Underwater acoustic network transmission method and system for multi-platform information convergence scene

Abstract

The invention relates to the field of underwater acoustic network transmission, in particular to an underwater acoustic network transmission method and system for a multi-platform information convergence scene. The underwater acoustic network transmission method comprises the following steps: acquiring a network node broadcast cluster head competition frame of target information, participating in cluster head competition, and forming a sensing cluster; establishing an intra-cluster conflict-free delay optimal transmission model, and calculating an optimal scheduling scheme under the current transmission demand; in-cluster data aggregation and information transmission tasks of the sensing clusters are completed according to the optimal scheduling scheme; and cluster head competition is carried out again in the next information convergence period and a new sensing cluster is formed, and the execution is repeated until the dynamic target disappears in the underwater acoustic network. According to the underwater acoustic network transmission method, on the basis of the idea of link interference avoidance, the clustering network whole-process transmission model facing the multi-platform information dynamic convergence scene is established according to the real-time state in the cluster, the optimal transmission scheme in the current scene is obtained, and the underwater acoustic network convergence efficiency facing the multi-platform information dynamic convergence scene is further improved.

Description

Technical Field

[0001] This application relates to the field of underwater acoustic network transmission, specifically to an underwater acoustic network transmission method and system for multi-platform information convergence scenarios. Background Technology

[0002] Multi-platform information aggregation is a common scenario in underwater acoustic networks, requiring the convergence of information sensed by multiple platforms within the network to a single node for processing. However, the transmission of information between nodes within an underwater acoustic network requires network protocol control. If the signal transmission timing of each node is inappropriate, it can cause conflicts between multiple network signals, degrading transmission performance. Particularly during the aggregation of moving target sensing information, the nodes within the underwater acoustic network that can sense target information dynamically change with the target's position, further increasing the difficulty of conflict-free transmission of target information across multiple nodes within the underwater acoustic network.

[0003] In related technologies, neighbor node tables are obtained by listening to signals within the network, and a network-aware cluster is established. Data aggregation is then performed within the cluster using the TDMA method. However, during this aggregation process, time slots are allocated to all cluster member nodes. Cluster member nodes without target information do not transmit data in their designated time slots, reducing channel utilization and network transmission efficiency. Therefore, efficiently aggregating multi-node sensing information within a network remains a challenging problem for industry professionals. Summary of the Invention

[0004] This addresses the issue of low channel utilization and network transmission efficiency during intra-cluster data aggregation in underwater acoustic network transmission methods.

[0005] In a first aspect, embodiments of this application provide an underwater acoustic network transmission method for multi-platform information convergence scenarios, the underwater acoustic network transmission method comprising: Network nodes that monitor and sense dynamic targets within the underwater acoustic network broadcast cluster head contention frames and participate in cluster head contention to acquire target information; When a network node wins the cluster head competition, the network node and its neighboring nodes are treated as cluster members to form a perception cluster. At the beginning of each information aggregation cycle, a cluster-wide collision-free delay-optimal transmission model is established based on the network aggregation transmission characteristics, the transmission requirements of the next cycle, and the underwater acoustic network collision avoidance principle. The optimal scheduling scheme under the current transmission requirements is then calculated. Complete the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme; In the next information aggregation cycle, cluster head competition is carried out again to form a new sensing cluster. The optimal scheduling scheme under the current transmission requirements is determined again in the current information aggregation cycle. The intra-cluster data aggregation and information transmission tasks of the sensing cluster are completed according to the optimal scheduling scheme until the dynamic target disappears in the underwater acoustic network.

[0006] In conjunction with the first aspect, in one implementation, establishing an intra-cluster collision-free delay-optimal transmission model based on network aggregation transmission characteristics, next cycle transmission requirements, and underwater acoustic network collision avoidance principles includes: Construct an correlation matrix, a link convergence matrix, and an intra-cluster convergence conflict matrix. The correlation matrix is ​​used to describe the possible conflicts in the underwater acoustic network, the link convergence matrix is ​​used to describe the clustered transmission characteristics, and the intra-cluster convergence conflict matrix is ​​used to describe the conflicts existing in the current transmission state. By utilizing the principle of collision avoidance in underwater acoustic networks and combining the network aggregation transmission characteristics and the transmission requirements of the next cycle, constraints are imposed on the correlation matrix, link aggregation matrix, and intra-cluster aggregation collision matrix to generate a collision-free delay-optimal transmission model.

[0007] In conjunction with the first aspect, in one implementation, the method of utilizing the underwater acoustic network collision avoidance principle, and constraining the correlation matrix, link convergence matrix, and intra-cluster convergence collision matrix based on network convergence transmission characteristics and the transmission requirements of the next cycle to generate a collision-free delay-optimal transmission model includes: Based on the principle of collision avoidance in underwater acoustic networks, generate collision-free transmission conditions; Generate network aggregation conditions based on network aggregation transmission characteristics; Based on the conflict-free transmission conditions, network aggregation conditions, and transmission requirements of the next cycle, the correlation matrix, link aggregation matrix, and intra-cluster aggregation conflict matrix are constrained to generate a conflict-free delay-optimal transmission model.

[0008] In conjunction with the first aspect, in one implementation, the collision-free transmission condition includes: The condition for ensuring no signal overlap or interference at the receiving node and collision-free transmission is expressed by the following formula:

[0009] In the formula, S ik This represents the moment when node i sends a data packet to node k. The representative node k sends a data packet to node k. At that moment, S represents the moment when node k sends a data packet to node j. jk This represents the moment when node j sends a data packet to node k. D represents the data packet length. ik D represents the propagation delay between node i and node k.jk represents the propagation delay between node j and node k, and g represents the guard interval.

[0010] In conjunction with the first aspect, in one implementation, the network convergence condition is expressed as follows:

[0011] In the formula, 𝑠 𝑖x R represents the moment when node X sends a data packet to node X. jy represents the moment when node j sends a data packet to node y, and 𝐷jy represents the moment when node j sends a data packet to node y.

[0012] In conjunction with the first aspect, in one implementation, the collision-free delay optimal transmission model is expressed as:

[0013] In the formula, C ij When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C ik When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mk When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mj When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet Indicates the length of the data packet. The maximum value of propagation delay and clock fluctuation within a single convergence cycle. ， b mj It is an incidence matrix. and For link aggregation matrix, To minimize the transmission delay of the scheduled aggregation task, Indicates the first The waiting time for each link Indicates the first The time it takes for a link to complete transmission.

[0014] In conjunction with the first aspect, in one implementation, the network node that monitors and senses dynamic targets within the underwater acoustic network, and the network node that acquires the target information broadcasts cluster head contention frames and participates in cluster head contention, includes: Network nodes that perceive target information and analyze the cluster head priority of network nodes; The priority of the cluster head is broadcast through the cluster head contention frame and participates in cluster head contention.

[0015] In conjunction with the first aspect, in one implementation, the analysis of cluster head priority of network nodes includes: Cluster head priority is calculated using the following formula. and waiting delay :

[0016] In the formula, , and These are the weighting coefficients; For nodes Current remaining energy, Let i be the current received target signal-to-noise ratio. Let i be the number of neighboring nodes of node i; , and These represent the maximum energy of a network node, the maximum signal-to-noise ratio of the target received signal, and the maximum number of neighboring nodes, respectively. This represents the maximum waiting time during the cluster head contention process.

[0017] In conjunction with the first aspect, in one implementation, the step of completing the intra-cluster data aggregation and information transmission task of the sensing cluster according to the optimal scheduling scheme further includes: If a cluster foot node senses that target information needs to be transmitted at the end of the current cycle, it will join the data aggregation process in the next cycle after receiving a cluster head query frame.

[0018] Secondly, embodiments of this application provide an underwater acoustic network transmission device for multi-platform information convergence scenarios, comprising: The dynamic target monitoring module is used to monitor dynamic targets within the underwater acoustic network through network nodes and to sense target information; The cluster head contention module is used to control network nodes to broadcast cluster head contention frames to participate in the cluster head contention process; The cluster member determination module is used to identify the neighboring nodes of the network node as cluster member nodes after the cluster head contention is successful, thus forming a perceptual cluster. The transmission model construction module is used to establish a collision-free delay-optimal transmission model within the cluster at the beginning of each information aggregation cycle, based on the aggregation transmission characteristics of the underwater acoustic network, the transmission requirements of the next cycle, and the collision avoidance principle of the underwater acoustic network. The scheduling calculation module is used to calculate the optimal scheduling scheme under the current transmission demand based on the transmission model. The data transmission module is used to complete the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme; The cluster head update module is used to initiate the cluster head update process to form a new sensing cluster after completing the current cycle transmission task, and to control the repeated execution of the above module functions until the target disappears in the underwater acoustic network.

[0019] The beneficial effects of the technical solutions provided in this application include: This application's underwater acoustic network transmission method is based on the idea of ​​link interference avoidance. According to the real-time status within the cluster, a full-process transmission model of the clustered network for dynamic information aggregation scenarios of multiple platforms is established to obtain the optimal transmission scheme under the current scenario, thereby further improving the aggregation efficiency of underwater acoustic networks for dynamic information aggregation scenarios of multiple platforms. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the workflow of an underwater acoustic network transmission method in one embodiment of this application; Figure 2 This is a schematic diagram of distributed network deployment in one embodiment of this application; Figure 3 This is a schematic diagram of network node contention for cluster head in one embodiment of this application; Figure 4 This is a schematic diagram of cluster head node requesting information in one embodiment of this application; Figure 5 This is a schematic diagram of the cluster head update process in one embodiment of this application; Figure 6 This is a schematic diagram of the cluster head transfer process in one embodiment of this application; Figure 7 This is a schematic diagram of the cluster head node autonomous transfer process in one embodiment of this application; Figure 8 This is a schematic diagram of the control frame structure in one embodiment of this application. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0022] This addresses the issue of low channel utilization and network transmission efficiency during intra-cluster data aggregation in underwater acoustic network transmission methods.

[0023] In a first aspect, embodiments of this application provide an underwater acoustic network transmission method for multi-platform information convergence scenarios, which includes the following steps: Step S1: Deploy multiple network nodes in the working area according to a certain topology to form an underwater acoustic network, complete the initialization process, and obtain the neighboring nodes and propagation delay of the network nodes. information.

[0024] Step S2: Network nodes that monitor and sense dynamic targets within the underwater acoustic network broadcast cluster head competition frames and participate in cluster head competition.

[0025] Step S2 above includes: Step S2a: When a dynamic target appears in the underwater acoustic network, the network node that senses the target information.

[0026] Step S2b: Analyze the cluster head priority of network nodes.

[0027] Specifically, cluster head priority is calculated according to the following formula. and waiting delay :

[0028] In the formula, , and These are the weighting coefficients; For nodes Current remaining energy, Let i be the current received target signal-to-noise ratio. Let i be the number of neighboring nodes of node i; , and These represent the maximum energy of a network node, the maximum signal-to-noise ratio of the target received signal, and the maximum number of neighboring nodes, respectively. This represents the maximum waiting time during the cluster head contention process.

[0029] It should be noted that the cluster head priority calculation method in this application incorporates the influence of remaining energy and the number of neighboring nodes. Including the number of neighboring nodes makes the priority calculation more accurate. Furthermore, incorporating remaining energy into the priority assessment allows for better utilization of each node's energy, preventing some nodes from running out of energy and failing, thereby improving the algorithm's accuracy and stability.

[0030] Step S2c: Broadcast the priority of the cluster head through the cluster head contention frame and participate in cluster head contention.

[0031] Specifically, the cluster head contention algorithm is as follows: When each network node in the underwater acoustic network receives a cluster head contention frame from another node, it extracts the corresponding cluster head priority and compares it with its own cluster head priority. If a node with a higher cluster head priority is found, it automatically relinquishes its position as cluster head; if a node... After transmitting the cluster head contention frame, the waiting time reaches If a node successfully acquires a cluster head and does not receive any other cluster head contention frames with a higher priority than itself, then the contention is successful. Each node forms a perception cluster by using its neighboring nodes as cluster feet nodes, thus completing the cluster head competition process.

[0032] Step S3: When a network node successfully competes for the cluster head, the network node and its neighboring nodes are treated as cluster member nodes to form a perception cluster.

[0033] Specifically, after successfully competing for cluster head status, it obtains its own list of neighboring nodes, and uses these neighboring nodes as cluster member nodes to form a perceptual cluster.

[0034] Step S4: At the beginning of each information aggregation cycle, establish a cluster-wide conflict-free delay-optimal transmission model based on network aggregation transmission characteristics, transmission requirements for the next cycle, and the underwater acoustic network conflict avoidance principle, and calculate the optimal scheduling scheme under the current transmission requirements.

[0035] Step S4 above includes: Step S4a: Construct the association matrix Link aggregation matrix and cluster convergence conflict matrix .

[0036] Understandably, the correlation matrix Link convergence matrix is ​​used to describe potential conflicts in underwater acoustic networks. Used to describe clustered transmission characteristics, intra-cluster convergence collision matrix Used to describe the conflicts that exist in the current transmission state.

[0037] Furthermore, the correlation matrix Correlation matrix used to describe potential conflicts in underwater acoustic networks Describing logical link relationships, represented as:

[0038] It is worth noting that the correlation matrix The rows represent nodes, and the columns represent links. The number of nodes is... The number of links is .

[0039] Multi-level link aggregation matrix Specifically, it is expressed as follows:

[0040] Understandable Indicates the highest convergence level. When the... The first link has a higher priority than the second. When there is a link, it needs to be in the first... This will be done after the transmission of each link is completed.

[0041] Furthermore, the intra-cluster convergence conflict matrix This represents the time C from when the cluster head node completes transmitting the target information query frame, during which different nodes receive different link data packets, with a size of [missing information]. In the matrix, horizontal rows represent nodes and columns represent links. If the matrix... The Middle The source node of the link is The cluster head node is Then the value of the element in the i-th row and k-th column of matrix C is... It can be represented as:

[0042] In the formula, For the first The destination node of the link receives the source node The time required to wait after transmitting the target information query frame; This indicates that the query frame originates from the cluster head node. to link Source node Propagation delay between; Indicates that the data packet originated from the source node. To the node The propagation delay between them, when hour, Indicates that the data packet originated from the source node. The propagation delay to itself is 0 seconds.

[0043] Step S4b: Using the principle of underwater acoustic network collision avoidance, and combining the network aggregation transmission characteristics and the transmission requirements of the next cycle, constraints are applied to the correlation matrix, link aggregation matrix, and intra-cluster aggregation collision matrix to generate a collision-free delay-optimal transmission model.

[0044] The above step S4b includes: Step A: Generate collision-free transmission conditions based on the principle of collision avoidance in underwater acoustic networks.

[0045] Specifically, the principle of collision avoidance in underwater acoustic networks is to ensure that there is no signal overlap interference at the receiving node. There are four types of collisions that can occur in underwater acoustic networks: transmit collisions, receive collisions, transmit / receive collisions, and receive interference collisions. To ensure no signal overlap interference at the receiving node, the expression for the collision-free transmission condition is:

[0046] In the formula, S ik This represents the moment when node i sends a data packet to node k. The representative node k sends a data packet to node k. At that moment, S represents the moment when node k sends a data packet to node j. jk This represents the moment when node j sends a data packet to node k. D represents the data packet length. ik D represents the propagation delay between node i and node k. jk represents the propagation delay between node j and node k, and g represents the guard interval.

[0047] Step B: Generate network aggregation conditions based on network aggregation transmission characteristics.

[0048] Specifically, network convergence characteristics refer to nodes with high convergence levels. Requires low-aggregation level nodes After transmission is completed, the network aggregation condition is expressed as follows:

[0049] In the formula, S ix S represents the time when node i sends a data packet to node x. jy D represents the moment when node j sends a data packet to node y. iy This represents the propagation delay between node i and node y.

[0050] Step C: Based on the conflict-free transmission conditions, network aggregation conditions, and transmission requirements of the next cycle, constrain the correlation matrix, link aggregation matrix, and intra-cluster aggregation conflict matrix to generate a conflict-free delay-optimal transmission model.

[0051] Specifically, the collision-free delay optimal transmission model is expressed as:

[0052] In the formula, C ij When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C ik When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mk When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mj When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet Indicates the length of the data packet. This represents the maximum value of propagation delay and clock fluctuation within a single convergence cycle. It is an incidence matrix. For link aggregation matrix, For the link scheduling result, This refers to the link transmission completion time. To minimize the transmission delay of the scheduled aggregation task, Indicates the first The waiting time for each link Indicates the first The time it takes for a link to complete transmission.

[0053] Step S5: Complete the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme.

[0054] Specifically, step S5 includes: Step S5a: The cluster head transmits an information retrieval frame, which includes the optimal scheduling result and the silence time. After the current periodic scheduling cluster foot node waits for the corresponding time, it transmits an information response frame to gather the target information to the cluster head node.

[0055] Furthermore, the optimal scheduling result includes the link waiting time. The link transmission completion time is .

[0056] And silent time The calculation method is as follows:

[0057] In the formula, For nodes With buoy nodes Propagation delay between This is the set of unscheduled cluster nodes in the current period. This indicates the length of the target information query frame.

[0058] In step S5b, the cluster head node receives the information response frame, extracts and saves the target feature information in the response frame, and processes or directly packages it. After the link waiting time expires, it sends the target feature information within the cluster to the buoy, which then transmits the information to the shore-to-ship monitoring center via radio for further processing.

[0059] Step S5c: Unscheduled cluster nodes in the current period If the storage detects that target information needs to be transmitted, it will wait for a delay after receiving the cluster head query frame. Then, an information request frame is sent, and the data aggregation process is added in the next cycle.

[0060] Furthermore, waiting for delay The calculation method is as follows:

[0061] in, For nodes With cluster head node Propagation delay between This is the maximum random time, which can be set according to the actual topology. ) indicates the generation of a number from 0 to 1. Random numbers.

[0062] After step S5d, when the cluster head node sends the fusion information to the buoy node, wait time... Then, it receives target information request frames from other nodes within the cluster.

[0063] Furthermore, if a cluster foot node senses that target information needs to be transmitted at the end of the current cycle, it will join the data aggregation process in the next cycle after receiving the cluster head query frame.

[0064] Specifically, if the cluster head node receives a cluster foot node If the target information request frame is received, it will be added to the latency-optimal conflict-free model in the next cycle, and a node will be added to the target information query frame. The numbering and response delay.

[0065] It is worth noting that traditional technologies allocate time slots for each node within a cluster for information transmission. However, in practice, not every node needs to transmit information, leading to wasted transmission time and low efficiency. In this application, time slots are only allocated to nodes that require information transmission, while other nodes that need to transmit information are added to the data aggregation process in the next cycle.

[0066] Furthermore, waiting time The calculation method is as follows:

[0067] in, Request the frame length for the target information.

[0068] Step S6: In the next information aggregation cycle, cluster head competition is carried out again to form a new sensing cluster. The optimal scheduling scheme under the current transmission requirements is determined again in the current information aggregation cycle. The intra-cluster data aggregation and information transmission tasks of the sensing cluster are completed according to the optimal scheduling scheme until the dynamic target disappears in the underwater acoustic network.

[0069] Understandably, when the network updates the cluster head node, the newly formed cluster head node will take its neighbor nodes as cluster member nodes, update the perceived cluster, and begin a new information aggregation process until the target disappears.

[0070] Furthermore, the cluster head update algorithm is as follows: Specifically, in each information aggregation cycle, after the cluster head node's received information response frame times out, it sorts its perceived target signal-to-noise ratio and the cluster head priorities of the received cluster member nodes. The node with the highest priority becomes the next cluster head, and the aggregation of target information continues. The cluster head transfer process is as follows: If the next cluster head is not the current cluster head node, the current cluster head node continuously sends cluster head transfer frames to the next cluster head and relinquishes its position as cluster head. The destination node of the cluster head transfer frame becomes the new cluster head. If the next cluster head is still the current cluster head node, no cluster head transfer process is required.

[0071] This application provides a specific embodiment of the underwater acoustic network transmission method for multi-platform information convergence scenarios described above.

[0072] Specifically, in this embodiment, various control frame structures are as follows: Figure 8 As shown, the control frame structure mainly includes cluster head contention frames, information inquiry frames, information response frames, and cluster head transfer frames. Cluster head contention frames and cluster head transfer frames operate during the cluster establishment process, used for the initial target detection requiring cluster head contention and the target position change requiring cluster head transfer, respectively. The target information inquiry frame contains the transmission delay of the cluster foot nodes, used to control the transmission time of target information by the cluster foot nodes. The target information request frame is a single-frequency signal. When a cluster foot node transmits this signal, the cluster head node receives it, indicating that it has no target information in the current transmission cycle, but has target information to transmit in the next cycle. Each cluster foot node corresponds to a different signal frequency, and the cluster head node can simultaneously receive target information request frames from multiple cluster foot nodes.

[0073] A specific implementation of underwater acoustic network transmission includes the following steps: First, a 23-node underwater acoustic network was constructed in the working area, including 17 underwater moorings (#46, #50, #41, #39, #49, #35, #48, #44, #43, #32, #51, #42, #53, #57, #54, #47, #37), 4 buoys (#2, #3, #4, #5), 1 ship-based command and control center (#21), and 1 mobile target node (#91).

[0074] It is worth noting that the specific network topology is as follows: Figure 2 As shown in the diagram, the solid line corresponds to the trajectory of moving target #91. Each buoy node is equipped with a sensing unit, which can sense the target's azimuth, spectral density, and received signal-to-noise ratio in real time. The buoys are mainly used to sense the network status and upload fusion information from the cluster head nodes. (Data packet length) =9.5s, Information query frame length =3.5s, target information request frame length =1s, protection time slot length =0.5s.

[0075] Secondly, the query frame sent by the cluster head contains the response delays of the cluster member nodes. The cluster member nodes reply with response packets sequentially according to their response delays. After receiving the response packets, the cluster head node performs fusion processing and uploads the processing result to the monitoring center. This process is as follows: Figure 4 As shown in the figure, the horizontal axis corresponds to the experimental time progress, and the vertical axis corresponds to the network node number, which includes all nodes that participated in the sensing experiment. Each time in the figure corresponds to one sensing cycle, and the data column corresponding to that time represents the information aggregation process within the cluster in that cycle. The different colors filled in each grid in the figure represent the different actions of the nodes in that cycle, and their relationships are as follows: Figure 5 As shown.

[0076] In some alternative embodiments, Figure 4 In the image, the data at 09:55:07, indicated by the red arrow, represents the time when the cluster head node is #46 within this sensing period. At this time, three nodes—#50, #41, and #39—need to send data, requiring the transmission of four links: links from the three cluster foot nodes to the cluster head node #46, and a link from the cluster head node #46 to the buoy node #2. The association matrix established by cluster head node #32 is also shown. and convergence matrix They are respectively:

[0077] Intra-cluster convergence conflict matrix for

[0078] in, For the first The waiting interval of each link.

[0079] The current period establishes the following clustered network transmission model:

[0080] The model calculates the waiting delay for cluster foot nodes #50, #41, and #39 after receiving a cluster head query frame. The specific scheduling results for the current period are as follows: Figure 6 As shown.

[0081] Furthermore, cluster head node #32 transmitted an information query frame, and cluster member nodes #50, #41, and #39 delayed their response times. Information response data packets were subsequently transmitted, and all were successfully received. After processing the target information of the three cluster foot nodes and itself, the cluster head node obtained the fusion result and sent it to the #3 buoy node, completing the information upload. During this cycle, #35 and #39 transmitted target information request frames, which will join the intra-cluster data aggregation and upload process in the next cycle.

[0082] Finally, regarding the intra-cluster information transmission process, Figure 7 This paper compares the transmission delay of this application with that of the traditional TDMA method for different cycles. The statistical results of the traditional TDMA method were obtained from experimental network sensing results combined with simulation analysis, while the results of this method were obtained from experimental results. The average transmission delay per cycle of this method is 64.1s, while that of the traditional TDMA method is 107.2s, representing an average performance improvement of 67.2%. This verifies the effectiveness of this method.

[0083] Secondly, this application provides an underwater acoustic network transmission device for multi-platform information convergence scenarios, comprising: a dynamic target monitoring module, a cluster head contention module, a cluster member determination module, a transmission model construction module, a scheduling calculation module, a data transmission module, and a cluster head update module; wherein, The system comprises the following modules: a dynamic target monitoring module for monitoring dynamic targets within the underwater acoustic network and sensing target information; a cluster head contention module for controlling network nodes to broadcast cluster head contention frames to participate in the cluster head contention process; a cluster member determination module for identifying neighboring nodes of the network node as cluster members after successful cluster head contention, forming a sensing cluster; a transmission model construction module for establishing a conflict-free delay-optimal transmission model within the cluster at the beginning of each information aggregation cycle, based on the aggregation transmission characteristics of the underwater acoustic network, the transmission requirements of the next cycle, and the collision avoidance principle of the underwater acoustic network; a scheduling calculation module for calculating the optimal scheduling scheme under the current transmission requirements based on the transmission model; a data transmission module for completing the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme; and a cluster head update module for initiating a cluster head update process to form a new sensing cluster after completing the current cycle's transmission task, and controlling the repeated execution of the above module functions until the target disappears within the underwater acoustic network.

[0084] The functions of each module in the above-mentioned underwater acoustic network transmission device correspond to the steps in the above-mentioned underwater acoustic network transmission method embodiment, and their functions and implementation processes will not be described in detail here.

[0085] Thirdly, embodiments of this application provide an underwater acoustic network transmission device, which can be a personal computer (PC), laptop computer, server, or other device with data processing capabilities.

[0086] In this embodiment of the application, the underwater acoustic network transmission device may include a processor, a memory, a communication interface, and a communication bus.

[0087] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0088] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting internal components of the underwater acoustic network transmission equipment, as well as interfaces used for interconnecting the underwater acoustic network transmission equipment with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0089] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0090] The processor can be a general-purpose processor, which can call the underwater acoustic network transmission program stored in the memory and execute the underwater acoustic network transmission method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the underwater acoustic network transmission program is called can be referred to in the various embodiments of the underwater acoustic network transmission method of this application, and will not be repeated here.

[0091] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0092] The present application has a computer-readable storage medium storing an underwater acoustic network transmission program, wherein when the underwater acoustic network transmission program is executed by a processor, it implements the steps of the underwater acoustic network transmission method as described above.

[0093] The method implemented when the underwater acoustic network transmission program is executed can be referred to in various embodiments of the underwater acoustic network transmission method of this application, and will not be repeated here.

[0094] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0095] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0096] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0097] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0098] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0100] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for underwater acoustic network transmission in multi-platform information convergence scenarios, characterized in that, The underwater acoustic network transmission method includes: Network nodes that monitor and sense dynamic targets within the underwater acoustic network broadcast cluster head contention frames and participate in cluster head contention to acquire target information; When a network node wins the cluster head competition, the network node and its neighboring nodes are treated as cluster members to form a perception cluster. At the beginning of each information aggregation cycle, a cluster-wide collision-free delay-optimal transmission model is established based on the network aggregation transmission characteristics, the transmission requirements of the next cycle, and the underwater acoustic network collision avoidance principle. The optimal scheduling scheme under the current transmission requirements is then calculated. Complete the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme; In the next information aggregation cycle, cluster head competition is carried out again to form a new sensing cluster. The optimal scheduling scheme under the current transmission requirements is determined again in the current information aggregation cycle. The intra-cluster data aggregation and information transmission tasks of the sensing cluster are completed according to the optimal scheduling scheme until the dynamic target disappears in the underwater acoustic network.

2. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 1, characterized in that, The establishment of a cluster-based collision-free delay-optimal transmission model based on network aggregation transmission characteristics, next cycle transmission requirements, and underwater acoustic network collision avoidance principles includes: Construct an correlation matrix, a link convergence matrix, and an intra-cluster convergence conflict matrix. The correlation matrix is ​​used to describe the possible conflicts in the underwater acoustic network, the link convergence matrix is ​​used to describe the clustered transmission characteristics, and the intra-cluster convergence conflict matrix is ​​used to describe the conflicts existing in the current transmission state. By utilizing the principle of collision avoidance in underwater acoustic networks, and combining the network aggregation transmission characteristics and the transmission requirements of the next cycle, constraints are imposed on the correlation matrix, link aggregation matrix, and intra-cluster aggregation collision matrix to generate a collision-free delay-optimal transmission model.

3. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 2, characterized in that, The method utilizes the principle of underwater acoustic network collision avoidance, combined with network aggregation transmission characteristics and the transmission requirements of the next cycle, to constrain the correlation matrix, link aggregation matrix, and intra-cluster aggregation collision matrix to generate a collision-free delay-optimal transmission model, including: Based on the principle of collision avoidance in underwater acoustic networks, generate collision-free transmission conditions; Generate network aggregation conditions based on network aggregation transmission characteristics; Based on the conflict-free transmission conditions, network aggregation conditions, and transmission requirements of the next cycle, the correlation matrix, link aggregation matrix, and intra-cluster aggregation conflict matrix are constrained to generate a conflict-free delay-optimal transmission model.

4. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 3, characterized in that, The conflict-free transmission conditions include: The condition for ensuring no signal overlap or interference at the receiving node and collision-free transmission is expressed by the following formula: In the formula, S ik This represents the moment when node i sends a data packet to node k. The representative node k sends a data packet to node k. At that moment, S represents the moment when node k sends a data packet to node j. jk This represents the moment when node j sends a data packet to node k. D represents the data packet length. ik D represents the propagation delay between node i and node k. jk represents the propagation delay between node j and node k, and g represents the guard interval.

5. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 4, characterized in that: The network aggregation condition is expressed as follows: In the formula, S ix S represents the time when node i sends a data packet to node x. jy D represents the moment when node j sends a data packet to node y. iy This represents the propagation delay between node i and node y.

6. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 5, characterized in that: The collision-free delay optimal transmission model is expressed as: In the formula, C ij When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C ik When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mk When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet, C mj When the cluster head node completes transmitting the target information query frame, the node... Received the The time of each link data packet Indicates the length of the data packet. The maximum value of propagation delay and clock fluctuation within a single convergence cycle. ， b mj It is an incidence matrix. and For link aggregation matrix, To minimize the transmission delay of the scheduled aggregation task, Indicates the first The waiting time for each link Indicates the first The time it takes for a link to complete transmission.

7. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 1, characterized in that, The network nodes that monitor and sense dynamic targets within the underwater acoustic network, and broadcast cluster head contention frames and participate in cluster head contention to obtain target information, include: Network nodes that perceive target information and analyze the cluster head priority of network nodes; The priority of the cluster head is broadcast through the cluster head contention frame and participates in cluster head contention.

8. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 7, characterized in that, The cluster head priority of the analyzed network nodes includes: Cluster head priority is calculated using the following formula. and waiting delay : In the formula, , and These are the weighting coefficients; For nodes Current remaining energy, Let i be the current received target signal-to-noise ratio. Let i be the number of neighboring nodes of node i; , and These represent the maximum energy of a network node, the maximum signal-to-noise ratio of the target received signal, and the maximum number of neighboring nodes, respectively. This represents the maximum waiting time during the cluster head contention process.

9. The underwater acoustic network transmission method for multi-platform information convergence scenarios as described in claim 1, characterized in that, The step of completing the intra-cluster data aggregation and information transmission task of the sensing cluster according to the optimal scheduling scheme also includes: If a cluster foot node senses that target information needs to be transmitted at the end of the current cycle, it will join the data aggregation process in the next cycle after receiving a cluster head query frame.

10. A water acoustic network transmission device for multi-platform information convergence scenarios, characterized in that, include: The dynamic target monitoring module is used to monitor dynamic targets within the underwater acoustic network through network nodes and to sense target information; The cluster head contention module is used to control network nodes to broadcast cluster head contention frames to participate in the cluster head contention process; The cluster member determination module is used to identify the neighboring nodes of the network node as cluster member nodes after the cluster head contention is successful, thus forming a perceptual cluster. The transmission model construction module is used to establish a collision-free delay-optimal transmission model within the cluster at the beginning of each information aggregation cycle, based on the aggregation transmission characteristics of the underwater acoustic network, the transmission requirements of the next cycle, and the collision avoidance principle of the underwater acoustic network. The scheduling calculation module is used to calculate the optimal scheduling scheme under the current transmission demand based on the transmission model. The data transmission module is used to complete the intra-cluster data aggregation and information transmission tasks of the sensing cluster according to the optimal scheduling scheme; The cluster head update module is used to initiate the cluster head update process to form a new sensing cluster after completing the current cycle transmission task, and to control the repeated execution of the above module functions until the target disappears in the underwater acoustic network.

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