication task adaptation data; execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

[0038] In this embodiment of the invention, communication task requests from the command system are received, and required parameters such as data rate, latency, and reliability are extracted. A multi-factor weighted scoring method is used to classify tasks, forming a service priority list. Subsequently, the time slot resource configuration of each communication cluster is adjusted to prioritize high-priority task requirements. The source transmission nodes for each task are determined based on the topology, and multiple potential transmission paths are calculated. Communication resources are optimized and allocated according to the number of time slots required for each node to complete data transmission within the communication cluster, generating multi-link communication task adaptation data. Next, real-time quality analysis of the communication links is performed, dividing the links into high, medium, and low quality levels, and configuring different modulation schemes and coding rates for each. Differentiated subcarrier allocation and adaptive frequency hopping mechanisms are implemented based on link quality to construct a multi-link fusion transmission strategy. Finally, redundant transmission configuration for key data is implemented, a ship network connectivity model is constructed, node communication weight coefficients are calculated, multi-path routing is performed based on physical distance data, and load balancing control and data priority strategy management are implemented to achieve secure switching and continuous stable operation of the multi-link communication system.

[0039] Preferably, receiving navigation information broadcast by other vessels within a preset range in step S1 includes:

[0040] Obtain the ship's unique identification code and the specific pseudo-random sequence preset for each communication link;

[0041] The detection signal to be loaded is obtained by digital encoding and waveform shaping based on the ship's unique identification code and the specific pseudo-random sequences preset in each communication link.

[0042] Based on the detection signal to be loaded, parameter commands are issued to specify the low-power transmission target level value of each link in order to obtain the configuration command for the transmission link to be activated.

[0043] The transmission link type and the actual output power value fed back by the self-organizing network radio are determined according to the transmission link configuration command to be activated, and the radio frequency front-end is activated to start the all-time, multi-channel concurrent monitoring mode and obtain the activated multi-link concurrent monitoring status.

[0044] Based on the active multi-link concurrent listening state, a spectrum scan monitoring of 0.5-3000MHz is performed, and the broadband digital intermediate frequency streams received by the unidirectional AIS receiver in each link are subjected to real-time matched filtering to generate neighbor detection and acquisition signals.

[0045] Based on the neighbor detection and capture signals, identify the neighbor's vessel signals to obtain a single vessel detection event;

[0046] The dynamic information of surrounding vessels is aggregated based on a single vessel detection event to obtain dynamic information of surrounding vessels.

[0047] In this embodiment of the invention, the system reads a nine-digit maritime mobile service identification code as the unique identifier for the vessel. Simultaneously, it extracts 1024-bit pseudo-random sequences pre-set for VHF, HF, and satellite links from the encrypted storage area built into the communication controller. These sequences are generated through a linear feedback shift register, with seed values ​​obtained by multiplying the vessel's identification code by a fixed prime number (e.g., 7919, 7907, 7901) and then taking the modulo operation, ensuring that each vessel possesses a unique and unpredictable pseudo-random sequence on different links. Digital encoding employs forward error-correcting convolutional coding with a code rate of 1 / 2 and a constraint length of 7. The unique identifier for the vessel is converted into a binary sequence and then XORed with the corresponding pseudo-random sequence of the communication link. Waveform shaping processing uses a root-raised cosine filter with a roll-off factor of 0.35 and a bandwidth 1.35 times the signal bandwidth to achieve concentrated spectral energy. For the UHF link, Gaussian minimum shift keying modulation is used; for the HF link, orthogonal frequency division multiplexing modulation is used; and for the satellite link, quadrature phase shift keying modulation is used to generate intermediate frequency digital signal streams, forming the probe signal to be loaded. The communication controller calculates the optimal transmit power based on the characteristics of the probe signal to be loaded: below 5 watts for the UHF link, below 10 watts for the HF link, and below 2 watts for the satellite link. Transmission parameters are transmitted to each transmitting unit via a serial communication bus at a baud rate of 115200. The transmission command includes four key parameters: transmit frequency, bandwidth, power, and modulation method, each occupying 4 bytes, forming a 16-byte command frame. A 2-byte cyclic redundancy check (CRC) code is added to the command frame to ensure transmission correctness, constituting the configuration command for the transmit link to be activated. The controller executes three command transmissions to ensure at least one successful reception. Based on the configuration command for the transmit link to be activated, the RF front-ends of the three links—UHF (156MHz band), HF (2-30MHz band), and satellite (1.6GHz band)—are activated sequentially. Each RF front-end comprises three core components: a low-noise amplifier, a mixer, and a power amplifier. The actual output power is read through a status register, verifying that the deviation from the commanded power does not exceed 0.5 dB. Simultaneously, a full-time monitoring mode is activated, with three channels operating in parallel. The sampling rate is 48 kHz per channel, and the quantization precision is 16 bits, enabling concurrent monitoring of the three links and continuous surveillance of surrounding signals. The shipborne multi-link receiving system employs a digital receiver, performing spectrum scanning in 100 kHz steps within the 0.5-3000 MHz band, with a dwell time of 10 milliseconds at each frequency point. The received wideband digital intermediate frequency stream undergoes digital downsampling processing and is then detected by a matched filter. The matched filter coefficients are convolved with the waveform of the probe signal transmitted by the ship and inverted to achieve maximum signal-to-noise ratio reception.The VHF link employs a cyclic scanning of eight channels from 156.025 to 162.025 MHz, while the HF link alternately monitors six frequencies: 2082.5 kHz, 4125 kHz, 6215 kHz, 8291 kHz, 12290 kHz, and 16420 kHz. The satellite link is fixed at 1626.5 MHz for reception, generating neighbor detection acquisition signals. The acquired neighbor detection signals are demodulated: the VHF signal uses Gaussian minimum shift keying demodulation, the HF signal uses orthogonal frequency division multiplexing demodulation, and the satellite signal uses quadrature phase shift keying demodulation. The demodulated digital bitstream undergoes forward error correction decoding via a convolutional decoder to recover the original data. The first 12 bytes of the data frame contain a 9-bit ship identification code and a 3-bit link type code, with data integrity verified through cyclic redundancy check. The signal processing unit extracts three core pieces of information—ship identification code, communication link type, and signal reception time—to form a single ship detection event, which is then stored in a temporary buffer. For multiple detection events of the same vessel, the time difference and signal strength change between two consecutive detections are calculated to deduce the vessel's relative speed and relative heading. The information processing system uses a Kalman filter algorithm to eliminate measurement noise, and after processing, obtains dynamic information such as the position, heading, and speed of surrounding vessels, updated every 30 seconds.

[0048] Of particular importance is the identification of neighboring vessel signals based on neighbor detection and signal capture, including:

[0049] Link autocorrelation analysis was performed on the neighbor detection and acquisition signals to obtain link autocorrelation data;

[0050] The root mean square delay spread estimate is evaluated based on the link autocorrelation data to obtain the instantaneous multipath delay spread.

[0051] The offset of the signal carrier frequency is estimated from the neighbor detection and acquisition signal to obtain instantaneous Doppler frequency shift estimation data;

[0052] Instantaneous channel state analysis of the single-probe signal receiving link is performed based on instantaneous multipath delay spread and instantaneous Doppler frequency shift estimation data to generate single-probe channel state data.

[0053] A single ship detection event is bound to the channel state data of a single detection event; the single ship detection event includes the reception timestamp, source node identifier, reception link type, measured signal strength, measured signal-to-noise ratio data, and preliminary channel characteristics of each link.

[0054] In this embodiment of the invention, a sliding window processing method is used for the captured digital signal, with a window length of 1024 points and an overlap rate of 50%. For the sampled data within each window, an autocorrelation function is calculated using the formula R(τ)=∑[x(n)×x(n+τ)], where x(n) is the signal sample value, τ is the time delay variable, and the calculation range is from 0 to 511 sample points. The autocorrelation calculation is implemented using a fast algorithm based on Fast Fourier Transform (FFT). First, a 512-point FFT is performed on the signal to obtain the frequency domain representation X(f), then the power spectrum |X(f)|² is calculated, and finally, a 512-point IFFT is used to transform it back to the time domain to obtain the autocorrelation function R(τ). The calculation results are normalized, with the main peak value standardized to 1, forming a link autocorrelation data curve, and feature parameters such as the autocorrelation peak position, peak height, and full width at half maximum (FWHM) are extracted. A threshold decision is made on the autocorrelation function R(τ), setting the threshold to 0.1 times the peak value, and all peak values ​​exceeding the threshold and their corresponding time delay values ​​τ are extracted. i The root mean square delay spread is estimated using the second-order moment calculation method, and the calculation formula is as follows: Where P(τ) i ) represents the corresponding time delay τ i The power value at the location is calculated. The result is converted to actual time units with a conversion factor of 5 microseconds for the sampling period, yielding the instantaneous multipath delay spread accurate to the nanosecond level. For shortwave links, the typical value is 1-5 milliseconds; for VHF links, it is 5-20 microseconds; and for satellite links, it is 0.1-1 microseconds. The received signal is converted to a complex number representation, expressed in the form I+jQ. The phase change rate is extracted by calculating the phase difference between consecutive frames, using the following formula: Where z(n) is the complex representation of the current sampling point, and z*(n-1) is the complex conjugate of the previous sampling point. The relationship between the phase change rate and the frequency offset is as follows: Where Ts is the sampling period, taken as 1 / 48000 seconds. A 10-point moving average filter is applied to the calculation results to eliminate the influence of random noise, ultimately obtaining the instantaneous Doppler frequency shift estimation data with an estimation accuracy of 0.1 Hz. The channel state analysis unit then applies the instantaneous multipath delay spread τ... ms Combined with the instantaneous Doppler frequency shift estimate fd, the channel coherence bandwidth Bc = 1 / (5×τ) is calculated. ms) and the coherence time \(T_c = 0.423 / f_d\). According to the calculation results, the channel type is judged: when the signal bandwidth \(B_s < B_c\) and the symbol period \(T_s < T_c\), it is classified as a flat slow fading channel; when \(B_s > B_c\) and \(T_s < T_c\), it is classified as a frequency selective slow fading channel; when \(B_s < B_c\) and \(T_s > T_c\), it is classified as a flat fast fading channel; when \(B_s > B_c\) and \(T_s > T_c\), it is classified as a frequency selective fast fading channel. Based on the judgment results, the system records the channel status code, fading type, coherence bandwidth value, coherence time value, and channel stability score, and generates a single detection channel status data structure containing 15 parameters. The system creates a detection event data structure, which includes the reception timestamp (a 64-bit integer accurate to milliseconds), the source node identifier (a 9-bit ship identification code), the reception link type (a 1-byte encoding, representing links such as shortwave, ultra-shortwave, satellite communication, etc.), the measured signal strength (a floating-point number in dBm, ranging from -120 to 0), and the measured signal-to-noise ratio data (a floating-point number in dB, ranging from -10 to 50). At the same time, the preliminary channel characteristics of each link are recorded, including parameters such as multipath extension, Doppler shift, coherence bandwidth, coherence time, and channel stability score. The system writes the complete single ship detection event into the ship detection database, and the index key is the combined value of "timestamp_ship identification code_link type".

[0055] Preferably, the communication link quality level division according to the surrounding ship dynamic information in step S1 includes the following steps:

[0056] Extract the measured signal strength of the communication link and the measured signal-to-noise ratio data of the communication link according to the surrounding ship dynamic information;

[0057] Mark the links with a measured signal strength of the communication link greater than -85 dBm and a measured signal-to-noise ratio data of the communication link greater than 12 dB through a preset link quality classification threshold to obtain high-quality link identification data;

[0058] Mark the links with a measured signal strength of the communication link between -85 dBm and -100 dBm and a measured signal-to-noise ratio data of the communication link between 8 dB and 12 dB through a preset link quality classification threshold to obtain medium-quality link identification data;

[0059] Based on the high-quality link identification data and the medium-quality link identification data, mark the communication links that do not meet the above conditions to obtain low-quality link identification data;

[0060] Perform a communication link quality rating on the surrounding ship dynamic information through the high-quality link identification data, medium-quality link identification data, and low-quality link identification data to obtain link quality rating data.

[0061] In this embodiment of the invention, all ship communication events recorded within the last 300 seconds are retrieved from the surrounding ship dynamic information database table. Data extraction uses a structured query to filter out four key fields: ship identification code, link type, measured signal strength (RSSI), and measured signal-to-noise ratio (SNR). For shortwave links, the system reads the signal power value from the receiver front-end measurement point and converts it into a digital quantity within the range of -120dBm to 0dBm using an 8-bit analog-to-digital converter. The signal-to-noise ratio data is calculated using the power spectral density ratio, with the formula SNR = 10 × log0. 10 (Ps / Pn), where Ps is the average power within the signal bandwidth, and Pn is the noise power within the same bandwidth. The system iterates through the extracted link data and performs conditional judgment: when the measured signal strength of the communication link is greater than -85dBm and the measured signal-to-noise ratio is greater than 12dB, the link is marked as a high-quality link. During the marking process, a link quality identification bitmap is created, with each ship link corresponding to a 4-byte status word, where bit 0 is set to indicate a high-quality link. For links that meet the conditions, the system records parameters such as link number, ship identification code, signal strength value, signal-to-noise ratio value, link hold time (in seconds), and link change trend (rising, stable, or falling), forming a high-quality link identification data structure, and calculates the link reliability score. The scoring formula is Q = 0.6 × (RSSI + 120) / 120 + 0.4 × SNR / 30, with the result ranging from 0 to 1. The measured signal strength of the communication link is within the closed interval of -85dBm to -100dBm and the measured signal-to-noise ratio is within the closed interval of 8dB to 12dB. The judgment process is implemented using an interval comparator circuit. When the comparator output AND operation result is true, the first bit of the corresponding link is set to 1 in the link quality identifier bitmap to indicate a medium-quality link. The system establishes a data structure for each medium-quality link, recording link stability indicators in addition to basic link parameters. The variance is calculated through the variance of 10 consecutive measurements, and the variance formula is σ. 2 =∑(xi-μ) 2 / n, where xi is a single measurement value, μ is the average value, and n is the number of measurements. The quality scoring formula for the medium-quality link is Q=0.5×(RSSI+100) / 15+0.3×(SNR-8) / 4+0.2×(1-σ 2 / 25), with a result range of 0 to 1. Signal strength is below -100dBm or signal-to-noise ratio is below 8dB. When performing the marking operation, the system sets the second bit of the corresponding link to 1 in the link quality identification bitmap to indicate a low-quality link. Low-quality links are further subdivided into three subcategories: weak signal type (signal strength < -100dBm but signal-to-noise ratio > 8dB), high noise type (signal strength > -100dBm but signal-to-noise ratio < 8dB), and double degradation type (signal strength < -100dBm and signal-to-noise ratio < 8dB). The system records the subcategory code, link maintenance probability, and link recovery suggestion strategy for each low-quality link. The low-quality link scoring formula is Q = 0.7 × (RSSI + 110) / 10 + 0.3 × SNR / 8, with a result range of 0 to 1. Links with a score below 0.4 are marked as unusable. High-quality, medium-quality, and low-quality link identification data are integrated to construct a complete link quality rating data structure. The rating data is indexed according to the ship identification code, and each ship record contains the quality rating results for all available links. The link quality level is represented by one byte: the high four bits represent the quality level (3-high quality, 2-medium quality, 1-low quality, 0-unavailable), and the low four bits represent the link type code (1-shortwave, 2-VHF, 3-satellite, 4-microwave). The system calculates the optimal communication link sequence for each ship, with the priority calculation formula being P = Q × T × R, where Q is the link quality score, T is the link throughput coefficient, and R is the reciprocal of the link resource consumption. The rating results are stored in the link quality database, updated every 300 milliseconds, and a link switching recommendation table is generated.

[0062] Preferably, step S1, which assesses the availability of communication frequency bands for surrounding vessel dynamics using current marine meteorological and hydrological data and link quality rating data, includes:

[0063] Spectrum power density analysis is performed based on link quality rating data, and spectrum occupancy status is assessed to generate spectrum occupancy status data.

[0064] Based on current marine meteorological and hydrological data, the propagation environment impact factors of each frequency band are correlated to obtain meteorological impact factors;

[0065] Multipath signal propagation was measured using an array antenna, and channel delay characteristics were correlated and corrected based on meteorological influence factors to obtain channel delay characteristic data.

[0066] The availability of each frequency band in the communication environment is evaluated by using channel delay characteristic data to assess spectrum occupancy status data, thereby generating maritime communication channel status data.

[0067] In this embodiment of the invention, a digital spectrum analyzer is used to scan the 0.5-3000MHz frequency band with a scan step size of 1kHz and a dwell time of 10ms. The acquired raw spectrum data is processed by Fast Fourier Transform, and the power spectral density estimate is calculated using the Welch method. The segment length is 1024 points, the overlap rate is 50%, and the Hanning window function is used. The calculation formula is PSD(f)=(1 / N)|∑x(n)w(n)e^(-j2πfn)| 2 Where x(n) is the sampled signal, w(n) is the window function, and N is the number of FFT points. The calculated power spectral density is compared with the background noise baseline, which is obtained by statistically analyzing the minimum value over 72 consecutive hours. When the frequency band power exceeds the background noise by 15dB, it is marked as occupied; when the power is lower than the background noise by 10dB, it is marked as idle; and when it is between the two, it is marked as partially occupied. The system divides the entire frequency band into 24 sub-bands, records the occupancy rate, interference level, and time-varying characteristics of each sub-band, and generates a spectrum occupancy status data table. Real-time data is obtained from the shipborne meteorological station and marine hydrological data interface, including air temperature (°C), air pressure (hPa), humidity (%), wind speed (m / s), wind direction (°), precipitation (mm / h), wave height (m), sea temperature (°C), and sea salinity (‰). For the shortwave (3-30MHz) band, the system calculates the atmospheric refractive index N = 77.6(P / T) + 3.73 × 10⁻⁶. 5 (e / T2), where P is air pressure (hPa), T is temperature (K), and e is water vapor pressure (hPa). For the VHF (30-300MHz) band, the radio wave attenuation coefficient α is calculated to be 0.0018 × f. 2 ×r / (1+0.0036×f 2The meteorological influence factor for the satellite communication band (1-3GHz) is calculated as I = w1×(T / T0) + w2×(P / P0) + w3×(H / H0) + w4×(R / R0) + w5×(S / S0), where T, P, H, R, and S represent temperature, air pressure, humidity, precipitation, and wave height, respectively. The subscript 0 indicates the standard condition value, and w1 to w5 are weighting coefficients derived from historical data training. The calculation results form a meteorological influence factor matrix covering the entire frequency band. An eight-element circular array antenna with an element spacing of half a wavelength operates in a wide frequency band of 0.5-3000MHz. The system transmits a detection signal, which is a linear frequency modulated pulse with a bandwidth of 100MHz and a pulse width of 10μs. The receiver uses a high-speed analog-to-digital converter with a baseband digital sampling rate of 200MHz to acquire the echo signal. The angle-of-arrival power spectrum P(θ) = a^H(θ)Ra(θ) is calculated using beamforming technology, where a(θ) is the array manifold vector and R is the received signal covariance matrix. The system detects significant peaks in the power spectrum and extracts the angle of arrival, time delay, and power of the multipath signal. The time delay profile is calculated using the formula h(τ) = ∑α i δ(τ-τ i ), where α i Let τ be the complex amplitude of the i-th path. i To account for the time delay, the system corrects the measurement results based on the calculated meteorological influence factors, using the correction formula τ'. i =τ i ×[1+β(N-N0)], where β is the correction coefficient, N is the current atmospheric refractive index, and N0 is the standard atmospheric refractive index. After processing, the delay spread parameters, coherence bandwidth parameters, and time-varying characteristic parameters of 24 sub-bands are obtained, forming complete channel delay characteristic data. Based on the spectrum occupancy status data, meteorological influence factors, and channel delay characteristic data, a comprehensive evaluation model for band availability is constructed. The evaluation model adopts a weighted scoring mechanism, and the calculation formula is A(f)=w1×(1-O(f))+w2×(1-I(f))+w3×(1-D(f)), where O(f) is the occupancy rate of band f (0-1), I(f) is the normalized value of meteorological influence (0-1), D(f) is the normalized value of delay spread (0-1), and w1, w2, and w3 are weighting coefficients, satisfying w1+w2+w3=1. The weighting coefficients are dynamically adjusted according to the type of communication service: w1 = 0.5, w2 = 0.3, w3 = 0.2 for voice communication; and w1 = 0.4, w2 = 0.2, w3 = 0.4 for data communication. The system sorts the 24 sub-frequency bands according to their availability scores from highest to lowest, setting a threshold of 0.6. Bands above the threshold are marked as "available," and those below are marked as "unavailable." The evaluation results are organized into a three-dimensional matrix, with dimensions of frequency band index, spatial orientation, and timestamp, forming complete maritime communication channel status data.

[0068] As an example of the present invention, reference is made to Figure 2 As shown, Figure 1 A detailed flowchart illustrating the implementation steps of step S2 is provided. In this example, step S2 includes:

[0069] Step S21: Obtain the geographical location data of each vessel using the BeiDou-3 navigation equipment;

[0070] Step S22: Measure the heading and speed information of each vessel using the shipborne inertial navigation system, and share the information via broadcast among the vessels to generate motion status data for each vessel.

[0071] Step S23: Based on the geographical location data of each vessel, the vessels are used as communication nodes, and a relative coordinate system of the formation is established according to the motion status data of each vessel to obtain the position data of the formation nodes;

[0072] Step S24: Analyze the relative distances and relative azimuths between ships based on the formation node position data to generate ship relative situation data;

[0073] Step S25: Based on the relative situation data of ships and the status data of sea communication channels, perform link spatial isolation analysis to generate cross-link spatial communication potential data.

[0074] In this embodiment of the invention, real-time geographic location data is acquired through an integrated BeiDou-3 multi-mode navigation receiver. The receiver adopts a 72-channel parallel receiving architecture, simultaneously receiving BeiDou B1I / B1C / B2a / B3I signals, with a receiving sensitivity of -130dBm. The receiver outputs positioning data once per second, with the data format conforming to the BeiDou B code standard, including longitude (positive for east, negative for west, accurate to 6 decimal places, approximately 0.1 meters), latitude (positive for north, negative for south, accurate to 6 decimal places), altitude (relative to sea level, in meters), positioning accuracy factor (GDOP value), number of satellites (currently participating in positioning), and positioning status code (0 - invalid, 1 - single-point positioning, 2 - differential positioning, 4 - fixed solution, 5 - floating-point solution). The data is transmitted to the ship's communication main control unit via an RS422 serial interface at a baud rate of 115200, encapsulated using the NMEA-0183 protocol format, and data integrity is ensured through a checksum mechanism. Integrated three-axis fiber optic gyroscope inertial navigation module, with gyroscope drift rate less than 0.01° / hour and accelerometer accuracy better than 10. -5g. The inertial system fuses BeiDou positioning data using a Kalman filter algorithm to calculate in real time the vessel's heading (angle relative to true north, clockwise is positive, accuracy 0.1°), pitch angle (upward is positive, accuracy 0.1°), roll angle (starboard is positive, accuracy 0.1°), and three-dimensional velocity vector (eastward, northward, and vertical components, in meters per second, accuracy 0.05 meters per second). The measurement frequency is 10Hz, generating a complete data set every 100 milliseconds. All vessels broadcast data via shortwave ad hoc radio at 5-second intervals, using a TDMA time slot allocation mechanism to avoid data conflicts, with each vessel occupying a 50-millisecond time slot. The data includes the vessel identification code, timestamp, position, attitude angle, and velocity vector, and forward error correction coding is used to improve transmission reliability. After time synchronization processing, the received multi-vessel data forms a state dataset containing the motion parameters of all participating vessels. The designated formation command ship is used as the coordinate origin, and its WGS-84 coordinates (longitude λ1, latitude λ1) obtained from BeiDou positioning are used. Let be the reference point. A transformation from the geocentric Earth-fixed coordinate system to the local northeast-sky coordinate system is used to convert the geographical locations of each ship into relative rectangular coordinates. The transformation formula is: Where R is the Earth's radius (6,378,137 meters), h is the ship's altitude, and h1 is the ship's altitude at the origin. Then, a coordinate rotation is performed so that the X-axis points to the heading of the command ship. The transformation matrix is ​​[cos(θ), -sin(θ), 0; sin(θ), cos(θ), 0; 0, 0, 1], where θ is the command ship's heading angle. The system assigns the transformed coordinates to each ship communication node, constructing a formation node position data table containing node identifiers, relative coordinates, and relative speeds, with a data update frequency of 1 Hz. For n ships in the formation, the system constructs an n×n matrix to record the relative parameters between ships. The relative distance is calculated using the three-dimensional Euclidean distance formula: Where (x_i, y_i, z_i) represents the position of the i-th ship in the formation coordinate system. The relative azimuth calculation includes the horizontal azimuth α(i, j) = arctan2(y_j - y_i, x_j - x_i) and the pitch angle β(i, j) = arcsin((z_j - z_i) / d(i, j)). The azimuth is based on the ship's bow, positive for starboard and negative for port, ranging ±180°; the pitch angle is positive upwards and negative downwards, ranging ±90°. The system calculates the relative velocity vector v(i, j) = (v_j - v_i) and predicts the relative position change within 5 minutes. All calculation results are organized into a ship relative situation data structure, including a distance matrix, azimuth matrix, relative velocity matrix, and predicted position matrix. Spatial isolation analysis is performed on each communication link. The system establishes a radio frequency propagation model. For shortwave, a CCIR ground wave and sky wave composite model is used; for VHF, a dual-path fading model is used; and for microwave, a free-space propagation model is used. For each pair of ship nodes, the system calculates the spatial isolation K(i,j,f) = L(i,j,f) - G_t - G_r + I(f) in different frequency bands, where L is the path loss (dB), G_t is the transmit antenna gain (dBi), G_r is the receive antenna gain (dBi), and I is the interference level (dBm). The spatial isolation threshold is 85dB; values ​​above this are marked as "good isolation," values ​​between 75-85dB are marked as "moderate isolation," and values ​​below 75dB are marked as "weak isolation." The system constructs a three-dimensional link potential matrix. Each cell contains the ship pair number, frequency band number, link type, spatial isolation, estimated communication capacity (bits / s), and stability score. This matrix constitutes cross-link spatial communication potential data.

[0075] Preferably, the link spatial isolation analysis based on ship relative situation data and maritime communication channel status data includes:

[0076] The physical distances between nodes are calculated based on the relative ship situation data to obtain the node distance matrix;

[0077] Based on the node distance matrix, the interference coupling degree data is obtained by analyzing the channel interference overlap between nodes using marine communication channel status data.

[0078] The directional isolation parameters are obtained by calculating the directional angle difference of the ship's antenna based on the interference coupling data.

[0079] Based on the node distance matrix and directional isolation parameters, two ships with a distance greater than 5 nautical miles or a difference in azimuth greater than 60 degrees are marked as spatially sufficiently isolated node pairs; two ships with a distance less than 5 nautical miles and a difference in azimuth less than 60 degrees are marked as spatially insufficiently isolated node pairs.

[0080] Link independence is marked for spatially sufficiently isolated node pairs, and node spatial integration is performed on spatially insufficiently isolated node pairs to generate cross-chain spatial communication potential data.

[0081] In this embodiment of the invention, the three-dimensional coordinate data (x, y, z) of each ship are extracted from the ship relative situation database, where x represents the east-west displacement, y represents the north-south displacement, and z represents the vertical displacement, in meters. For n ships in a formation, an n×n symmetric matrix D is constructed, where the matrix element d_ij represents the distance between ship i and ship j. The distance is calculated using the Havesing formula: Where r is the Earth's radius, 6371000 meters. and Let λ_i and λ_j be the latitudes (in radians) of ships i and j, respectively, and λ_i and λ_j be the longitudes (in radians) of ships i and j, respectively. The calculation results are automatically converted to nautical miles (1 nautical mile = 1852 meters) and stored in the distance matrix, accurate to two decimal places. The system updates the distance matrix every 5 seconds to ensure real-time data accuracy. The node distance matrix is ​​combined with the maritime communication channel status data to calculate the interference coupling degree between the communication systems of each ship. The system divides the 0.5-3000MHz spectrum into 24 sub-bands, and calculates the spectral overlap coefficient for each sub-band. Where P_i(f) and P_j(f) are the transmit power spectral densities of ships i and j at frequency f, respectively. The interference power calculation formula is I(i,j,f)=P_t(j,f)-L(d_ij,f)+G_t(j,f)+G_r(i,f), where P_t is the transmit power, L is the path loss (including free space loss, atmospheric absorption, and scattering loss), and G_t and G_r are the transmit and receive antenna gains, respectively. The system constructs a three-dimensional interference coupling matrix C, where the element c_ijf represents the interference coupling degree between ships i and j in frequency band f, with a value range of 0 to 1, where 0 represents no interference and 1 represents complete interference. Based on the heading data and antenna installation position parameters of each ship, the antenna azimuth angle difference between ships is calculated. First, the heading angle H_i of each ship (the angle relative to true north, clockwise is positive, 0-359.9 degrees) is extracted from the ship attitude data. For ships i and j, the relative azimuth difference ΔA_ij = min(|H_i - H_j|, 360 - |H_i - H_j|). The antenna directivity gain difference is calculated as ΔG_ij(θ) = |G_i(θ_i) - G_j(θ_j)|, where G_i(θ_i) represents the antenna gain of ship i in direction θ_i, and θ_i is the angle between the main lobe of ship i's antenna and the line connecting ship j. The directivity isolation parameter D_ij is calculated as D_ij = α × ΔA_ij + β × ΔG_ij, where α and β are weighting coefficients, obtained through regression analysis of measured data: α = 0.7 and β = 0.3. The system generates an n × n directivity isolation parameter matrix, with matrix elements being standardized values ​​from 0 to 100. Node pairs are classified and labeled according to the following criteria: when the distance d_ij between the two ships is greater than 5 nautical miles (i.e., 9260 meters) or the azimuth difference ΔA_ij is greater than 60 degrees, the node pair is labeled as a "spatially sufficiently isolated node pair" with a label code of 1; when the distance d_ij between the two ships is less than or equal to 5 nautical miles and the azimuth difference ΔA_ij is less than or equal to 60 degrees, the node pair is labeled as a "spatially insufficiently isolated node pair" with a label code of 0. The labeling operation is implemented through a high-speed comparator circuit, and the comparison result is stored in a Boolean two-dimensional matrix S with a dimension of n×n. The element s_ij represents the spatial isolation state of ships i and j. The labeling result is also appended with a timestamp to record the generation time, which is convenient for subsequent tracking of the dynamic changes in the spatial relationship of node pairs. The system calculates a spatial isolation stability index for each node pair, representing the probability of maintaining the current isolation state within the next 30 minutes. The calculation is based on the relative velocity vector of the two ships and the current distance. Link independence labels are assigned to all spatially sufficiently isolated node pairs (i.e., node pairs with s_ij = 1 in matrix S). During the labeling process, the system constructs a link independence matrix L, where the element l_ijf represents the link independence between ships i and j in frequency band f, and takes a value of 0 or 1. When the interference coupling degree c_ijf is less than 0.15, l_ijf is set to 1, indicating link independence; otherwise, it is set to 0, indicating link non-independence.For spatially insufficiently isolated node pairs (i.e., node pairs where s_ij = 0 in the S matrix), the system performs node spatial integration, organizing these nodes into communication groups G_k. Nodes within a group share communication resources, and time-division multiplexing or frequency-division multiplexing is used to avoid interference. Group partitioning employs the maximum clique partitioning algorithm from graph theory, grouping nodes with severe interference into the same group. The system ultimately generates a cross-link spatial communication potential data structure, including node identifier, isolation status, link independence, group affiliation, link capacity estimate (bits / second), and quality score, with the data indexed by ship identification code.

[0082] Preferably, step S3 includes the following steps:

[0083] Step S31: Identify a list of potentially available communication links based on cross-chain space communication potential data and marine communication channel status data;

[0084] Step S32: Perform resource reuse assessment based on the list of potentially available communication links to obtain feasible spatial reuse link pairs;

[0085] Step S33: Divide feasible link communication clusters according to the feasible links for spatial multiplexing;

[0086] Step S34: Establish time-division multiplexing mechanisms within each communication cluster based on feasible link communication clusters, and construct a multi-link self-organizing network topology.

[0087] In this embodiment of the invention, multi-channel monitoring equipment is used to acquire cross-link space communication potential data, including the transmit power, antenna gain, spatial path loss, and interference level of each link. Simultaneously, distributed marine sensing nodes collect real-time marine communication channel status data, recording influencing factors such as wave height, seawater temperature and salinity distribution, meteorological conditions, and electromagnetic environment. Subsequently, a link prediction model is applied to calculate the signal-to-noise ratio (SNR) of each link: SNR = Transmit Power × Transmit Antenna Gain × Receive Antenna Gain ÷ (Path Loss × Noise Power Density × Bandwidth). When the SNR exceeds a preset threshold (typically 10 dB), and the link's sustained stable time is expected to exceed the communication task duration, the link is marked as a potentially usable communication link and added to the link list. After obtaining the list of potentially usable communication links, a resource reuse assessment is performed. For each pair of links A and B in the list, a spatial isolation index is calculated: Spatial Isolation = |Azimuth Difference| + |Elevation Difference| × Weighting Factor. The azimuth difference represents the angle between the two links on the horizontal plane, the elevation difference represents the angle on the vertical plane, and the weighting factor is set to 1.5. When the spatial isolation is greater than a preset threshold (set at 45 degrees), link pair AB is considered to have spatial reuse feasibility. Furthermore, the mutual interference coefficient of the link pair is calculated: Mutual interference coefficient = Transmitter power density × Antenna sidelobe gain × Attenuation coefficient. When the mutual interference coefficient is below -90 dB / mW, the link pair is confirmed as a spatially reuseable link pair and recorded in the spatial reuse link pair matrix. Based on the spatial reuse feasible link pair matrix, an undirected graph structure is constructed, with each communication link as a node in the graph, and spatial reuse feasibility as the connection relationship between nodes. A graph coloring algorithm is used for communication cluster partitioning: First, a color set is defined, and the initial link is assigned color 1. The remaining links are traversed; if there is no spatial reuse feasibility relationship with an already colored link, it is assigned the same color; otherwise, a new color is assigned. In the specific implementation, the reusability relationship between links is represented by an adjacency matrix, where a matrix element value of 1 indicates that two links can be spatially reused, and a value of 0 indicates that they cannot be reused. All links with the same color are grouped into one communication cluster, resulting in multiple sets of non-interfering communication clusters. Links within each communication cluster cannot communicate simultaneously. For each communication cluster, an improved time slot allocation algorithm is applied to establish a time-division multiplexing mechanism: the communication period T (usually set to 100 milliseconds) is divided into n time slots (n is the number of links within the cluster), and time slots are allocated to each link by solving an optimization problem. The optimization objective function is to maximize ∑(bandwidth i × time slot length i × link weight i), where bandwidth i is the effective bandwidth of link i, time slot length i is the time allocated to link i, and link weight i is set according to service priority (range 1-10). The optimization constraints are that the sum of all time slots does not exceed T, no two time slots overlap, and there is a 5-millisecond guard interval. Based on the allocation results, a time slot allocation table is generated and broadcast to the nodes within the cluster through the control channel to achieve coordinated operation of the links within the cluster, thereby constructing a complete multi-link self-organizing network topology.

[0088] Preferably, step S4, which involves allocating communication links for task adaptation based on a multi-link ad hoc network topology, includes:

[0089] Receive specific communication task requests from upper-layer applications or operators, and extract the required data rate, maximum allowable latency, and minimum reliability requirements to obtain the current communication task requirements;

[0090] The current communication task requirements are classified and prioritized to obtain a service priority list;

[0091] Based on the aforementioned business priority list and cross-chain spatial communication potential data, the redundancy of time slot resources is adjusted to obtain the formation time slot configuration data.

[0092] Based on the multi-link self-organizing network topology, the task source transmission nodes of the service priority list are determined, and potential transmission paths are identified to obtain the full topology transmission paths.

[0093] Based on the full topology transmission path, calculate the estimated number of time slots required for each communication node to complete data transmission within its respective communication cluster, and obtain the node time slot requirement.

[0094] Based on the node time slot demand, task adaptation communication link allocation is performed on the full topology transmission path to generate multi-link communication task adaptation data.

[0095] In this embodiment of the invention, communication task requests input by upper-layer applications or operators are received through the task request interface of the ship's communication control center. The task requests are transmitted in a standardized data packet format, including a task type identifier (1-video transmission, 2-command and control, 3-intelligence interaction, 4-routine communication), a target node identifier, and data size (unit: kilobytes). The control center extracts specific parameters for different task types using a preset task type parameter mapping table: video transmission requires a data rate of no less than 2 megabits per second, a maximum allowable latency of 200 milliseconds, and a reliability of 99.5%; command and control requires a data rate of no less than 512 kilobits per second, a maximum allowable latency of 50 milliseconds, and a reliability of 99.9%; intelligence interaction requires a data rate of no less than 1 megabit per second, a maximum allowable latency of 100 milliseconds, and a reliability of 99.8%; routine communication requires a data rate of no less than 256 kilobits per second, a maximum allowable latency of 500 milliseconds, and a reliability of 99%. The extracted results form the current communication task requirement data structure. Based on the current communication task requirement data structure, a multi-factor weighted scoring method is used for grading and prioritization. The scoring formula is: Priority Score = 0.4 × Data Rate Score + 0.3 × Latency Sensitivity Score + 0.3 × Reliability Requirement Score. Data Rate Score = Actual Required Data Rate ÷ Maximum Baseline Data Rate (10 Mbps) × 100; Latency Sensitivity Score = (1000 - Actual Allowable Latency) ÷ 1000 × 100; Reliability Requirement Score = (Actual Reliability Requirement - 95) ÷ 5 × 100. An additional 20 points are added for tasks involving command and control; an additional 30 points are added for tasks marked as urgent. Tasks are divided into four priorities based on the final score: 90 points and above is the highest priority (Level 1), 75-90 points is high priority (Level 2), 60-75 points is medium priority (Level 3), and below 60 points is ordinary priority (Level 4). A business priority list is generated by sorting priorities from highest to lowest. Time slot resource redundancy is adjusted based on the business priority list and cross-chain spatial communication potential data. First, the basic time slot configuration for each priority task is calculated: The unit time slot length is 10 milliseconds, and the link rate is obtained from cross-link spatial communication potential data. Then, redundancy coefficients are set according to priority: 2.0 for level 1 tasks, 1.5 for level 2 tasks, 1.2 for level 3 tasks, and 1.0 for level 4 tasks. For areas with severe sea conditions (wave height exceeding 4 meters or wind force greater than 7), an additional redundancy coefficient of 0.5 is added. The actual number of allocated time slots = base number of time slots × redundancy coefficient. Subsequently, an improved backtracking algorithm is used to solve the time slot sorting problem, ensuring that high-priority tasks are allocated consecutive time slots first, while low-priority tasks are allocated discontinuous time slots if resources permit, generating a formation time slot configuration data matrix. Based on the multi-link self-organizing network topology, the task source transmission nodes for the service priority list are determined. A greedy heuristic algorithm is used to select the node with the highest degree centrality from the topology graph as the source transmission node for each communication task. The degree centrality calculation formula is: CD(v) = d(v) ÷ (N-1), where d(v) represents the connectivity of node v, and N represents the total number of nodes. Subsequently, an improved Dijkstra algorithm is used to identify potential transmission paths from the source node to the target node. The path weight calculation formula is: W(p) = ∑(α × link load rate + β × link delay + γ × link error rate), where α = 0.4, β = 0.3, and γ = 0.3. For priority services of level 1 and level 2, additional backup paths are calculated, and the suboptimal path with a path separation degree greater than 70% is used as a backup. The algorithm calculates at least 3 different transmission paths for each task (when the network topology supports it), arranged in ascending order of path weight, forming a full topology transmission path table. Each transmission path is segmented to identify the links in which each node participates within its respective communication cluster. Next, the amount of data transmitted for each link is calculated: data amount = original task data amount × (1 + protocol overhead rate), where the protocol overhead rate is set according to the type of protocol used (usually 0.1-0.3). Then, the estimated number of time slots required to complete data transmission for each node is calculated: Node time slot requirement = ∑(Link data transmission volume ÷ Link effective transmission rate ÷ Time slot length), where the effective transmission rate considers real-time link state correction: Effective rate = Nominal rate × (1 - Link congestion) × (1 - Link bit error rate). For nodes participating in transmission along multiple paths, the final time slot requirement is determined using the maximum value principle, generating a node time slot requirement table containing information such as node identifier, communication cluster, and total time slot requirement. A mixed-integer linear programming method is used to establish an optimization model, with the objective function being: minimizing ∑(Task completion time × Task priority weight), where the task completion time is the longest link transmission time from the source node to the target node, and the task priority weight is 4 - priority value. Constraints include: the total number of time slots allocated to any node does not exceed the communication cycle, each task ensures that the end-to-end delay meets the requirements, and the transmission path must be connected. The branch and bound algorithm is used to solve the optimization problem, obtaining the specific time slot allocation scheme for each task on each link.For Level 1 tasks, a dual-path transmission strategy is implemented, with resources allocated on both the primary and backup paths. For Levels 2-4 tasks, a single optimal path is dynamically selected based on network load. The final result is multi-link communication task adaptation data, including task identifier, priority, path information, and complete configuration information for the node timeslot allocation table.

[0096] Preferably, step S4 involves performing multi-link parallel transmission based on multi-link communication task adaptation data to construct a multi-link fusion transmission strategy, including:

[0097] By using link quality rating data to perform real-time channel quality analysis on the target communication link of the multi-link communication task adaptation data, an instant channel snapshot of the target link is generated; the instant channel snapshot of the target link includes high-quality links, medium-quality links, and low-quality links.

[0098] Link weighted stability assessment is performed based on real-time channel snapshots of the target link to generate a channel stability index. Based on the channel stability index and link quality rating data, stable link modulation configuration is performed to generate multi-link modulation configuration data. Among them, high-quality links use 64QAM modulation with a coding rate of 5 / 6; medium-quality links use 16QAM modulation with a coding rate of 3 / 4; and low-quality links use QPSK modulation with a coding rate of 1 / 2.

[0099] Link subcarrier allocation is performed based on multi-link modulation configuration data to generate link subcarrier allocation data.

[0100] The adaptive frequency hopping sequence is obtained by adjusting the frequency hopping point of the multi-link communication task adaptation data through the link subcarrier allocation data.

[0101] Multi-link parallel transmission is implemented based on adaptive frequency hopping sequences to construct a multi-link fusion transmission strategy.

[0102] In this embodiment of the invention, real-time link quality rating data, including signal-to-noise ratio (SNR), bit error rate (BER), carrier-to-noise ratio (CNR), Doppler frequency shift, and channel coherence time, is collected through a distributed channel monitoring module of the ship communication system. For each target communication link in the multi-link communication task adaptation data, a comprehensive channel quality score is calculated: Q = 0.4 × SNR / SNR reference + 0.3 × (1 - BER / BER reference) + 0.2 × CNR / CNR reference + 0.1 × coherence time / coherence time reference, where the reference values ​​are set as SNR reference = 25 dB, BER reference = 10^-5, CNR reference = 15 dB, and coherence time reference = 100 ms. Based on the score results, the links are divided into three categories: Q ≥ 0.8 for high-quality links, 0.5 ≤ Q < 0.8 for medium-quality links, and Q < 0.5 for low-quality links. Real-time measurement data is received through a three-dimensional polarized antenna array and, after calculation by a digital signal processing unit, forms an instantaneous channel snapshot of the target link. Calculate the parameter volatility index for each link over the past 10 sampling periods: Δ = standard deviation / mean × 100%, obtaining ΔSNR, ΔBER, and ΔCNR respectively. Then, calculate the channel stability index: S = 0.5 × (1 - ΔSNR) + 0.3 × (1 - ΔBER) + 0.2 × (1 - ΔCNR), where S ranges from 0 to 1, with a larger value indicating a more stable link. Combine S with the link quality rating Q to form a weighted score W = 0.6 × Q + 0.4 × S. Based on the W value, the link modulation scheme is configured as follows: high-quality links with W ≥ 0.75 use 64-QAM (64 Quadrature Amplitude Modulation), with a forward error correction coding rate of 5 / 6 and a spectral efficiency of 5 bits / Hz per unit bandwidth; medium-quality links with W ≤ 0.5 and W < 0.75 use 16-QAM (16 Quadrature Amplitude Modulation), with a coding rate of 3 / 4 and a spectral efficiency of 3 bits / Hz; low-quality links with W < 0.5 use Quadrature Phase Shift Keying (QPSK), with a coding rate of 1 / 2 and a spectral efficiency of 1 bit / Hz. The modulation configuration data is broadcast to all communication nodes via the control channel. The total bandwidth is divided into 128 equal-width subcarriers, numbered from 0 to 127. The subcarrier allocation algorithm employs an improved greedy search method, allocating a differentiated number of subcarriers based on different link quality levels: 40% of subcarrier resources (subcarriers 0-51) are allocated to high-quality links, 35% (subcarriers 52-96) to medium-quality links, and 25% (subcarriers 97-127) to low-quality links. Within each quality level, the subcarriers are further subdivided based on the carrier signal-to-noise ratio measurement result C(i), and the potential carrying capacity of each subcarrier is calculated using the formula P(i) = log2(1+C(i)).Then, the water filling algorithm is used to allocate the transmission power: P_total = ∑P(i), which satisfies the constraint condition of ∑P(i) ≤ P_max, where P_max is the maximum allowable transmission power (usually 20 watts). Finally, a link subcarrier allocation data table is generated, which contains information such as subcarrier number, center frequency, bandwidth, modulation mode, coding rate, power configuration, etc. A frequency interference map is constructed. By using a frequency scanning receiver, the background noise and interference distribution are measured in three frequency bands of 2 - 30 MHz, 118 - 174 MHz, and 420 - 512 MHz to form a frequency - interference intensity matrix I(f). Then, a frequency hopping sequence generation algorithm is designed: Use the Mersenne prime number p = 2^n - 1 (n = 7, 11, 13) as the frequency hopping point interval, and construct a maximum length sequence through the generating polynomial g(x) = x^n + x^m + 1 (where m < n and m, n are relatively prime) to generate a pseudo - random code. The sequence is screened according to the real - time interference map, and the frequency points with I(f) > - 85 dBm are removed. For high - quality links, a frequency hopping rate of 500 hops per second is adopted; for medium - quality links, a frequency hopping rate of 300 hops per second is adopted; for low - quality links, a frequency hopping rate of 150 hops per second is adopted. Finally, an adaptive frequency hopping sequence matrix is formed, which contains information such as frequency hopping time, frequency point, dwell time, link number, etc., and is distributed to all nodes in the communication network synchronously through a pre - agreed control channel. The data to be transmitted is divided into blocks, and the size of each block is set to 1024 bytes. Fountain code encoding is implemented through the forward error correction layer, using the Rapid Luby Transform code (Raptor code), and the redundancy rate is set to 1.2 times the original data. Subsequently, a multi - path packet scheduling algorithm is adopted: For high - priority services (levels 1 - 2), they are simultaneously allocated to high, medium, and low - class links for parallel transmission, and the data allocation ratio is 5:3:2; for medium - priority services (level 3), they are allocated to high - and medium - quality links, with a ratio of 6:4; for low - priority services (level 4), they are only allocated to low - quality links. The data on each link is secondarily encoded and protected by the Reed - Solomon code (255, 223). The transmission controller strictly switches the carrier frequency according to the adaptive frequency hopping sequence and achieves time synchronization accurate to the microsecond level at the MAC layer. The receiving end uses the maximum ratio combining technology to selectively combine the multi - link received data, and restores the original information through Turbo decoding to achieve efficient multi - link fusion transmission.

[0103] Particularly importantly, before the real - time communication link security switching management, it also includes:

[0104] Obtain key transmission data; perform redundant transmission configuration according to the multi - link fusion transmission strategy, and adjust the bandwidth allocation to obtain a link security switching sequence;

[0105] Construct the ship network connectivity relationship according to the link security switching sequence to obtain a full - network connectivity model;

[0106] The communication efficiency parameters between nodes are calculated based on the overall network connectivity model, and the node communication weight coefficients are obtained.

[0107] Obtain physical distance data between ships; perform routing strategy selection based on node communication weight coefficients and physical distance data between ships to obtain a multi-path routing table;

[0108] The load balancing configuration is obtained by monitoring node load and performing load balancing control based on the multi-path routing table.

[0109] Based on load balancing configuration, different types of data are prioritized and processed to obtain a data priority strategy.

[0110] In this embodiment of the invention, key transmission data, including command and control data, situational awareness data, equipment status data, and daily operational data, are acquired through the data acquisition module of the ship's multi-link fused communication system. A data classification algorithm is used to divide the data into four levels according to importance: Level I (command and control), Level II (situational awareness), Level III (equipment status), and Level IV (daily operational data). Subsequently, differentiated redundant transmission configurations are implemented according to the multi-link fused transmission strategy: Level I data uses a triple redundancy transmission mechanism, encoded with Hamming code (72, 64); Level II data uses double redundancy transmission, encoded with BCH (127, 106); Level III data uses 1.5 times redundancy transmission, encoded with convolutional code (2, 1, 7); and Level IV data uses single transmission, protected by checksums. Bandwidth allocation uses a weighted proportional algorithm: the proportion of each level of data is I:II:III:IV = 4:3:2:1, calculated using the formula Bi = B × Wi / ∑Wj, where Bi is the bandwidth allocated to Level I data, B is the total bandwidth, and Wi is the weight. Finally, a link security switching sequence list is generated, containing transmission link assignments, redundancy strategies, switching conditions, and priority markers for each data type. Each ship node sends a probe frame containing its own identifier, communication capability parameters, and location information through a preset probe channel. The probe frame uses low-complexity BPSK modulation to ensure transmission reliability. Nodes receiving probe responses establish an initial connectivity table, recording the set of directly reachable nodes. Next, an improved link-state protocol is used to achieve multi-hop connectivity discovery: each node broadcasts its own connectivity table, and receiving nodes update their local topology information. This process is repeated three times to form two-hop and three-hop connectivity relationships. A connectivity graph G = (V, E) is constructed using matrix representation, where the vertex set V represents ship nodes, the edge set E represents direct communication links, and the matrix element gij takes a value of 1 to indicate that nodes i and j are directly connected, and a value of 0 indicates that they are not connected. Finally, a depth-first search algorithm is used to calculate strongly connected components and identify network cut points and bridges, generating a complete network connectivity model, including the complete network topology, link characteristics, and key node identifiers. A multi-round measurement method was used to collect link performance metrics: the link transmission delay τij, throughput θij, and packet loss rate λij were measured by sending standard test data packets (1024 bytes in length). For each pair of nodes (i, j), the comprehensive communication efficiency index was calculated: Eij=α×(θij / θmax)×(1-λij) / (1+τij / τ0), where α is the normalization coefficient, θmax is the theoretical maximum throughput, and τ0 is the baseline delay (set to 10 milliseconds). Next, the node centrality index was calculated: Ci=∑jEij / ∑j∑kEjk, representing the relative importance of node i in the network. Then, a communication probability model was established based on a Markov process, and the k-step transition probability matrix Pk between nodes was calculated.Based on the above indicators, the node communication weight coefficient is generated as follows: Wi = 0.5 × Ci + 0.3 × Pi + 0.2 × Bi, where Pi is the node's communication participation rate and Bi is the node's remaining bandwidth ratio. The weight coefficient ranges from 0 to 1, with a larger value indicating stronger node communication capabilities. Physical distance data between ships is obtained using the ship's autonomous navigation equipment. Each ship obtains its precise position coordinates (longitude λi, latitude) via a BeiDou / GPS dual-mode receiver. The system broadcasts its position information via a secure communication channel. It calculates the actual distance between ships using the great circle distance formula. Where R is the Earth's radius (6371 km). An improved link-state routing strategy is implemented, incorporating node communication weight coefficients: the path cost function C(p) = ∑(dij / Wi×Wj), where the cost of each link (i, j) in path p is the physical distance divided by the product of the weights of the two endpoints. An improved Dijkstra algorithm is used to calculate the k shortest paths (k=3) between all node pairs, forming an initial routing table. Then, a path separation evaluation algorithm is used to filter highly independent paths: separation S(p1, p2) = 1 - |E(p1)∩E(p2)| / |E(p1)∪E(p2)|, retaining only path pairs with a separation greater than 0.7. Finally, a multi-path routing table is formed, containing primary paths, backup paths, and emergency paths. Node load monitoring and balancing control are implemented based on the multi-path routing table. Each node periodically (every 5 seconds) reports load status information, including processor utilization, memory usage, queue length, throughput, and packet loss rate. The load aggregation metric is calculated as follows: L = 0.2 × processor utilization + 0.2 × memory utilization + 0.3 × queue length / queue capacity + 0.3 × (current throughput / maximum throughput). Based on the load metric L, nodes are divided into three categories: L < 0.5 (low load), 0.5 ≤ L < 0.8 (medium load), and L ≥ 0.8 (high load). A load balancing threshold control algorithm is used: when a node load L ≥ 0.8, a traffic splitting mechanism is triggered, redirecting 50% of new traffic to backup paths via route updates; when a node load L ≥ 0.9, an overload protection mechanism is triggered, blocking non-critical business traffic and redirecting all new traffic. A weighted round-robin method is used to distribute traffic to multiple paths, with the weight inversely proportional to the path cost: Wi = 1 / C(pi) / ∑(1 / C(pj)). Finally, a load balancing configuration table is generated, containing the node's current load, traffic allocation ratio, and load balancing trigger conditions. A data type classification table is established, containing business type identifiers, priority base values, and latency sensitivity. A multi-factor comprehensive evaluation method is used to calculate the real-time priority of data packets: P = Pb + f(T) + g(S) + h(L), where Pb is the basic priority (1-10); f(T) is the delay function, f(T) = α × (Tdeadline - Tcurrent) / Tdeadline, increasing priority when the deadline Tdeadline is approaching; g(S) is the data size function, g(S) = -β × S / Smax, giving priority to smaller data packets; h(L) is the load function, h(L) = γ × L, appropriately reducing the priority of non-critical data when network congestion occurs. Coefficients α = 2, β = 1, γ = -3. Data priority queue management is implemented: a four-level priority queue is set up at each forwarding node, employing a hybrid mechanism of strict priority scheduling and weighted fair queues.Level I (Emergency Command) data packets are placed in the highest-priority queue and are preferentially transmitted unconditionally; Level II (Tactical Situation) data packets are allocated 50% of the total bandwidth; Level III (Status Monitoring) data packets are allocated 30%; Level IV (Daily Operations) data packets are allocated 20%. Finally, a data priority policy configuration is generated, including queue allocation, bandwidth guarantee, and preemption mechanism settings for various types of data. A distributed link status monitoring mechanism is deployed, and monitoring probes are arranged at each communication node to collect link quality indicators: signal-to-noise ratio SNR, bit error rate BER, packet loss rate PLR, and round-trip delay RTT. Define the link health score: H = 0.3×(SNR / SNRth)+0.3×(1 - BER / BERth)+0.2×(1 - PLR / PLRth)+0.2×(RTTth / RTT), where the respective thresholds are SNRth = 10dB, BERth = 10^-4, PLRth = 10^-2, and RTTth = 200ms. Set the secure switching threshold Hth = 0.6, and trigger a link switching warning when H < Hth. Adopt a proactive switching decision algorithm: predict the link degradation time based on the change trend of the link health ΔH / Δt, and initiate switching preparation 10 seconds before the actual interruption. The switching process adopts a seamless connection mechanism: keep the original link in an active state, and at the same time establish a connection on the backup link, and perform data flow migration after verifying the availability of the backup link. Adopt a hot switching strategy for Level I and II data, and transmit simultaneously on multiple links; adopt a cold switching strategy for Level III and IV data, and only enable the backup link when the primary link fails. Record the switching event log, including the switching trigger conditions, timestamp, and performance comparison before and after switching.

[0111] This invention, through real-time capture of navigation information broadcast by surrounding vessels and multi-link channel quality classification, combined with frequency band availability assessment using marine meteorological and hydrological data, can accurately identify the channel quality of each communication link under the current environment and dynamically select and switch between high, medium, and low quality links. Simultaneously, based on an adaptive modulation and frequency hopping strategy using a link stability index, the system can maintain high link availability and low bit error rate under complex sea conditions such as Doppler shift, multipath fading, and weather changes, significantly improving communication reliability and anti-interference capabilities. Combined with real-time channel snapshots and stability assessments, it can automatically activate backup links and seamlessly switch data streams when any link experiences performance degradation or interruption, avoiding packet loss and retransmission overhead. Through subcarrier differential allocation and adaptive frequency hopping sequences, it ensures the smoothness and controllable delay of the switching process, achieving truly "seamless" communication switching. Based on the relative position of vessels, spatial isolation, and channel status, it intelligently divides reusable link clusters and constructs a multi-link self-organizing network topology. This topology combines spatial and time-slot multiplexing. Through improved graph coloring and time-slot allocation algorithms, it not only achieves non-interference between links but also maximizes the utilization of spectrum resources, significantly increasing the number of links that can be transmitted in parallel within the same time slot, thereby significantly improving the overall network throughput.

[0112] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0113] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A marine multi-link converged communication method, characterized in that, Includes the following steps: Step S1: Receive navigation information broadcast by other vessels within a preset range to obtain dynamic information of surrounding vessels; Based on the dynamic information of surrounding vessels, the communication link quality level is classified to obtain link quality rating data; Obtain current marine meteorological and hydrological data; Based on current marine meteorological and hydrological data and link quality rating data, the availability of communication frequency bands for surrounding vessels is assessed, and marine communication channel status data is generated. Step S2: Use BeiDou-3 navigation equipment to obtain the geographical location data of each vessel; Based on the geographical location data of each vessel and the status data of the sea area communication channels, a potential analysis of space communication links is conducted to generate cross-link space communication potential data; wherein, step S2 specifically includes: Step S21: Obtain the geographical location data of each vessel using the BeiDou-3 navigation equipment; Step S22: Measure the heading and speed information of each vessel using the shipborne inertial navigation system, and share the information via broadcast among the vessels to generate motion status data for each vessel. Step S23: Based on the geographical location data of each vessel, the vessels are used as communication nodes, and a relative coordinate system of the formation is established according to the motion status data of each vessel to obtain the position data of the formation nodes; Step S24: Analyze the relative distances and relative azimuths between ships based on the formation node position data to generate ship relative situation data; Step S25: Perform link spatial isolation analysis based on ship relative situation data and maritime communication channel status data to generate cross-link spatial communication potential data; specifically, the link spatial isolation analysis based on ship relative situation data and maritime communication channel status data involves: The physical distances between nodes are calculated based on the relative ship situation data to obtain the node distance matrix; Based on the node distance matrix, the interference coupling degree data is obtained by analyzing the channel interference overlap between nodes using marine communication channel status data. The directional isolation parameters are obtained by calculating the directional angle difference of the ship's antenna based on the interference coupling data. Based on the node distance matrix and directional isolation parameters, two ships with a distance greater than 5 nautical miles or a difference in azimuth greater than 60 degrees are marked as spatially sufficiently isolated node pairs; two ships with a distance less than 5 nautical miles and a difference in azimuth less than 60 degrees are marked as spatially insufficiently isolated node pairs. Link independence is marked for spatially sufficiently isolated node pairs, and node spatial integration is performed on spatially insufficiently isolated node pairs to generate cross-chain spatial communication potential data; Step S3: Based on the cross-chain spatial communication potential data, divide feasible link communication clusters and construct a multi-link self-organizing network topology; specifically, step S3 involves: Step S31: Identify a list of potentially available communication links based on cross-chain space communication potential data and marine communication channel status data; Step S32: Perform resource reuse assessment based on the list of potentially available communication links to obtain feasible spatial reuse link pairs; Step S33: Divide feasible link communication clusters according to the feasible links for spatial multiplexing; Step S34: Establish time-division multiplexing mechanisms within each communication cluster based on feasible link communication clusters, and construct a multi-link self-organizing network topology; Step S4: Based on the multi-link self-organizing network topology, perform task adaptation communication link allocation and generate multi-link communication task adaptation data; execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

2. The marine multi-link converged communication method according to claim 1, characterized in that, Step S1, receiving navigation information broadcast by other vessels within a preset range, includes: Obtain the ship's unique identification code and the specific pseudo-random sequence preset for each communication link; The detection signal to be loaded is obtained by digital encoding and waveform shaping based on the ship's unique identification code and the specific pseudo-random sequences preset in each communication link. Based on the detection signal to be loaded, parameter commands are issued to specify the low-power transmission target level value of each link in order to obtain the configuration command for the transmission link to be activated. The transmission link type and the actual output power value fed back by the self-organizing network radio are determined according to the transmission link configuration command to be activated, and the radio frequency front-end is activated to start the all-time, multi-channel concurrent monitoring mode and obtain the activated multi-link concurrent monitoring status. Based on the active multi-link concurrent listening state, a spectrum scan monitoring of 0.5-3000MHz is performed, and the broadband digital intermediate frequency streams received by the unidirectional AIS receiver in each link are subjected to real-time matched filtering to generate neighbor detection and acquisition signals. Based on the neighbor detection and capture signals, identify the neighbor's vessel signals to obtain a single vessel detection event; The dynamic information of surrounding vessels is aggregated based on a single vessel detection event to obtain dynamic information of surrounding vessels.

3. The marine multi-link converged communication method according to claim 1, characterized in that, Step S1, which classifies the communication link quality level based on the dynamic information of surrounding vessels, includes: Extract measured signal strength and signal-to-noise ratio data of the communication link based on the dynamic information of surrounding vessels; By using a preset link quality classification threshold, links with a measured signal strength greater than -85dBm and a measured signal-to-noise ratio greater than 12dB are marked to obtain high-quality link identification data. By using a preset link quality classification threshold, links with measured signal strength between -85dBm and -100dBm and measured signal-to-noise ratio between 8dB and 12dB are marked to obtain medium-quality link identification data. Based on high-quality link identification data and medium-quality link identification data, communication links that do not meet the above conditions are marked to obtain low-quality link identification data. The link quality rating data is obtained by using high-quality link identification data, medium-quality link identification data, and low-quality link identification data to evaluate the communication link quality of surrounding vessel dynamic information.

4. The marine multi-link converged communication method according to claim 1, characterized in that, Step S1 involves assessing the availability of communication frequency bands for surrounding vessels using current marine meteorological and hydrological data and link quality rating data. Spectrum power density analysis is performed based on link quality rating data, and spectrum occupancy status is assessed to generate spectrum occupancy status data. Based on current marine meteorological and hydrological data, the propagation environment impact factors of each frequency band are correlated to obtain meteorological impact factors; Multipath signal propagation was measured using an array antenna, and channel delay characteristics were correlated and corrected based on meteorological influence factors to obtain channel delay characteristic data. The availability of each frequency band in the communication environment is evaluated by using channel delay characteristic data to assess spectrum occupancy status data, thereby generating maritime communication channel status data.

5. The marine multi-link converged communication method according to claim 1, characterized in that, Step S4, which involves allocating communication links for task adaptation based on a multi-link ad hoc network topology, includes: Receive specific communication task requests from upper-layer applications or operators, and extract the required data rate, maximum allowable latency, and minimum reliability requirements to obtain the current communication task requirements; The current communication task requirements are classified and prioritized to obtain a service priority list; Based on the aforementioned business priority list and cross-chain spatial communication potential data, the redundancy of time slot resources is adjusted to obtain the formation time slot configuration data. Based on the multi-link self-organizing network topology, the task source transmission nodes of the service priority list are determined, and potential transmission paths are identified to obtain the full topology transmission paths. Based on the full topology transmission path, calculate the estimated number of time slots required for each communication node to complete data transmission within its respective communication cluster, and obtain the node time slot requirement. Based on the node time slot demand, task adaptation communication link allocation is performed on the full topology transmission path to generate multi-link communication task adaptation data.

6. The marine multi-link converged communication method according to claim 1, characterized in that, In step S4, multi-link parallel transmission is performed based on the multi-link communication task adaptation data, and a multi-link fusion transmission strategy is constructed, including: By using link quality rating data to perform real-time channel quality analysis on the target communication link of the multi-link communication task adaptation data, an instant channel snapshot of the target link is generated; the instant channel snapshot of the target link includes high-quality links, medium-quality links, and low-quality links. Link weighted stability assessment is performed based on real-time channel snapshots of the target link to generate a channel stability index. Based on the channel stability index and link quality rating data, stable link modulation configuration is performed to generate multi-link modulation configuration data. Among them, high-quality links use 64QAM modulation with a coding rate of 5 / 6; medium-quality links use 16QAM modulation with a coding rate of 3 / 4; and low-quality links use QPSK modulation with a coding rate of 1 / 2. Link subcarrier allocation is performed based on multi-link modulation configuration data to generate link subcarrier allocation data. The adaptive frequency hopping sequence is obtained by adjusting the frequency hopping point of the multi-link communication task adaptation data through the link subcarrier allocation data. Multi-link parallel transmission is implemented based on adaptive frequency hopping sequences to construct a multi-link fusion transmission strategy.

7. A marine multi-link converged communication system, characterized in that, For executing the marine multi-link converged communication method as described in claim 1, the marine multi-link converged communication system comprises: The channel status awareness module is used to receive navigation information broadcast by other ships within a preset range to obtain dynamic information of surrounding ships; classify the communication link quality level based on the dynamic information of surrounding ships to obtain link quality rating data; acquire current marine meteorological and hydrological data; and evaluate the availability of communication frequency bands based on the current marine meteorological and hydrological data and link quality rating data to generate marine communication channel status data. The link potential analysis module is used to obtain the geographical location data of each vessel using Beidou-3 navigation equipment; and to perform space communication link potential analysis based on the geographical location data of each vessel and the status data of the sea area communication channels, thereby generating cross-link space communication potential data. The network topology construction module is used to divide feasible link communication clusters based on cross-chain spatial communication potential data and construct a multi-link self-organizing network topology. The link fusion scheduling module is used to allocate communication links for task adaptation based on the multi-link self-organizing network topology, generate multi-link communication task adaptation data, execute multi-link parallel transmission according to the multi-link communication task adaptation data, and construct a multi-link fusion transmission strategy to achieve real-time communication link security switching management.

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