Multi-dimensional moving target ad hoc network method and system based on double links and storage medium

Abstract

The invention discloses a multi-dimensional moving target ad hoc network method and system based on double links and a storage medium, and relates to the field of communication transmission, and the method comprises the steps: taking a moving target as a deployment node in a search and rescue area, and constructing an ad hoc network of the moving target; based on the ad hoc network, performing communication dual-path construction on the deployment nodes to obtain dual communication links of the search and rescue area; performing time sequence state trend deduction on the multi-dimensional state information of the deployment nodes to obtain a mobile prediction vector of the search and rescue area; based on the mobile prediction vector, performing path evolution on the sending node and the receiving node to obtain an optimal communication path of the search and rescue area; based on the optimal communication path, dynamically adjusting the active state of the dual communication links to obtain a target communication link of the search and rescue area; and based on the optimal communication path, carrying out search and rescue task data forwarding on the deployment node through the target communication link, and completing the search and rescue task of the search and rescue area. The search and rescue efficiency of the ad hoc network based on the double-link multi-dimensional moving target can be improved.

Description

Technical Field

[0001] This invention relates to the field of communication transmission technology, and in particular to a method, system, and storage medium for a multidimensional mobile target self-organizing network based on dual links. Background Technology

[0002] In search and rescue applications using dual-link, multi-dimensional mobile target ad hoc networks, existing technologies often struggle to balance the stability and continuity of communication links. Some solutions employ a single communication path to build the network, which is prone to link interruptions and signal attenuation when faced with the dynamic displacement of mobile targets within the search and rescue area. Furthermore, the lack of an efficient backup path switching mechanism hinders data transmission during search and rescue missions. Other solutions attempt to configure dual links, but their interface coordination and status monitoring of deployed nodes are inadequate, failing to promptly detect changes in link connectivity, resulting in delays in link switching and impacting the real-time transmission of search and rescue commands and data.

[0003] Existing technologies have significant shortcomings in communication path optimization and load control. Most fail to fully consider the multi-dimensional state information of deployed nodes, making it difficult to accurately predict node movement trends. This results in a lack of foresight in path selection and insufficiently scientific reliability assessment of candidate paths. Furthermore, existing technologies lack dynamic adaptability to adjust the active state of dual links, failing to allocate load reasonably based on the node distribution and transmission load of the optimal communication path. This easily leads to overload of the primary link and idle resources on the backup link, thereby reducing the overall communication efficiency of the ad hoc network and failing to meet the rapid response and efficient collaboration requirements of search and rescue missions. Therefore, improving the search and rescue efficiency of dual-link multi-dimensional mobile target ad hoc networks has become an urgent problem to be solved. Summary of the Invention

[0004] This disclosure provides a method, system, and storage medium for a multi-dimensional mobile target self-organizing network based on dual links.

[0005] In a first aspect, this disclosure provides a method for multi-dimensional mobile target ad hoc networking based on dual links, including: S1. Within the search and rescue area, construct an ad hoc network of the mobile targets, using them as deployment nodes; S2. Based on the self-organizing network, the deployment nodes are constructed with dual communication paths to obtain dual communication links in the search and rescue area; S3. Perform time-series state trend deduction on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area; S4. Based on the motion prediction vector, perform path evolution on the sending node and receiving node to obtain the optimal communication path in the search and rescue area; S5. Based on the optimal communication path, dynamically adjust the active state of the dual communication links to obtain the target communication link in the search and rescue area. S6. Based on the optimal communication path, the search and rescue mission data is forwarded to the deployment node through the target communication link to complete the search and rescue mission in the search and rescue area.

[0006] In a preferred embodiment, the step of constructing an ad hoc network of the mobile targets within the search and rescue area, using the mobile targets as deployment nodes, includes: Use moving targets within the search and rescue area as deployment nodes; The neighbor detection signaling of the deployed node is detected through the wireless communication interface, and the neighbor discovery message of the deployed node is obtained. Receive neighbor response messages between the deployed nodes; By performing coordinated link configuration on the neighbor discovery message and the neighbor response message, a temporary point-to-point communication link in the search and rescue area is obtained. Based on the temporary point-to-point communication link and the distributed route discovery process, the initial topology of the mobile target is constructed; Based on the initial topology, the routing tables of the deployed nodes are initialized to obtain the self-organizing network of the mobile target.

[0007] In a preferred embodiment, the step of constructing dual-path communication for the deployed nodes based on the self-organizing network to obtain dual communication links in the search and rescue area includes: Configure a primary network interface and a backup network interface on the deployment node; Based on the current topology of the self-organizing network, two logically isolated data transmission paths are allocated to the deployment node; The connectivity status of the primary network interface is continuously monitored to obtain the real-time monitoring results of the self-organizing network; When the real-time monitoring result indicates that the connectivity is lost, the data stream is switched to the data transmission path corresponding to the backup network interface to obtain a dual communication link in the search and rescue area.

[0008] In a preferred embodiment, the step of performing time-series state trend extrapolation on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area includes: The multidimensional state information of the deployment node is time-series aligned to obtain the state information sequence of the deployment node; Based on the state information sequence, forward prediction is performed on the deployment node to obtain the state prediction result of the deployment node; Based on the real-time observation data of the deployment node, the state prediction result is optimized and corrected to obtain the calibrated state prediction result of the deployment node. The calibrated state prediction results are vectorized to obtain the movement prediction vector of the search and rescue area.

[0009] In a preferred embodiment, the step of performing path evolution on the sending and receiving nodes based on the mobility prediction vector to obtain the optimal communication path for the search and rescue area includes: Based on the motion prediction vector, the predicted motion trajectories of the sending node and the receiving node are extracted; The predicted motion trajectory is used to perform trajectory-guided path deduction to obtain candidate communication paths between the sending node and the receiving node; Obtain the velocity vectors and current distances of the sending node and the receiving node in the candidate communication path; Based on the velocity vector and the current distance, the reliability of the candidate communication path is quantitatively evaluated to obtain the reliability value of the candidate communication path; Based on the reliability value, the candidate communication path with the highest reliability is selected as the optimal communication path for the search and rescue area.

[0010] In a preferred embodiment, the reliability value is calculated using the following formula: ; In the formula, Indicates the candidate communication path Reliability value, This represents the preset reliability degradation coefficient. Indicates the candidate communication path The number of links in Indicates the candidate communication path Midlink The velocity vector of the sending node, Indicates the candidate communication path Midlink The velocity vector of the receiving node, Indicates the candidate communication path Midlink Current distance, Indicates An exponential function with base 0.

[0011] In a preferred embodiment, the step of dynamically adjusting the active state of the dual communication links based on the optimal communication path to obtain the target communication link in the search and rescue area includes: Monitor the real-time transmission load of the primary link and the backup link in the dual communication links; Based on the node distribution of the optimal communication path, the real-time transmission load of the primary link is compared with the preset load balancing threshold to determine the risk of exceeding the limit. When the real-time transmission load of the primary link exceeds the preset load balancing threshold, a portion of the data transmission tasks in the data stream are allocated to the backup link. The primary link and the backup link, which are in a collaborative working state, are integrated and calibrated to obtain the target communication link in the search and rescue area.

[0012] In a preferred embodiment, the step of forwarding search and rescue mission data to the deployment node through the target communication link based on the optimal communication path to complete the search and rescue mission in the search and rescue area includes: The search and rescue mission data to be transmitted is formatted and encapsulated to obtain a data packet of the search and rescue mission data; Based on the node sequence of the optimal communication path, the data packet is forwarded to the next deployed node through the target communication link; When the data packet is forwarded to the receiving node of the optimal communication path, the data packet is decapsulated to obtain the search and rescue mission data of the search and rescue area; The search and rescue mission is completed in response to search and rescue instructions detected in the search and rescue mission data.

[0013] In summary, this application includes at least one of the following beneficial technical effects: 1. This invention constructs dual communication links by configuring primary and backup network interfaces for deployment nodes, and monitors the connectivity status and transmission load of the primary link in real time. When the primary link fails, it can switch to the backup link. When the primary link is overloaded, it can allocate some data transmission tasks to the backup link, avoiding interruption of search and rescue data transmission caused by single link failure or overload. This ensures stable and continuous transmission of search and rescue mission data in dynamic mobile scenarios and provides reliable communication support for the search and rescue process.

[0014] 2. This invention obtains a movement prediction vector by performing time-series extrapolation on the multi-dimensional state information of deployed nodes. Based on this vector, the predicted movement trajectory of the nodes is extracted, and the reliability of candidate paths is evaluated to determine the optimal communication path, reducing the problem of frequent path failures caused by node movement. Simultaneously, forwarding search and rescue data based on the optimal path can shorten data transmission latency, ensuring that search and rescue instructions and task data are quickly transmitted to the target node, effectively improving the response speed and execution efficiency of search and rescue missions. Attached Figure Description

[0015] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings: Figure 1The flowchart of the multi-dimensional mobile target ad hoc network method based on dual links according to Embodiment 1 of the present invention is shown. Figure 2 The diagram shows the functional modules of a dual-link-based multidimensional mobile target self-organizing network system according to Embodiment 2 of the present invention. Detailed Implementation

[0016] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0017] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0018] Example 1 Figure 1 This is a flowchart illustrating the multi-dimensional mobile target ad hoc network method based on dual links provided in this disclosure. Figure 1 As shown, the multi-dimensional mobile target ad hoc network method based on dual links includes: S1. Within the search and rescue area, construct an ad hoc network of the mobile targets, using them as deployment nodes; In this embodiment of the invention, the step of constructing an ad hoc network of the mobile targets within the search and rescue area, using the mobile targets as deployment nodes, includes: Use moving targets within the search and rescue area as deployment nodes; The neighbor detection signaling of the deployed node is detected through the wireless communication interface, and the neighbor discovery message of the deployed node is obtained. Receive neighbor response messages between the deployed nodes; By performing coordinated link configuration on the neighbor discovery message and the neighbor response message, a temporary point-to-point communication link in the search and rescue area is obtained. Based on the temporary point-to-point communication link and the distributed route discovery process, the initial topology of the mobile target is constructed; Based on the initial topology, the routing tables of the deployed nodes are initialized to obtain the self-organizing network of the mobile target.

[0019] Specifically, the entire implementation process centers on mobile targets within the search and rescue area, unfolding a complete closed-loop operation around the construction of an ad hoc network. First, deployment nodes with communication and data processing capabilities are identified through precise identification and positioning. Then, neighbor detection signaling is sent, received, and parsed using wireless communication interfaces to generate neighbor discovery messages. Subsequently, bidirectional transmission of neighbor response messages between deployment nodes is achieved. Based on the interaction results of the two types of messages, collaborative link configuration is completed, and temporary point-to-point communication links are established. Then, the initial topology is constructed by integrating link information and neighbor information. Finally, the routing tables of all deployment nodes are populated and initialized based on the topology, ultimately forming an ad hoc network of mobile targets capable of supporting autonomous data transmission and interaction between nodes. Each link is closely connected to ensure the coherence and effectiveness of network construction.

[0020] Furthermore, the specific scope of the search and rescue area is first clearly defined. Using ground-deployed infrared and microwave sensors, as well as drones equipped with aerial image acquisition devices, all moving targets within the area are scanned and monitored comprehensively. The movement trajectories and signal characteristics of these targets are captured, and those with stable wireless communication capabilities and basic data processing abilities are selected. These targets include portable communication terminals carried by search and rescue personnel, mobile rescue robots, and rescue vehicles equipped with communication modules. Each selected moving target is assigned a unique identifier, which is stored and retrieved through a built-in chip to ensure that each moving target's identity is unique. These identified, screened, and assigned moving targets are then formally defined as deployment nodes. Simultaneously, positioning devices are used to confirm that all deployment nodes are within the designated search and rescue area, laying the foundation for subsequent network construction.

[0021] Furthermore, each deployment node activates its configured radio frequency communication interface. This interface continuously broadcasts neighbor detection signaling containing its own unique identification information to the search and rescue area at fixed intervals. The signaling propagation range covers the entire search and rescue area, ensuring that other deployment nodes can receive it. At the same time, each deployment node's radio frequency communication interface remains in a 24 / 7 receiving state, capturing neighbor detection signaling sent by other deployment nodes in the vicinity in real time. During the reception process, interference signals outside the search and rescue area are automatically filtered out, and only valid signaling sent by deployment nodes within the area is retained. Each valid signaling is parsed byte by byte to extract the unique identification information of the sending deployment node contained therein. This extracted identification information is associated and recorded with its own unique identification information, and a complete list is formed according to the reception time order. Finally, a neighbor discovery message exclusive to that deployment node is generated, which clearly presents the identity information of all other deployment nodes detected by it.

[0022] Furthermore, after generating the neighbor discovery message, each deployment node immediately initiates a response mechanism. Through its own radio frequency communication interface, it sends a neighbor response message to each other deployment node recorded in the neighbor discovery message. This response message contains the unique identifier of the sending deployment node, confirmation feedback of the received neighbor probe signaling, and its own current communication status information, ensuring that the receiver can clearly identify the sender's identity and confirm the validity of the interaction. At the same time, each deployment node's radio frequency communication interface maintains a high-sensitivity receiving state, performs source verification on each received neighbor response message, checks whether the sender's identifier exists in its own neighbor discovery message, filters out invalid and unfamiliar messages, and archives and stores the verified response messages according to the sender's identifier. This ensures that the response messages sent by all deployment nodes that have probe interactions with it can be completely received, verified, and stored without any omissions or errors.

[0023] Furthermore, through the temporary signal interaction channels established between the deployed nodes, neighbor discovery messages and stored neighbor response messages generated by all deployed nodes within the search and rescue area are collected. All messages are aggregated into a unified processing stage, and the sender and receiver identifiers in each message are compared item by item to identify the sending and receiving nodes corresponding to each neighbor detection signaling message, as well as the feedback and receiving nodes corresponding to each neighbor response message. Deployment node pairs that simultaneously meet the criteria of "the sending node sent a neighbor detection signaling message to the receiving node" and "the receiving node returned a neighbor response message to the sending node" are selected. For each pair of qualified deployment nodes, a dedicated communication frequency band is locked, a unique access permission is set, and a bidirectional channel for data transmission between these two nodes is established. This channel is independent of the communication links between other nodes to avoid transmission resource conflicts. All dedicated bidirectional data transmission channels established in this way constitute a temporary point-to-point communication link covering all effective interaction node pairs within the search and rescue area.

[0024] Furthermore, based on the established temporary point-to-point communication links, each deployed node shares its unique identifier, all neighbor node identifiers recorded in the neighbor discovery message, and the status information of the established temporary point-to-point communication links with all directly connected neighbor deployed nodes through its own established links. After receiving this information, each neighbor node integrates it with the neighbor discovery messages, response messages, and link information it already possesses, removes duplicate connection relationships, and supplements information on indirect connection nodes that it has not detected, forming a comprehensive understanding of the connection relationships of all deployed nodes in the entire search and rescue area. Subsequently, each deployed node is treated as an independent network node, and each temporary point-to-point communication link is treated as a connection edge between nodes. The identity information of all nodes and the connection relationships between nodes are fully recorded in a structured data form, clearly presenting the direct connection nodes, indirect connection paths, and link status of each node, and finally constructing an initial topology structure that can comprehensively reflect the distribution and connection status of mobile targets.

[0025] Furthermore, based on the completed initial topology, each deployment node first parses the topology data to determine its specific location within the entire network, as well as the direct and indirect connection paths between itself and all other deployment nodes formed through temporary point-to-point communication links. A blank routing table with a uniform format is then created for each deployment node. This routing table contains three core fields: target node identifier, next-hop node identifier, and communication link identifier. Subsequently, according to the connection relationships defined in the initial topology, the shortest effective transmission path corresponding to each target node is queried one by one to determine the next-hop node identifier and the temporary point-to-point communication link identifier used in that path. This information is accurately entered into the routing table of the corresponding deployment node. After completion, the routing table information is verified to ensure that each target node has a corresponding valid path record without errors or missing entries. Once the routing tables of all deployment nodes have been filled and verified, each node can autonomously select the optimal communication path based on the information in the routing table. When the node location changes dynamically, the routing table can autonomously adjust the path information according to the update of the topology to ensure the continuity and stability of data transmission between nodes. At this point, all deployment nodes, temporary point-to-point communication links, and the initialized routing tables together form a fully functional mobile target ad hoc network.

[0026] In summary, this step involves defining the search and rescue area, using ground sensors and aerial reconnaissance equipment to identify, screen, and locate moving targets, assigning unique identifiers to eligible moving targets and defining them as deployment nodes, ensuring the validity and uniqueness of the basic nodes required for building the self-organizing network, and providing a reliable node foundation for all subsequent network construction operations.

[0027] In summary, this step enables the continuous transmission and reception of neighbor detection signaling through the radio frequency communication interface of the deployed nodes. After filtering out interference signals, valid identification information is parsed and extracted, and integrated to form a neighbor discovery message containing the identities of all detected neighbor nodes, providing initial identity recognition and information support for subsequent interactions between deployed nodes.

[0028] In summary, this step enables the deployed node to send neighbor response messages containing identity identifiers, confirmation feedback, and communication status to detected neighbor nodes, while simultaneously receiving and verifying response messages from other nodes. This ensures the integrity and accuracy of bidirectional interaction between nodes and provides an interaction basis for subsequent link configuration.

[0029] In summary, this step, by aggregating neighbor discovery and response messages from all nodes, comparing and identifying the bidirectional interaction relationships between nodes, selecting valid node pairs and establishing dedicated bidirectional data transmission channels, completes the collaborative link configuration and successfully constructs a temporary point-to-point communication link covering all valid interactive nodes.

[0030] In summary, this step, based on temporary point-to-point communication links, comprehensively grasps the connection relationships of all nodes through the sharing and integration of neighbor information between nodes. It constructs a structured initial topology with nodes as the core and links as the connecting edges, clearly presenting the distribution and connection status of mobile targets, and providing a key structural basis for routing table initialization.

[0031] In summary, this step clarifies the node locations and connection paths based on the initial topology, creates and populates a routing table containing the target node, next-hop node, and link identifier, and verifies the routing information to ensure its accuracy and effectiveness. This enables all deployed nodes to autonomously select communication paths, ultimately forming a mobile target ad hoc network with autonomous data transmission and dynamic adjustment capabilities, thus completing the closed loop of the entire network construction.

[0032] S2. Based on the self-organizing network, the deployment nodes are constructed with dual communication paths to obtain dual communication links in the search and rescue area; In this embodiment of the invention, the step of constructing dual-path communication for the deployed nodes based on the self-organizing network to obtain dual communication links in the search and rescue area includes: Configure a primary network interface and a backup network interface on the deployment node; Based on the current topology of the self-organizing network, two logically isolated data transmission paths are allocated to the deployment node; The connectivity status of the primary network interface is continuously monitored to obtain the real-time monitoring results of the self-organizing network; When the real-time monitoring result indicates that the connectivity is lost, the data stream is switched to the data transmission path corresponding to the backup network interface to obtain a dual communication link in the search and rescue area.

[0033] Specifically, the entire implementation process revolves around the construction of dual communication links in the search and rescue area. By configuring functionally independent primary and backup network interfaces on the deployment nodes, and allocating two logically isolated data transmission paths based on the current topology of the self-organizing network, the connectivity status of the primary network interface is continuously monitored to obtain real-time feedback. When the primary interface fails to connect, the data flow is immediately switched, and the transmission task is transferred to the path corresponding to the backup network interface. This ultimately forms a dual communication link that ensures communication continuity. Each step is progressive, ensuring the timeliness of link switching and the stability of network communication.

[0034] Furthermore, each deployment node's hardware architecture reserves two independent interface mounting slots, each embedding a performance-adapted wireless communication module. One module is explicitly designated as the primary network interface, and the other as the backup network interface. The primary network interface employs a high-frequency communication mode, which increases data transmission rate by shortening the signal wavelength to meet the rapid transmission needs of large amounts of real-time data during search and rescue operations. The backup network interface employs a low-frequency communication mode, utilizing a longer wavelength to enhance signal penetration, maintaining signal stability even in complex search and rescue environments with numerous obstacles. The two interfaces are connected to dedicated antennas facing different directions to avoid mutual interference during signal transmission. Simultaneously, the deployment node's system kernel configures unique identifiers for each interface. The primary network interface identifier is fixed to a specific character combination through system-level parameters, while the backup network interface identifier uses a completely distinct character combination, ensuring accurate system identification of both interfaces. After hardware installation and identifier configuration are completed, the node's built-in communication management program is activated. This program sends an activation command to the primary network interface, putting it into continuous operation, and simultaneously sends a standby command to the backup network interface, keeping it powered on and ready to respond to switching commands at any time.

[0035] Furthermore, by using the topology reading module of the deployed nodes, the system fully retrieves all connection relationships of deployed nodes, temporary point-to-point communication link status, and node location information recorded in the current topology of the ad hoc network. For each deployed node, two unrelated communication paths are selected from the topology data. The first path prioritizes temporary point-to-point communication links with short transmission distances, low link loads, and high historical transmission success rates, which are then sequentially connected to form an efficient primary path. This path is bound to the primary network interface. The second path avoids all intermediate nodes and communication links involved in the first path, selecting independent temporary point-to-point communication links to ensure that the two paths do not overlap in transmission path, forming a redundant backup path. This path is bound to the backup network interface. In the routing table of each intermediate node involved in the two paths, a unique path identifier is added. The routing entry corresponding to the primary path is marked with unique identification information, and the routing entry corresponding to the backup path is marked with another set of unique identification information. This allows the system to accurately distinguish between the two paths based on the identifiers during data forwarding, avoiding routing conflicts. Ultimately, this completes the allocation of two logically isolated data transmission paths for each deployed node.

[0036] Furthermore, the primary network interface initiates its built-in connectivity monitoring program, sending standardized heartbeat detection frames to the next-hop nodes in its bound data transmission path at fixed time intervals. This detection frame contains the sending node's unique identifier, the current transmission timestamp, and verification information calculated based on the data within the frame, ensuring the receiver can verify data integrity. Upon receiving the detection frame, the next-hop node immediately identifies the identifier within the frame. After confirming it belongs to a valid communication node, it extracts the verification information and compares it with its local calculation result. If the comparison matches, it generates a response frame containing its own identifier and confirmation of reception, and immediately sends it back to the sending node. The primary network interface's monitoring program records the time interval between sending detection frames and receiving response frames in real time, while continuously verifying the integrity of the information in the response frames. If a verified response frame is received within a specified time in multiple consecutive detection cycles, the primary network interface is considered to be in a normal connectivity state; if no response frame is received in a certain detection cycle, or the received response frame fails verification or exceeds the specified time range, the primary network interface is considered to have an abnormal connectivity state. All status information, detection results, and time records during the monitoring process are stored in the local status log of the deployment node in real time, forming a complete real-time monitoring result for the self-organizing network.

[0037] Furthermore, when the status monitoring program of the deployed node determines that the primary network interface has failed, it immediately sends a trigger signal to the link switching control module to initiate the switching process. The link switching control module first sends a shutdown command to the primary network interface, stopping its data transmission and reception functions, cutting off the data flow channel of the primary data transmission path, and simultaneously recording the time and status information of the primary interface failure. Subsequently, the link switching control module reads the configuration parameters and bound backup data transmission path information of the backup network interface, sends an activation command to the backup network interface, switching it from standby to normal operation, and enabling the routing entries of the backup data transmission path. Next, all data streams originally transmitted through the primary network interface, including real-time search and rescue data and node status information, are redirected to the backup network interface via the data forwarding module, and the backup data transmission path continues transmission, ensuring uninterrupted data flow. After the switch is completed, the link switching control module sends a path switching notification to all nodes in the ad hoc network that have a communication association with the deployed node, informing other nodes that the current communication path has been switched to the backup path, facilitating other nodes to synchronously adjust their routing configurations. At this time, the primary network interface enters the fault recording and troubleshooting state, while the backup network interface continues to undertake data transmission tasks. The two work together to form a dual communication link in the search and rescue area.

[0038] In summary, this step completed the hardware installation, mode configuration, identification setting, and status activation of the primary and backup network interfaces of the deployment node, ensuring that the two interfaces are functionally independent and free from signal interference, thus providing a hardware foundation for subsequent dual-path transmission and link switching.

[0039] In summary, this step, based on the current topology of the self-organizing network, filters and binds two unrelated communication paths for each deployment node, achieves logical isolation through routing identifiers, and completes the allocation of two logically isolated data transmission paths.

[0040] In summary, this step involves sending heartbeat monitoring frames, receiving response frames, and performing verification and judgment through the primary network interface, while recording the monitoring results in real time, thus forming a real-time monitoring result of the self-organizing network that reflects the connectivity status of the primary network interface.

[0041] In summary, this step triggers a link switching process when the primary network interface fails to connect, shutting down the primary interface and activating the backup interface, directing data flow to the backup path, and ultimately forming a dual communication link in the search and rescue area that ensures communication continuity.

[0042] S3. Perform time-series state trend deduction on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area; In this embodiment of the invention, the step of performing time-series state trend extrapolation on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area includes: The multidimensional state information of the deployment node is time-series aligned to obtain the state information sequence of the deployment node; Based on the state information sequence, forward prediction is performed on the deployment node to obtain the state prediction result of the deployment node; Based on the real-time observation data of the deployment node, the state prediction result is optimized and corrected to obtain the calibrated state prediction result of the deployment node. The calibrated state prediction results are vectorized to obtain the movement prediction vector of the search and rescue area.

[0043] Specifically, the entire implementation process revolves around the status analysis and movement prediction of deployment nodes. First, multi-dimensional status information of deployment nodes is collected and time-series aligned to form a coherent sequence of status information. Then, based on this sequence, historical change patterns are analyzed to make forward predictions and obtain status prediction results. Subsequently, real-time observation data is combined to correct prediction deviations and generate calibrated status prediction results. Finally, through standardized mapping, the calibrated prediction results are transformed into a combination of numerical values ​​in a fixed format, ultimately obtaining a movement prediction vector of the search and rescue area that reflects the future status changes of deployment nodes. Each step is progressive to ensure the accuracy and practicality of the prediction results.

[0044] Furthermore, comprehensive multi-dimensional status information of the deployed nodes is collected. This information covers key dimensions such as real-time node location, communication signal strength, remaining battery power, link connectivity, and data transmission rate. Information for each dimension is continuously collected by dedicated sensors built into the deployed nodes. Location information is captured by a satellite positioning module, signal strength is monitored by an RF sensor, remaining battery power is read by a power management module, and link connectivity and data transmission rate are statistically analyzed in real time by the communication interface. During the collection process, each sensor synchronously records the timestamp of the corresponding status information, accurate to the instant of the status change. A unified and fixed time interval is determined as the benchmark unit for time alignment. All multi-dimensional status information is precisely matched with the benchmark time interval according to their respective collection timestamps. For a certain dimension of status information not collected at the benchmark time point, the same dimension of status information from the two most recent valid collection times before and after the benchmark time point is selected, and linear interpolation is performed according to the trend between the two to supplement the complete status information of the benchmark time point, ensuring that each benchmark time point has complete and intact multi-dimensional status information. Following the chronological order of the baseline time points, the complete multidimensional status information corresponding to each time point is arranged sequentially to form a sequence of deployment node status information presented coherently along the timeline.

[0045] Furthermore, the historical change trajectories of state information in each dimension are completely extracted from the state information sequence, and the changing patterns of each dimension over time are analyzed. For example, in the node location dimension, the direction, speed, and turning characteristics of the horizontal and vertical coordinates; in the communication signal strength dimension, the fluctuation frequency, amplitude, and peak occurrence time patterns; in the remaining power dimension, the consumption rate and whether charging is available; in the link connectivity dimension, the stable duration and interruption frequency; and in the data transmission rate dimension, the peak, valley, and average level trends. Based on these extracted historical change patterns, the possible values ​​of each dimension's information at multiple consecutive reference time points in the future are deduced one by one. For example, based on the node's average movement speed and continuous movement direction over a period of time, the position coordinates of each reference time point in the future are determined; based on the periodic fluctuation pattern of signal strength, the signal strength value of each reference time point in the future is predicted; and based on the power consumption rate, the remaining power at each time point in the future is calculated. The future values ​​of all dimensions' information are integrated one by one according to the corresponding reference time points to ensure that each future time point contains complete multi-dimensional state prediction information, ultimately forming the state prediction results of the deployed nodes.

[0046] Furthermore, real-time observation data at the current reference time point is synchronously acquired through real-time monitoring devices on the deployment nodes. This real-time observation data is completely consistent with the multi-dimensional state information dimensions in the state information sequence, including the current real-time location, real-time communication signal strength, real-time remaining power, real-time link connectivity, and real-time data transmission rate. The predicted values ​​for each dimension corresponding to the current reference time point in the state prediction results are compared one by one with the synchronously acquired real-time observation data to clarify the differences between the predicted value and the real-time observation value for each dimension, including the direction and degree of the difference. Based on the differences in each dimension, the corresponding dimension values ​​for all future reference time points in the state prediction results are adjusted accordingly. For example, if there is a deviation between the current location prediction value and the real-time observation value, the location prediction value for each future reference time point is proportionally corrected according to the direction and magnitude of the deviation to ensure that the corrected prediction value better matches the actual movement trend; if the predicted value for a certain dimension is completely consistent with the real-time observation value, the predicted value for that dimension remains unchanged for all future time points. After a comprehensive adjustment of the future prediction values ​​for all dimensions, a more accurate calibrated state prediction result for the deployment nodes is obtained.

[0047] Furthermore, the actual numerical ranges of each dimension of information in the calibrated state prediction results are first clarified. For example, location information corresponds to the geographical boundary range of the search and rescue area, signal strength corresponds to the range of the maximum and minimum effective signal values ​​of the device, and remaining power corresponds to the range of the device's full-power and power-off values. A dedicated fixed mapping rule is assigned to each dimension of information, and the specific values ​​of each dimension are converted into a unified standard numerical form according to the mapping rule. For example, location coordinates are normalized according to the boundary extremes of the search and rescue area, converting them into standardized values ​​within a fixed interval; communication signal strength is converted into standardized values ​​according to the proportion of the device's maximum effective signal strength; and movement direction is converted into standardized values ​​within the corresponding interval according to the azimuth angle range. Following a preset fixed dimension order, all standardized values ​​at each future reference time point in the calibrated state prediction results are sequentially arranged to form a fixed-length numerical array. Each numerical array precisely corresponds to a complete state prediction at a future time point. All numerical arrays corresponding to future time points are combined to form a movement prediction vector for the search and rescue area that comprehensively reflects the future movement trajectory and state change trend of the deployed nodes.

[0048] In summary, this step completes the collection of multi-dimensional status information of deployment nodes, timestamp recording, baseline alignment and interpolation supplementation, and arranges them in chronological order to form a coherent and complete sequence of deployment node status information.

[0049] In summary, this step analyzes the historical change patterns of each dimension in the state information sequence, infers future values, and integrates them to obtain the state prediction results of the deployment nodes, which contain multi-dimensional state information at multiple future time points.

[0050] In summary, this step, by comparing the current real-time observation data with the corresponding predicted values, adjusts the future predicted values, corrects the prediction bias, and obtains more accurate calibrated state prediction results for the deployment nodes.

[0051] In summary, this step transforms the calibrated prediction results into a combination of numerical arrays by assigning mapping rules to each dimension and performing standardization, ultimately obtaining a movement prediction vector of the search and rescue area that reflects the future changing trend of the deployed nodes.

[0052] S4. Based on the motion prediction vector, perform path evolution on the sending node and receiving node to obtain the optimal communication path in the search and rescue area; In this embodiment of the invention, the step of performing path evolution on the sending and receiving nodes based on the mobility prediction vector to obtain the optimal communication path for the search and rescue area includes: Based on the motion prediction vector, the predicted motion trajectories of the sending node and the receiving node are extracted; The predicted motion trajectory is used to perform trajectory-guided path deduction to obtain candidate communication paths between the sending node and the receiving node; Obtain the velocity vectors and current distances of the sending node and the receiving node in the candidate communication path; Based on the velocity vector and the current distance, the reliability of the candidate communication path is quantitatively evaluated to obtain the reliability value of the candidate communication path; Based on the reliability value, the candidate communication path with the highest reliability is selected as the optimal communication path for the search and rescue area.

[0053] The formula for calculating the reliability value is as follows: ; In the formula, Indicates the candidate communication path Reliability value, This represents the preset reliability degradation coefficient. Indicates the candidate communication path The number of links in Indicates the candidate communication path Midlink The velocity vector of the sending node, Indicates the candidate communication path Midlink The velocity vector of the receiving node, Indicates the candidate communication path Midlink Current distance, Indicates An exponential function with base 0.

[0054] Specifically, the entire process revolves around selecting the optimal communication path in the search and rescue area based on the motion prediction vector. First, the predicted motion trajectory of the sending and receiving nodes is extracted from the motion prediction vector. Then, candidate communication paths are deduced based on the trajectory. Next, the velocity vector and current distance of the nodes in the path are obtained. The reliability of the candidate paths is evaluated by quantification using formulas. Finally, the most reliable path is selected as the optimal communication path. Each step is closely linked to ensure that the path selection is scientific and reliable.

[0055] Furthermore, the standardized state information of the sending and receiving nodes contained in the motion prediction vector is analyzed. This information covers key data such as position coordinates and movement direction at multiple future time points. The position coordinates of the sending node at each future time point are extracted in chronological order and then connected sequentially to form a continuous trajectory reflecting the future movement path of the sending node. The position coordinates of the receiving node at each future time point are extracted in the same way and concatenated to obtain the predicted motion trajectories of the sending and receiving nodes. The velocity vectors of the sending and receiving nodes are obtained by calculating the movement direction and speed from these predicted motion trajectories through position changes at adjacent time points, and the current distance is obtained by calculating the straight-line distance between the current positions of the sending and receiving nodes. These data are the core source for subsequent reliability formula calculations.

[0056] Furthermore, guided by the predicted movement trajectories of the sending and receiving nodes, and considering the distribution of other deployed nodes within the search and rescue area, possible communication paths connecting the sending and receiving nodes are deduced. During the deduction process, along the extension directions of the two predicted trajectories, deployed nodes distributed around the trajectories are preferentially selected as intermediate forwarding nodes to ensure that the paths can adapt to the future movement trends of the sending and receiving nodes, while avoiding potential node disconnection areas in the trajectories. This constructs multiple potential paths containing different combinations of intermediate nodes that can maintain connectivity as the nodes move. These paths collectively constitute candidate communication paths between the sending and receiving nodes. The number of links in each candidate communication path is determined by splitting the path into links and counting the total number of links, providing a basis for the values ​​of the parameters in the formula.

[0057] Furthermore, for each candidate communication path, a segment of the predicted motion trajectory of the sending node at the current time point is extracted. The direction and speed of movement of the sending node are calculated by the positional changes between two adjacent time points, and integrated to form the velocity vector of the sending node. The velocity vector at the current time point is extracted from the predicted motion trajectory of the receiving node in the same way. At the same time, the position coordinates of the sending node and the receiving node at the current time point are obtained. By calculating the straight-line distance between the two points, the current distance between the sending node and the receiving node is obtained, ensuring that each candidate communication path corresponds to a complete set of velocity vectors and current distance data. The preset reliability attenuation coefficient is pre-set by the system according to the communication requirements and environmental characteristics of the search and rescue scenario. These parameters are input into the formula for reliability calculation.

[0058] Furthermore, for each candidate communication path, the velocity vector and current distance are used to comprehensively analyze and calculate the reliability value according to a formula. This formula calculates the sum of the differences in velocity vectors between the sending and receiving nodes of each link, and combines this with the current distance to quantify the reliability of the candidate communication path in an exponential function form. When the sum of the differences in velocity vectors between the sending and receiving nodes of each link in the candidate communication path increases, the reliability value decreases exponentially, and the path reliability decreases; when the current distance of each link increases, the reliability value increases exponentially, and the path reliability improves. When the preset reliability attenuation coefficient increases, the same velocity vector difference and distance change will make the change in reliability value more significant, that is, the larger the attenuation coefficient, the more sensitive the reliability is to changes in velocity vector difference and distance. Through this calculation, the reliability value of each candidate communication path is finally obtained, which intuitively reflects its ability to maintain stable connectivity over a period of time.

[0059] Furthermore, the reliability values ​​of all candidate communication paths were collected, and these values ​​were compared one by one to identify the candidate communication path with the highest reliability value. The node connectivity, velocity vector adaptability, and current distance rationality of this path were then checked again to confirm that it could maintain stable connectivity during future movement and meet the rate and stability requirements of search and rescue data transmission. Finally, this candidate communication path with the highest reliability was determined as the optimal communication path for the search and rescue area.

[0060] In summary, this step extracts the position coordinates of the sending and receiving nodes from the motion prediction vector and concatenates them to obtain their respective predicted motion trajectories. At the same time, it obtains the basis for calculating the velocity vector and the current distance.

[0061] In summary, this step is guided by the prediction of motion trajectory, combines the distribution of deployed nodes to deduce and construct multiple candidate communication paths, and determines the value of the number of links in the formula.

[0062] In summary, this step extracts the velocity vector for each candidate communication path, calculates the current distance, and clarifies the setting method of the preset attenuation coefficient, thus completing all the preparation of the formula parameters.

[0063] In summary, this step uses a formula to comprehensively analyze the velocity vector and the current distance, quantifies the reliability value of each candidate communication path, and clarifies the trend of the reliability value.

[0064] In summary, this step compares the reliability values ​​of all candidate paths and, after verification, determines the optimal communication path as the one with the highest reliability.

[0065] S5. Based on the optimal communication path, dynamically adjust the active state of the dual communication links to obtain the target communication link in the search and rescue area. In this embodiment of the invention, the step of dynamically adjusting the active state of the dual communication links based on the optimal communication path to obtain the target communication link in the search and rescue area includes: Monitor the real-time transmission load of the primary link and the backup link in the dual communication links; Based on the node distribution of the optimal communication path, the real-time transmission load of the primary link is compared with the preset load balancing threshold to determine the risk of exceeding the limit. When the real-time transmission load of the primary link exceeds the preset load balancing threshold, a portion of the data transmission tasks in the data stream are allocated to the backup link. The primary link and the backup link, which are in a collaborative working state, are integrated and calibrated to obtain the target communication link in the search and rescue area.

[0066] Specifically, the entire implementation process revolves around the construction of target communication links in the search and rescue area. First, a dedicated module monitors the transmission load of the primary and backup links in real time. Then, based on the node distribution of the optimal communication path, the real-time load of the primary link is compared with a preset threshold to assess the risk of exceeding limits. When the load of the primary link exceeds the limit, a data diversion mechanism is activated to allocate some tasks to the backup link. Finally, the status of the two working links is integrated and labeled to form a target communication link that balances transmission efficiency and stability. Each link is closely connected to ensure balanced link load and smooth communication.

[0067] Furthermore, an independent load monitoring module is embedded in all deployed nodes within the dual communication links. This module is directly associated with the node's communication interface and can capture the entire data transmission process in real time. Each node on both the primary and backup links statistically analyzes the actual size of all data packets it receives and sends within a fixed time period, recording the start and end times of each data packet's transmission, as well as the number of successfully transmitted complete data frames, excluding invalid data that has failed to transmit or is corrupted. Each node on the primary link transmits information such as the total amount of data per unit time and the number of valid data frames to the link control center in real time via an internal dedicated channel. Nodes on the backup link also synchronize their statistical results to the control center at the same frequency and in the same format. After receiving the statistical data from all nodes on both links, the link control center accumulates the total amount of data per unit time for each link and, combined with the data transmission time period, calculates the actual transmission load value of the primary and backup links at the current moment. This value directly reflects the current data carrying capacity of the two links.

[0068] Furthermore, by retrieving complete node distribution information of the optimal communication path through the link management system, the total number of nodes in the path, the specific location of each node, the connection method between adjacent nodes, and the hardware processing capability parameters of the nodes are clearly understood. Based on this distribution information and the hardware configuration of each node, the maximum amount of data that a single node can continuously process under stable operating conditions is determined. Then, based on the tightness of the connections between nodes, the overall transmission capacity limit of the primary link is calculated. The preset load balancing threshold is determined comprehensively based on the total number of nodes in the primary link, the maximum capacity of a single node, and the overall transmission efficiency of the link. It is the maximum allowable load value to ensure that the link does not experience congestion and data loss. When performing over-limit risk comparison, the current real-time transmission load value of the primary link is directly compared with the preset load balancing threshold. At the same time, the judgment criteria are adjusted according to the density of node distribution. In sections with dense node distribution and redundant data processing capabilities, the comparison criteria are appropriately relaxed, allowing the load to approach the threshold. In sections with sparse node distribution and limited processing capabilities, the threshold is strictly followed. Once the real-time load exceeds the threshold, it is immediately determined that there is an over-limit risk, forming a clear over-limit risk comparison result.

[0069] Furthermore, when the risk comparison results show that the real-time transmission load of the primary link exceeds the preset load balancing threshold, the built-in traffic splitting mechanism in the link control center will be immediately activated. The splitting mechanism first classifies all data streams currently being transmitted on the primary link, dividing them into different levels based on their urgency and importance. Urgent and non-delayable data, such as data used for search and rescue command transmission and life signal feedback, are retained for transmission on the primary link. Non-urgent and delayable data, such as data backup for environmental monitoring and non-critical status reporting, are marked as data to be transferred and given a unique splitting identifier. The link control center sends a clear splitting instruction to the starting node of the primary link, detailing the splitting identifier of the data to be transferred, the total amount of data, and the target receiving node information. Upon receiving the instruction, the starting node of the primary link immediately updates its routing table, redirecting the data marked as to be transferred to the access node of the backup link, while simultaneously suspending the transmission of this data to subsequent nodes on the primary link. After receiving the data to be transferred, the access node of the backup link quickly transmits the data to the target node according to its own preset transmission path, ensuring that some data transmission tasks are smoothly and without interruption transferred to the backup link, thus achieving load sharing between the two links.

[0070] Furthermore, the link control center collects real-time status information of the primary and backup links in collaborative operation, including the current transmission rate, data transmission success rate, connectivity status of all nodes, and whether data congestion exists. A unified link identifier is assigned to both links; the primary link's identifier uses a format associated with the backup link but with a different prefix, ensuring quick differentiation in subsequent management. In the network topology diagram, the transmission path for emergency data handled by the primary link is marked in a unique format, while the transmission path for non-emergency data handled by the backup link is also clearly marked, clearly showing the coverage area, data transmission direction, and intersection nodes of the two links. For the intersection nodes of the two links, a data priority processing mechanism is set up. Through the node's built-in priority judgment program, it ensures that emergency data transmitted by the primary link can preferentially occupy the node's processing resources and transmission channels, avoiding conflicts with data from the backup link. The transmission status logs of the primary and backup links are synchronized, and all data transmission records of the two links are calibrated according to a unified time standard to eliminate data transmission time differences and ensure log consistency. Through the above integration and calibration operations, a target communication link in the search and rescue area is finally formed, which includes the primary and backup link collaborative working mode, data allocation rules, priority mechanism, and overall transmission capability parameters.

[0071] In summary, this step successfully obtained the real-time transmission load of the primary and backup links by deploying load monitoring modules at each node of the dual communication links, and by statistically summarizing the amount of data per unit time.

[0072] In summary, this step retrieves the node distribution information of the optimal communication path, determines the carrying capacity of the primary link, compares the real-time load with the preset threshold, and combines the node distribution adjustment standard to complete the over-limit risk comparison of the primary link.

[0073] In summary, this step activates the traffic splitting mechanism after the primary link exceeds its load limit, classifies and marks the data, sends splitting instructions, and directs non-urgent data to the backup link, thus realizing the allocation of some data transmission tasks to the backup link.

[0074] In summary, this step collects the real-time status of the two collaborative links, assigns unified identifiers, marks transmission paths, sets priority mechanisms, and synchronizes logs, completing the integration and calibration of the primary and backup links and obtaining the target communication links in the search and rescue area.

[0075] S6. Based on the optimal communication path, the search and rescue mission data is forwarded to the deployment node through the target communication link to complete the search and rescue mission in the search and rescue area.

[0076] In this embodiment of the invention, the step of forwarding search and rescue mission data to the deployment node through the target communication link based on the optimal communication path to complete the search and rescue mission in the search and rescue area includes: The search and rescue mission data to be transmitted is formatted and encapsulated to obtain a data packet of the search and rescue mission data; Based on the node sequence of the optimal communication path, the data packet is forwarded to the next deployed node through the target communication link; When the data packet is forwarded to the receiving node of the optimal communication path, the data packet is decapsulated to obtain the search and rescue mission data of the search and rescue area; The search and rescue mission is completed in response to search and rescue instructions detected in the search and rescue mission data.

[0077] Specifically, the entire implementation process revolves around the transmission and execution of search and rescue mission data. First, the original search and rescue mission data is standardized, formatted, and encapsulated to form a complete data packet. Then, based on the node sequence of the optimal communication path, the data packet is forwarded node by node through the target communication link. When the data packet arrives at the receiving node, it is decapsulated to restore the original data. Finally, the search and rescue instructions in the data are identified and resources are scheduled for execution to ensure the accurate implementation of the search and rescue mission. Each link is interconnected, ensuring the integrity of data transmission and the effectiveness of mission execution.

[0078] Furthermore, a comprehensive collection of search and rescue mission data to be transmitted is conducted. This data encompasses various key information, including the approximate location of the search and rescue target, specific rescue action plans, details of equipment scheduling involved in the rescue, on-site safety warnings, and material supply requirements. The data is categorized and organized according to its purpose and attributes, with clear format standards and core elements for each type. A pre-defined unified data encapsulation structure is used to process the categorized data. This structure is fixedly divided into three parts: header, data body, and trailer. The header specifically records the unique identifiers of the sending and receiving nodes, the specific data type, and the execution time of the encapsulation operation. The data body completely carries the original search and rescue mission data after classification and organization. The trailer contains verification information obtained by performing byte-by-byte verification calculations on all contents of the header and data body, used to verify whether the data remains intact during transmission. During the encapsulation operation, the corresponding content is filled in sequentially according to a fixed order of header, data body, and trailer. Through a dedicated encapsulation program built into the deployment node, the three parts of data are seamlessly spliced ​​and integrated into a continuous binary data stream, ultimately forming a data packet of search and rescue mission data with a unified structure, no missing information, and ready for direct transmission.

[0079] Furthermore, by retrieving the complete sequence of deployed nodes arranged sequentially in the optimal communication path through the link management system, the specific position of the deployment node currently responsible for forwarding data packets within the sequence, as well as the unique identifier and detailed communication address of the next deployment node immediately adjacent to it, are clearly identified. The current operating status of the target communication link is queried in real time, including the transmission load and connectivity stability of the primary and backup links. If the transmission load of the primary link is within the normal range and the connectivity is stable, the primary link is prioritized for data packet forwarding. If the primary link is still under load distribution or its connectivity fluctuates, the backup link with the better current status is selected for forwarding according to the preset link allocation rules. The currently deployed node sends targeted data through its communication interface bound to the target communication link, based on the unique identifier of the receiving node. Before sending, a link status detection program is initiated, sending a brief connectivity test signal to the next deployment node in the target sequence. After confirming that the other party is in a normal receiving state and the link is available, the complete data packet is accurately forwarded to the next deployment node in the node sequence through the designated transmission path of the target communication link.

[0080] Furthermore, when the data packet is transmitted to the receiving node of the optimal communication path, the receiving node's communication interface immediately receives the data packet and temporarily stores it in the local buffer. First, the check information at the end of the data packet is extracted, and at the same time, the built-in check calculation program is started to recalculate the header and data body of the data packet byte by byte. The newly calculated check result is compared bit by bit with the extracted tail check information. If the two are completely consistent, it is determined that the data packet has not been lost, tampered with, or damaged during transmission, and the check passes; if there is a discrepancy, the data packet is determined to be invalid and a retransmission mechanism is triggered. After the check passes, the decapsulation process is performed according to the fixed structure order at the time of encapsulation. First, the header information of the data packet is parsed to extract key auxiliary information such as the sending node identifier, data type, and encapsulation time, and these are recorded and archived. Then, the original encapsulated search and rescue mission data is completely extracted from the data body. Finally, all the auxiliary information at the header and tail is discarded, and only the core search and rescue mission data content is retained. Through this series of standardized operations, the initial search and rescue mission data of the search and rescue area is completely restored.

[0081] Furthermore, the built-in command monitoring module of the receiving node remains continuously operational, comprehensively scanning the decapsulated and restored search and rescue mission data to accurately identify various search and rescue commands contained therein. It clarifies the specific rescue action type corresponding to each command, such as a comprehensive search of a designated area, precise location of suspected targets, deployment of emergency supplies to designated locations, and organized evacuation of trapped personnel. Based on the identified command content, the corresponding mission execution system is automatically activated. The system sends start or dispatch signals to relevant rescue equipment within the search and rescue area according to the parameters set in the command. Simultaneously, it pushes detailed mission execution procedures and precautions to the terminals of personnel involved in the rescue. For example, based on the search area description in the command, it plans an efficient movement route and synchronizes it to the rescue personnel's terminals. It also activates corresponding drones, rescue robots, and other equipment according to equipment dispatch instructions and sets their operating parameters. During mission execution, the execution system collects real-time feedback information on the operating status of each device, the progress of rescue personnel, and the on-site environment, dynamically monitoring the execution process to ensure that all actions strictly follow the requirements of the search and rescue commands until all rescue operations corresponding to the commands are completed, successfully achieving the search and rescue mission objectives.

[0082] In summary, this step categorizes and organizes various search and rescue mission data, fills in header, data body, and tail information according to a fixed structure, and integrates them through a packaging program, successfully obtaining a data package with a complete structure of search and rescue mission data.

[0083] In summary, this step retrieves the node sequence to determine the forwarding path, queries the target communication link status to select a suitable link, and forwards the data packet after connectivity testing, thus completing the transmission of the data packet to the next deployment node.

[0084] In summary, this step involves the receiving node first verifying the integrity of the data packet, then parsing and extracting the core data according to the encapsulation structure, discarding auxiliary information, and successfully obtaining the search and rescue mission data for the search and rescue area.

[0085] In summary, this step involves the monitoring module identifying search and rescue commands, initiating the execution system to schedule resources, dynamically monitoring the execution process, and ultimately responding to the commands to complete the search and rescue mission.

[0086] Example 2 like Figure 2 As shown in the figure, this embodiment also provides a functional block diagram of a multi-dimensional mobile target self-organizing network system based on dual links.

[0087] The dual-link-based multidimensional mobile target ad hoc network system 100 described in this embodiment can be installed in an electronic device. Depending on the functions implemented, the dual-link-based multidimensional mobile target ad hoc network system 100 may include an ad hoc network construction module 101, a dual communication link establishment module 102, a temporal situational analysis module 103, an optimal path evolution module 104, a target communication link determination module 105, and a task execution module 106. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0088] In this embodiment, the functions of each module / unit are as follows: The self-organizing network construction module 101 is used to construct a self-organizing network of the mobile target in the search and rescue area, using the mobile target as the deployment node; The dual communication link building module 102 is used to construct dual communication paths for the deployment nodes based on the self-organizing network, thereby obtaining dual communication links in the search and rescue area. The time-series situational simulation module 103 is used to perform time-series state trend simulation on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area. The optimal path evolution module 104 is used to perform weighted path evolution on the sending node and the receiving node based on the movement prediction vector to obtain the optimal communication path in the search and rescue area. The target communication link determination module 105 is used to dynamically adjust the active status of the dual communication links based on the optimal communication path to obtain the target communication link of the search and rescue area. The task execution module 106 is used to forward search and rescue task data to the deployment node through the target communication link based on the optimal communication path, thereby completing the search and rescue task in the search and rescue area.

[0089] In detail, each module in the dual-link-based multidimensional mobile target ad hoc network system 100 described in this embodiment of the invention uses the same technical means as the dual-link-based multidimensional mobile target ad hoc network method described in Embodiments 1 and 2, and can produce the same technical effect, which will not be repeated here.

[0090] In the several embodiments provided by this invention, it should be understood that the disclosed electronic devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0091] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0093] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0094] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for multi-dimensional mobile target ad hoc networking based on dual links, characterized in that, The method includes: S1. Within the search and rescue area, construct an ad hoc network of the mobile targets, using them as deployment nodes; S2. Based on the self-organizing network, the deployment nodes are constructed with dual communication paths to obtain dual communication links in the search and rescue area; S3. Perform time-series state trend deduction on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area; S4. Based on the motion prediction vector, perform path evolution on the sending node and receiving node to obtain the optimal communication path in the search and rescue area; S5. Based on the optimal communication path, dynamically adjust the active state of the dual communication links to obtain the target communication link in the search and rescue area. S6. Based on the optimal communication path, the search and rescue mission data is forwarded to the deployment node through the target communication link to complete the search and rescue mission in the search and rescue area.

2. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of constructing an ad hoc network of mobile targets within the search and rescue area, using these mobile targets as deployment nodes, includes: Use moving targets within the search and rescue area as deployment nodes; The neighbor detection signaling of the deployed node is detected through the wireless communication interface, and the neighbor discovery message of the deployed node is obtained. Receive neighbor response messages between the deployed nodes; By performing coordinated link configuration on the neighbor discovery message and the neighbor response message, a temporary point-to-point communication link in the search and rescue area is obtained. Based on the temporary point-to-point communication link and the distributed route discovery process, the initial topology of the mobile target is constructed; Based on the initial topology, the routing tables of the deployed nodes are initialized to obtain the self-organizing network of the mobile target.

3. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of constructing dual-path communication for the deployed nodes based on the self-organizing network to obtain dual communication links in the search and rescue area includes: Configure a primary network interface and a backup network interface on the deployment node; Based on the current topology of the self-organizing network, two logically isolated data transmission paths are allocated to the deployment node; The connectivity status of the primary network interface is continuously monitored to obtain the real-time monitoring results of the self-organizing network; When the real-time monitoring result indicates that the connectivity is lost, the data stream is switched to the data transmission path corresponding to the backup network interface to obtain a dual communication link in the search and rescue area.

4. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of performing time-series state trend extrapolation on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area includes: The multidimensional state information of the deployment node is time-series aligned to obtain the state information sequence of the deployment node; Based on the state information sequence, forward prediction is performed on the deployment node to obtain the state prediction result of the deployment node; Based on the real-time observation data of the deployment node, the state prediction result is optimized and corrected to obtain the calibrated state prediction result of the deployment node. The calibrated state prediction results are vectorized to obtain the movement prediction vector of the search and rescue area.

5. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of performing path evolution on the sending and receiving nodes based on the motion prediction vector to obtain the optimal communication path in the search and rescue area includes: Based on the motion prediction vector, the predicted motion trajectories of the sending node and the receiving node are extracted; The predicted motion trajectory is used to perform trajectory-guided path deduction to obtain candidate communication paths between the sending node and the receiving node; Obtain the velocity vectors and current distances of the sending node and the receiving node in the candidate communication path; Based on the velocity vector and the current distance, the reliability of the candidate communication path is quantitatively evaluated to obtain the reliability value of the candidate communication path; Based on the reliability value, the candidate communication path with the highest reliability is selected as the optimal communication path for the search and rescue area.

6. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 5, characterized in that, The formula for calculating the reliability value is as follows: ； In the formula, Indicates the candidate communication path Reliability value, This represents the preset reliability degradation coefficient. Indicates the candidate communication path The number of links in Indicates the candidate communication path Midlink The velocity vector of the sending node, Indicates the candidate communication path Midlink The velocity vector of the receiving node, Indicates the candidate communication path Midlink Current distance, Indicates An exponential function with base 0.

7. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of dynamically adjusting the active status of the dual communication links based on the optimal communication path to obtain the target communication link in the search and rescue area includes: Monitor the real-time transmission load of the primary link and the backup link in the dual communication links; Based on the node distribution of the optimal communication path, the real-time transmission load of the primary link is compared with the preset load balancing threshold to determine the risk of exceeding the limit. When the real-time transmission load of the primary link exceeds the preset load balancing threshold, a portion of the data transmission tasks in the data stream are allocated to the backup link. The primary link and the backup link, which are in a collaborative working state, are integrated and calibrated to obtain the target communication link in the search and rescue area.

8. The multi-dimensional mobile target ad hoc network method based on dual links as described in claim 1, characterized in that, The step of forwarding search and rescue mission data to the deployed node through the target communication link based on the optimal communication path to complete the search and rescue mission in the search and rescue area includes: The search and rescue mission data to be transmitted is formatted and encapsulated to obtain a data packet of the search and rescue mission data; Based on the node sequence of the optimal communication path, the data packet is forwarded to the next deployed node through the target communication link; When the data packet is forwarded to the receiving node of the optimal communication path, the data packet is decapsulated to obtain the search and rescue mission data of the search and rescue area; The search and rescue mission is completed in response to search and rescue instructions detected in the search and rescue mission data.

9. A multi-dimensional mobile target ad hoc network system based on dual links, characterized in that, include: The self-organizing network construction module is used to construct a self-organizing network of the mobile target in the search and rescue area, using the mobile target as the deployment node; A dual communication link construction module is used to construct dual communication paths for the deployment nodes based on the self-organizing network, thereby obtaining dual communication links in the search and rescue area. The temporal situation simulation module is used to perform temporal state trend simulation on the multi-dimensional state information of the deployed nodes to obtain the movement prediction vector of the search and rescue area. The optimal path evolution module is used to perform weighted path evolution on the sending node and the receiving node based on the movement prediction vector to obtain the optimal communication path in the search and rescue area. The target communication link determination module is used to dynamically adjust the active status of the dual communication links based on the optimal communication path to obtain the target communication link in the search and rescue area. The task execution module is used to forward search and rescue task data to the deployment node through the target communication link based on the optimal communication path, thereby completing the search and rescue task in the search and rescue area.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 8.

Images