Satellite communication gateway control method and system, electronic device and storage medium

Abstract

The present application relates to the technical field of satellite communication, and especially relates to a satellite communication gateway control method and system, an electronic device and a storage medium. The method generates a field dependency graph by extracting the target service field of an emergency data packet, performs importance scoring and then performs segmented packaging, calculates a candidate frequency band signal quality prediction value based on antenna attitude parameters and electromagnetic interference characteristics and establishes a satellite communication link, constructs a transmission dependency tree based on the field dependency graph and performs topological sorting to obtain a transmission sequence, sends the packaged segments according to the transmission sequence and monitors the transmission state, and when the transmission state indicator is lower than a threshold value, adjusts the importance score based on the characteristics of the packaged segments, thereby improving the reliability and transmission efficiency of emergency communication in a network interruption environment.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to satellite communication gateway control methods, systems, electronic devices, and storage media. Background Technology

[0002] In emergency command scenarios, when conventional terrestrial communication networks are disrupted due to disasters or faults, satellite communication gateways become the core equipment for ensuring the transmission of command instructions and on-site data. Existing satellite communication gateway control methods typically employ a fixed data transmission mode, directly packaging emergency data messages generated by service terminals into uniformly formatted satellite data frames and transmitting them continuously through preset satellite communication frequency bands. This conventional approach focuses on maintaining the physical connectivity of the link, but lacks fine-grained processing of data content differences and transmission priorities.

[0003] The shortcomings of existing practices lie in low data transmission efficiency and a lack of targeted optimization for the payload. Emergency data messages contain various service fields, such as location information, status parameters, and command codes, with significantly different importance and real-time requirements. Existing technologies often treat all fields as equally important, indiscriminately packaging and sending them together. This makes important information susceptible to interference from secondary information during transmission, especially in bandwidth-constrained satellite channel environments, where redundant data can cause transmission delays or even loss of critical fields. Another shortcoming of existing practices is the lack of adaptive adjustment capabilities in establishing and maintaining satellite communication links. Existing methods typically rely on fixed frequency band selection and static antenna configurations. When encountering sudden electromagnetic interference or changes in weather conditions, signal quality may deteriorate sharply, but gateway control methods cannot proactively predict or dynamically switch to a better frequency band. Furthermore, once packet loss or bit errors occur during transmission, existing technologies often only employ simple retransmission mechanisms, failing to dynamically optimize the transmission strategy based on the actual value of the data fields. This results in limited channel resources being consumed by ineffective repeated transmissions. Summary of the Invention

[0004] The embodiments of the present invention provide a satellite communication gateway control method, system, electronic device and storage medium, which can solve the problems in the prior art.

[0005] A first aspect of the present invention provides a satellite communication gateway control method, comprising: Obtain emergency data packets sent by local service terminals; Extract the target business fields from the emergency data message to generate a field dependency graph. Based on the field dependency graph, score the importance of each field. Then, segment and encapsulate the target business fields according to the importance scores to obtain multiple encapsulation segments. Based on antenna attitude parameters and electromagnetic interference characteristics, predictive signal quality values ​​for multiple candidate frequency bands are calculated. Signal scanning is then performed sequentially in each candidate frequency band according to the order of the predicted signal quality values ​​to establish a satellite communication link. Based on the field dependency graph, the multiple encapsulation segments are constructed into a transport dependency tree, and the transport dependency tree is topologically sorted to obtain a transport sequence; The encapsulation segment is transmitted through the satellite communication link according to the transmission sequence. The transmission status of each encapsulation segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulation segment.

[0006] Extract the target business fields from the emergency data message to generate a field dependency graph. Based on the field dependency graph, score the importance of each field. Then, segment and encapsulate the target business fields according to the importance scores to obtain multiple encapsulation segments, including: Parse the header and payload of the emergency data message to extract the target business fields that carry business semantics; The semantic tags and data type attributes of each field are extracted by traversing the target business fields. The semantic tags are matched against a preset field association rule library. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated. For each field in the field dependency graph, calculate the influence range value of the field in the dependency propagation path and the dependency depth value of the field in the dependency propagation path, and calculate the dependency strength coefficient of each field based on the influence range value and the dependency depth value. Based on the dependency strength coefficient and the position weight of the target business field in the emergency data message, an importance score is given to each field; The target business fields are sorted according to their importance scores, and the sorted target business fields are sequentially divided according to a preset encapsulation segment length threshold to generate multiple encapsulation segments.

[0007] The target business fields are traversed to extract semantic tags and data type attributes for each field. Based on the semantic tags, a preset field association rule base is matched. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated, including: Traverse the target business fields, parse the field name and field value format of each field, extract keywords representing business meaning from the field name as semantic tags, and identify data type attributes from the field value format; The semantic tags of the target business field are matched one by one with the association rules in the field association rule base. When the semantic tag of any target business field is consistent with the source semantic tag of the association rule, the target business field corresponding to the target semantic tag defined by the association rule is found, and a dependency edge is established between the target business field and the target business field corresponding to any target semantic tag. The direction of the dependency edge is determined by the dependency direction defined by the association rule. The dependency weight is calculated based on the compatibility of the data type attributes of any target business field with the target business field corresponding to the target semantic tag; Generate a field dependency graph based on all target business fields, the dependent edges, and the dependent weights.

[0008] Based on antenna attitude parameters and electromagnetic interference characteristics, predictive signal quality values ​​for multiple candidate frequency bands are calculated. Signal scanning is then performed sequentially in each candidate frequency band according to the order of these predicted signal quality values ​​to establish a satellite communication link. This includes: The spatial geometric relationship between the antenna beam coverage area and the preset satellite orbit position is calculated based on the antenna attitude parameters. Spectral analysis of electromagnetic signals in the environment is performed to identify the frequency distribution of interference sources and the intensity of interference signals in each frequency band, generating electromagnetic interference characteristics. For each candidate frequency band, the antenna gain correction coefficient is calculated based on the spatial geometric relationship, and the interference suppression factor is calculated based on the interference signal strength corresponding to the candidate frequency band in the electromagnetic interference characteristics. Based on the antenna gain correction coefficient and the interference suppression factor, the predicted signal quality value of the candidate frequency band is calculated, and multiple candidate frequency bands are sorted according to the predicted signal quality value to generate a frequency band scanning sequence. Signal scanning operations are performed sequentially in each candidate frequency band according to the frequency band scanning sequence. When a satellite signal that meets the signal strength threshold is detected in any candidate frequency band, the center frequency and signal characteristic parameters of that candidate frequency band are recorded. Configure the operating parameters of the radio frequency transceiver module of the communication gateway based on the center frequency and signal characteristic parameters, and establish a satellite communication link in any candidate frequency band.

[0009] Based on the field dependency graph, the multiple encapsulation segments are constructed into a transport dependency tree, and the transport dependency tree is topologically sorted to obtain a transport sequence, including: Read the dependency descriptors of each encapsulation segment; For each encapsulation segment, based on the predecessor dependency field recorded in the dependency descriptor, the encapsulation segment to which the predecessor dependency field belongs is found in the field dependency graph and used as the parent node encapsulation segment of the current encapsulation segment. Based on the subsequent dependent field recorded in the dependency descriptor, the encapsulation segment to which the subsequent dependent field belongs is found in the field dependency graph as the child node encapsulation segment of the current encapsulation segment. Based on the association between the parent node encapsulation segment and the child node encapsulation segment of all encapsulation segments, a transmission dependency tree is generated. In the transmission dependency tree, there are directed edges between the parent node encapsulation segment and the child node encapsulation segment, and the direction of the directed edges is from the parent node encapsulation segment to the child node encapsulation segment. Calculate the dependency level depth of each encapsulation segment in the transport dependency tree. For multiple encapsulation segments with the same dependency level depth, calculate the intra-layer priority based on the sum of the dependency weights of the fields contained in each of the multiple encapsulation segments in the field dependency graph. The transmission dependency tree is topologically sorted based on the dependency level depth and the intra-layer priority to generate a transmission sequence.

[0010] Based on the dependency level depth and the intra-level priority, the transmission dependency tree is topologically sorted to generate a transmission sequence, including: Traverse all encapsulation segments in the transport dependency tree and divide all encapsulation segments into multiple level groups according to the dependency level depth value. The encapsulation segments in the level group have the same dependency level depth value. For each level group, the dependency correlation degree between the encapsulated segments within the level group is calculated. The dependency correlation degree is used to quantify the tightness of the cross-encapsulated segment dependency relationship between the fields contained in the encapsulated segments within the level group in the field dependency relationship graph. The encapsulation segments within the hierarchical group are clustered and grouped according to the dependency correlation degree to obtain multiple cluster subgroups. Within each cluster subgroup, the encapsulation segments are arranged according to the intra-layer priority value, which serves as the basis for determining the arrangement position of the encapsulation segment within the cluster subgroup. The expansion order of each level group is determined according to the dependency level depth value, and the encapsulation segments in each cluster subgroup are added to the candidate transmission sequence in order of their arrangement position. The transmission sequence is obtained by verifying that the dependency relationship between adjacent encapsulation segments in the candidate transmission sequence satisfies the constraint that the fields contained in the subsequent encapsulation segment depend on the fields contained in the preceding encapsulation segment.

[0011] The encapsulated segments are transmitted via the satellite communication link according to the transmission sequence. The transmission status of each encapsulated segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulated segments, including: The encapsulated segments are transmitted sequentially through the satellite communication link in the order determined by the transmission sequence, and transmission status parameters are collected in real time during the transmission of each encapsulated segment. The transmission status index of each encapsulation segment is calculated based on the transmission status parameters. The transmission status index is used to quantitatively characterize the stability of the transmission quality of the encapsulation segment in the satellite communication link. Determine whether the transmission status indicator is lower than a preset threshold. When the transmission status indicator is lower than the preset threshold, extract the encapsulation segment features of the encapsulation segment whose transmission status indicator is lower than the preset threshold. A transmission impact factor is calculated based on the characteristics of the encapsulation segment, and an importance adjustment is calculated based on the transmission impact factor. The importance adjustment is positively correlated with the transmission impact factor. The importance adjustment amount is added to the original importance score of the encapsulation segment whose transmission status index is lower than the preset threshold to generate the adjusted importance score.

[0012] A second aspect of the present invention provides a satellite communication gateway control system, comprising: The data acquisition unit is used to acquire emergency data messages sent by local business terminals; The field processing unit is used to extract the target business fields in the emergency data message to generate a field dependency graph, score the importance of each field based on the field dependency graph, and encapsulate the target business fields into multiple encapsulation segments according to the importance scores. The link establishment unit is used to calculate the predicted signal quality values ​​of multiple candidate frequency bands based on antenna attitude parameters and electromagnetic interference characteristics, and to perform signal scanning in each candidate frequency band in order of the predicted signal quality values ​​to establish a satellite communication link. A transmission sequence unit is used to construct a transmission dependency tree from the multiple encapsulation segments based on the field dependency graph, and to perform topological sorting on the transmission dependency tree to obtain a transmission sequence. The transmission monitoring unit is used to send the encapsulation segment through the satellite communication link according to the transmission sequence, monitor the transmission status of each encapsulation segment, and adjust the importance score based on the characteristics of the encapsulation segment when the transmission status index is lower than a preset threshold.

[0013] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0015] This invention significantly improves the reliability and transmission efficiency of emergency command satellite communications in network outage environments. By extracting target service fields from emergency data messages and constructing a field dependency graph, it is possible to accurately score the importance of each field. Based on the scoring results, differentiated encapsulation is implemented to ensure that high-priority service data is segmented, encapsulated, and transmitted preferentially under limited bandwidth conditions, avoiding the loss or delay of critical information and ensuring the timeliness of command decisions from the ground up.

[0016] This invention predicts the signal quality of candidate frequency bands based on antenna attitude parameters and electromagnetic interference characteristics, and performs frequency band scanning sequentially according to the predicted values. It can quickly lock the optimal communication frequency band and establish a satellite link in complex electromagnetic environments, significantly shortening the link establishment time, reducing the energy consumption and latency caused by frequent scanning, and improving the gateway's adaptive access capability in emergency disconnection scenarios.

[0017] This invention utilizes a field dependency graph to construct a transmission dependency tree and performs topology sorting to generate a transmission sequence. This ensures that the transmission order of encapsulation segments strictly follows the logical dependencies of the business data, preventing parsing failures or duplicate requests at the receiving end due to disordered order, thereby reducing retransmissions and bandwidth waste. Simultaneously, it monitors the transmission status of each encapsulation segment in real time. When the status indicator falls below a preset threshold, it automatically adjusts the importance score of the corresponding field, dynamically optimizing the subsequent transmission priority. This allows the system to adapt to channel fluctuations and interference changes, continuously maintaining priority for the transmission and reception of high-value data, and enhancing the overall communication link's anti-interference capability and task completion rate. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the satellite communication gateway control method according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the process of determining multiple encapsulation segments according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0021] Figure 1This is a flowchart illustrating the satellite communication gateway control method according to an embodiment of the present invention. Figure 1 As shown, the method includes: Obtain emergency data packets sent by local service terminals; Extract the target business fields from the emergency data message to generate a field dependency graph. Based on the field dependency graph, score the importance of each field. Then, segment and encapsulate the target business fields according to the importance scores to obtain multiple encapsulation segments. Based on antenna attitude parameters and electromagnetic interference characteristics, the predicted signal quality values ​​of multiple candidate frequency bands are calculated, and signal scanning is performed in each candidate frequency band in order of the predicted signal quality values ​​to establish a satellite communication link. Based on the field dependency graph, the multiple encapsulation segments are constructed into a transport dependency tree, and the transport dependency tree is topologically sorted to obtain a transport sequence; The encapsulation segment is transmitted through the satellite communication link according to the transmission sequence. The transmission status of each encapsulation segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulation segment.

[0022] Figure 2 This is a flowchart illustrating the process of determining multiple encapsulation segments according to an embodiment of the present invention. Figure 2 As shown, target business fields are extracted from the emergency data message to generate a field dependency graph. Based on the field dependency graph, each field is scored for importance. The target business fields are then segmented and encapsulated according to the importance scores to obtain multiple encapsulation segments, including: Parse the header and payload of the emergency data message to extract the target business fields that carry business semantics; The semantic tags and data type attributes of each field are extracted by traversing the target business fields. The semantic tags are matched against a preset field association rule library. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated. For each field in the field dependency graph, calculate the influence range value of the field in the dependency propagation path and the dependency depth value of the field in the dependency propagation path, and calculate the dependency strength coefficient of each field based on the influence range value and the dependency depth value. Based on the dependency strength coefficient and the position weight of the target business field in the emergency data message, an importance score is given to each field; The target business fields are sorted according to their importance scores, and the sorted target business fields are sequentially divided according to a preset encapsulation segment length threshold to generate multiple encapsulation segments.

[0023] In network outage emergency scenarios, emergency data packets often contain multiple types of business fields. These fields have complex semantic relationships, directly affecting the priority arrangement of subsequent transmissions. For emergency data packets, structured parsing is first performed on the header and payload areas of the packet. The header area typically contains control fields such as packet type identifier, timestamp, source address, and destination address; the payload area carries specific business semantic content, such as location coordinates, personnel status, and resource scheduling instructions. During the parsing process, only the target business fields carrying business semantics are extracted, filtering out pure link control fields or padding fields, thereby narrowing the set of fields for subsequent processing to the effective set of fields that truly affect emergency decisions.

[0024] After field extraction, all target business fields are traversed, and two types of attributes are extracted for each field: semantic tags and data type attributes. Semantic tags describe the business meaning of the field, such as location information, personnel number, event level, etc.; data type attributes describe the encoding format of the field, such as integer, floating-point, enumeration, or string. The extracted semantic tags are matched against a pre-built field association rule base. The field association rule base is pre-constructed based on emergency command business scenarios and records the rules that exist between different semantic tags. For example, resource scheduling instructions semantically depend on event level and location information, and personnel status depends on personnel number, etc. Based on the matching results, the direction and dependency weight of the dependency edges between each field are determined. The dependency weight reflects the tightness of the semantic association between two fields and is determined by the pre-built weight values ​​in the rule base and the data type compatibility. All fields are treated as nodes, and the dependency edges and their corresponding dependency weights are treated as directed weighted edges to construct a field dependency graph for subsequent importance assessment and transmission sequence planning.

[0025] After establishing the field dependency graph, two core metrics are calculated for each field node: influence range and dependency depth. The influence range measures the number of downstream fields that a field can directly or indirectly affect in the dependency propagation path, along with their accumulated weights. It reflects how many other fields will be affected by the missing value of this field. Specifically, starting with a field, a breadth-first traversal is performed along the directed dependency edges to count the number of all reachable successor nodes. The product of the accumulated dependency weights along the path is used as a decay coefficient to obtain the weighted influence range value S. i Where i is the index number of the field node. The dependency depth value measures the level at which a field is depended on by other fields in the dependency propagation path, that is, the length of the longest directed path ending with that field. It reflects that the deeper the field is in the basic level of the entire dependency structure, the more indispensable it is. Let the dependency depth value of field i be D. i This is achieved by performing a reverse topological sort on the field dependency graph and accumulating path weights layer by layer. Based on the influence range value S iWith the dependency depth value D i Calculate the dependency strength coefficient C for each field. i The calculation method is C. i =α·S i +β·D i α and β are preset weighting factors used to balance the relative contributions of the scope of influence and the depth of dependence to the strength of dependence. The sum of the two is 1, which can be adjusted according to specific emergency business scenarios.

[0026] Based on the dependency strength coefficient, and combined with the positional weight of the target business fields in the emergency data message, a comprehensive importance score is given to each field. The positional weight reflects the impact of the field's position in the message structure on the completeness of parsing. Generally, fields at the beginning of the message header area have higher positional weights because these fields are often prerequisites for message parsing. The positional weights of fields in the payload area are assigned according to preset rules based on their offset in the payload structure. Let the positional weight of field i be P. i Then the importance score R of field i i It is obtained by linearly fusing the dependency strength coefficient and the location weight, i.e. , where γ and To integrate weighting factors, satisfy The higher the importance score, the more indispensable the field is in emergency communications, and the more priority should be given to ensuring its transmission.

[0027] After scoring the importance of each field, all target business fields are sorted from highest to lowest importance, forming an ordered field list. This ordered field list is then sequentially divided based on a preset encapsulation segment length threshold. The encapsulation segment length threshold is dynamically configured based on the maximum transmission unit (MTU) of the satellite communication link and link quality prediction results. When link quality is poor, the threshold is appropriately reduced to decrease the data volume of a single encapsulation segment and mitigate the impact of transmission failures. During sequential division, starting from the head of the sorted list, several consecutive fields are packaged into one encapsulation segment until the cumulative data volume of the encapsulation segment reaches the length threshold. Then, the next encapsulation segment is initiated, and so on, until all fields are encapsulated. Each encapsulation segment retains the semantic tags, data type attributes, and position offset information of the fields in the original message. This allows the receiving end to independently parse received encapsulation segments even if some segments are lost, maximizing the availability of emergency data.

[0028] Through the segmented encapsulation process described above, highly important fields are prioritized and included in the earlier encapsulation segments. When satellite link resources are limited or transmission is interrupted, the prioritized encapsulation segments already contain the most critical emergency service information, providing minimal but essential data support for emergency command and decision-making. The segmentation results also provide the basic data structure for subsequently constructing a transmission dependency tree based on the field dependency graph. This allows transmission sequence planning to fully utilize the dependencies between fields at the encapsulation segment granularity, further optimizing end-to-end transmission efficiency and reliability.

[0029] The target business fields are traversed to extract semantic tags and data type attributes for each field. Based on the semantic tags, a preset field association rule base is matched. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated, including: Traverse the target business fields, parse the field name and field value format of each field, extract keywords representing business meaning from the field name as semantic tags, and identify data type attributes from the field value format; The semantic tags of the target business field are matched one by one with the association rules in the field association rule base. When the semantic tag of any target business field is consistent with the source semantic tag of the association rule, the target business field corresponding to the target semantic tag defined by the association rule is found, and a dependency edge is established between the target business field and the target business field corresponding to any target semantic tag. The direction of the dependency edge is determined by the dependency direction defined by the association rule. The dependency weight is calculated based on the compatibility of the data type attributes of any target business field with the target business field corresponding to the target semantic tag; Generate a field dependency graph based on all target business fields, the dependent edges, and the dependent weights.

[0030] After receiving the emergency data packets sent by the local service terminal, it is necessary to extract the target business fields and construct a field dependency graph to facilitate subsequent importance scoring and segmentation encapsulation of each field. The quality of the generated field dependency graph directly determines the rationality of the encapsulated segments; therefore, systematic semantic parsing and rule matching of the target business fields are required.

[0031] When traversing the target business fields, the field name and value format of each field are parsed. Field names are typically in camelCase, underscore-separated, or abbreviated form, such as "src_ip", "eventType", and "cmdPriority". The field names are then segmented, and the resulting tokens are mapped to a pre-defined business semantic dictionary to extract keywords that represent the business meaning. These keywords are used as the semantic tags for the field. For example, the field name "emergencyLevel" is segmented into "emergency" and "level". After semantic dictionary mapping, "emergency level" is extracted as the semantic tag. Simultaneously, the field value format is identified. Regular expressions or format template matching are used to determine whether the field value is an integer, floating-point, string, enumeration, timestamp, or binary data type. The identification result is recorded as the data type attribute of the field. The semantic tags and data type attributes together constitute the basic descriptive information of each field, providing input for subsequent rule matching.

[0032] The field association rule base is a set of rules pre-configured according to emergency command business scenarios. Each association rule consists of four elements: source semantic label, target semantic label, dependency direction, and rule confidence. For example, the rule "Emergency Level → Response Action" indicates that a field carrying the semantic label "Emergency Level" has a dependency relationship with a field carrying the semantic label "Response Action," and the dependency direction is from the "Emergency Level" field to the "Response Action" field. The semantic labels of each target business field are matched against all association rules in the rule base one by one. When the semantic label of a target business field matches the source semantic label of an association rule, the target semantic label defined by that association rule is searched in the rule base, and the field carrying that target semantic label is located in the target business field set. Subsequently, a directed dependency edge is established between the current target business field and the located target field, with the edge direction strictly following the dependency direction defined in the association rule. If multiple rules in the rule base simultaneously hit the same pair of fields, the rule with the highest confidence among all hitting rules is taken as the final edge construction basis to avoid redundant graph structure caused by duplicate edge construction.

[0033] After establishing dependency edges, it is necessary to further calculate the dependency weight of each edge to quantify the strength of the dependency relationship between the two fields. The calculation of dependency weights is based on the compatibility of the data type attributes of the two end fields. Data type compatibility reflects the quality of matching between the data types of the source field and the target field during semantic transmission. Specifically, a compatibility score W is defined. uvThe weight of the dependency edge between field u and field v is used to represent the weight of the edge, and its value ranges from [0, 1]. When the data types of the two fields are exactly the same, the compatibility score is the highest; when the data types of the two fields are implicitly convertible (such as integer and floating-point), the compatibility score is medium; when the data types of the two fields are semantically related but cannot be directly converted (such as enumeration and string), the compatibility score is low; when the data types of the two fields are completely incompatible, the compatibility score is the lowest, and the dependency edge is marked as a weak dependency. In actual calculations, a data type compatibility matrix can be pre-configured, where the rows and columns correspond to all supported data types, and the elements in the matrix represent the compatibility scores for the corresponding type combinations. W can be quickly obtained by looking up a table. uv The higher the compatibility score, the greater the dependency weight, indicating a stronger dependency relationship between the two fields.

[0034] After semantic tag extraction, data type attribute identification, dependency edge establishment, and dependency weight calculation are completed for all target business fields, a complete field dependency graph is generated, using each target business field as a node and the established dependency edges and their corresponding dependency weights as directed weighted edges. This graph is a directed weighted graph, where each node carries three attributes: field name, semantic tag, and data type attribute, and each edge carries two attributes: dependency direction and dependency weight. During graph generation, connectivity is checked. If an isolated node exists (i.e., a field node with neither incoming nor outgoing edges), it is marked as an independent field and assigned a lower base score in subsequent importance scoring. If a directed cycle exists in the graph, the cycle is identified by detecting strongly connected components, and the cycle is broken based on the edge with the smallest sum of dependency edge weights in the cycle. This ensures that the field dependency graph has a directed acyclic graph topology, thus supporting subsequent topology sorting operations.

[0035] Once the field dependency graph is generated, it will serve as the unified foundation for subsequent importance scoring calculations and transport dependency tree construction. This graph clearly reflects the semantic relationships and data flow between various service fields in emergency data messages, providing a structured basis for rationally prioritizing encapsulation segments and ensuring the priority transmission of critical fields in network outage emergency scenarios. In actual deployment, the field association rule base supports differentiated configuration based on different emergency service scenarios (such as earthquake rescue, flood emergency, public safety incidents, etc.), enabling the generation of the field dependency graph to adapt to the semantic structure of fields in different service types, thus improving the applicability of satellite communication gateways in multi-scenario emergency command tasks.

[0036] Based on antenna attitude parameters and electromagnetic interference characteristics, predictive signal quality values ​​for multiple candidate frequency bands are calculated. Signal scanning is then performed sequentially in each candidate frequency band according to the order of these predicted signal quality values ​​to establish a satellite communication link. This includes: The spatial geometric relationship between the antenna beam coverage area and the preset satellite orbit position is calculated based on the antenna attitude parameters. Spectral analysis of electromagnetic signals in the environment is performed to identify the frequency distribution of interference sources and the intensity of interference signals in each frequency band, generating electromagnetic interference characteristics. For each candidate frequency band, the antenna gain correction coefficient is calculated based on the spatial geometric relationship, and the interference suppression factor is calculated based on the interference signal strength corresponding to the candidate frequency band in the electromagnetic interference characteristics. Based on the antenna gain correction coefficient and the interference suppression factor, the predicted signal quality value of the candidate frequency band is calculated, and multiple candidate frequency bands are sorted according to the predicted signal quality value to generate a frequency band scanning sequence. Signal scanning operations are performed sequentially in each candidate frequency band according to the frequency band scanning sequence. When a satellite signal that meets the signal strength threshold is detected in any candidate frequency band, the center frequency and signal characteristic parameters of that candidate frequency band are recorded. Configure the operating parameters of the radio frequency transceiver module of the communication gateway based on the center frequency and signal characteristic parameters, and establish a satellite communication link in any candidate frequency band.

[0037] In emergency scenarios involving network outages, the rapid establishment of satellite communication links relies on precise perception of antenna attitude and the electromagnetic environment. Antenna attitude parameters typically include the antenna's azimuth, elevation, and polarization direction; these three parameters collectively determine the antenna beam's direction in space. Based on the antenna azimuth... By combining the elevation angle θ with ephemeris data from the preset satellite orbit position, the spatial geometric relationship between the antenna beam coverage area and the target satellite can be calculated using the spherical geometric projection method. Specifically, the satellite's geocentric latitude and longitude coordinates are converted into azimuth and elevation angles in the local station-centric coordinate system, and compared with the actual antenna pointing direction to obtain the beam deviation angle. This deviation angle directly reflects the degree to which antenna pointing accuracy affects link gain. When the gain is large, the antenna main lobe gain decreases significantly, which needs to be compensated for in subsequent gain correction.

[0038] Simultaneously, a broadband spectrum scan of the electromagnetic signals in the environment is performed, covering the frequency range of all candidate frequency bands. During the spectrum analysis, a fast Fourier transform is used to perform time-frequency analysis on the sampled signals to identify the frequency distribution of interference sources within each frequency band. For each candidate frequency band, the peak power spectral density and average power spectral density of the interference signal within that band are statistically analyzed, and the two are weighted and fused to obtain the interference signal strength I of that frequency band. f, where f is the identifier index of the candidate frequency band. By statistically averaging the spectral data within multiple time windows, persistent interference and transient burst interference can be distinguished, thus generating a more robust electromagnetic interference characteristic description. The electromagnetic interference characteristics generated in this process include a list of interference source center frequencies, interference bandwidth, and interference signal strength corresponding to each candidate frequency band, providing input for subsequent signal quality prediction.

[0039] For each candidate frequency band, the antenna gain correction factor and interference suppression factor are calculated separately, where the antenna gain correction factor G... f The calculation is based on the beam deviation angle. By substituting the actual pointing deviation into the antenna pattern function, the correction amount relative to the main lobe peak gain under the current pointing condition is obtained, based on the antenna pattern model. When G approaches zero f Approaching 1 indicates the minimum gain loss; when When G increases, f Monotonically decreasing, reflecting the gain attenuation caused by beam deviation; interference suppression factor η f Then, based on the interference signal strength I corresponding to the candidate frequency band f f The calculated value, in its physical sense, represents the ratio of the interference suppression capability to the interference intensity achievable by the communication system under this interference environment. When I... f At higher levels, η f A lower I indicates that the frequency band is significantly affected by interference, and the expected link quality is poor; when I f When approaching ambient noise level, η f Approaching the maximum value indicates that the interference environment in this frequency band is good.

[0040] Based on antenna gain correction coefficient G f and interference inhibition factor η f Calculate the predicted signal quality value Q for candidate frequency band f. f Q f This comprehensively reflects the combined impact of antenna pointing accuracy and electromagnetic environment quality on link availability. Its calculation method involves using G... f With η f The data is fused according to preset weighting coefficients, ensuring that both antenna gain loss and interference intensity are reflected in the predicted values. The Q values ​​for all candidate frequency bands are then calculated. f Then, according to Q f Candidate frequency bands are sorted from highest to lowest quality to generate a frequency band scanning sequence. Frequency bands ranked higher are expected to have the best signal quality; prioritizing their scanning can effectively shorten link establishment latency, which is crucial in emergency scenarios. If multiple candidate frequency bands have Q... f If the frequencies are similar, the historical link success rate of each frequency band will be further referenced as an auxiliary sorting criterion to improve the practicality of the scan sequence.

[0041] Following the frequency band scanning sequence, signal scanning operations are performed sequentially in each candidate frequency band. In each candidate frequency band, the RF transceiver module tunes its local oscillator frequency to the center frequency of that band, performs correlation detection on the received signal, and matches it against a pre-stored satellite pilot signal template. When the detected signal correlation peak exceeds a preset signal strength threshold, it is determined that a satellite signal has been successfully acquired in that candidate frequency band. The signal strength threshold is set by comprehensively considering the receiver noise floor, minimum usable signal-to-noise ratio requirements, and link margin to ensure that the acquired satellite signal can support subsequent data transmission services. Once signal acquisition is completed in a candidate frequency band, the center frequency f of that band is immediately recorded. c This includes signal characteristic parameters, such as received signal strength indication, carrier-to-noise ratio estimate, Doppler frequency shift, and signal polarization state. These signal characteristic parameters will serve as inputs for subsequent RF operating parameter configuration, ensuring that the communication gateway can access the satellite link in optimal operating condition.

[0042] Based on the center frequency f of the record c And signal characteristic parameters, to finely configure the operating parameters of the RF transceiver module of the communication gateway, with the local oscillator frequency set to f c Simultaneously, the local oscillator frequency is compensated based on the Doppler frequency shift to eliminate frequency deviations caused by satellite and terminal motion. The gain control word of the low-noise amplifier is adjusted according to the received signal strength indication to ensure the receiving link operates within its optimal dynamic range, avoiding signal overload or insufficient signal-to-noise ratio. The antenna polarization switching switch is configured according to the signal polarization state to select the antenna port matching the polarization direction of the received signal, maximizing polarization matching gain. After completing the above parameter configuration, a satellite communication link is formally established in the candidate frequency band, and subsequent encapsulation segment transmission sequences will be sent through this link. If link quality deteriorates after establishing a link in the current candidate frequency band, the frequency band scanning process can be retried, starting from the next candidate frequency band in the frequency band scanning sequence to retry link establishment, thereby achieving adaptive link switching and recovery.

[0043] Based on the field dependency graph, the multiple encapsulation segments are constructed into a transport dependency tree, and the transport dependency tree is topologically sorted to obtain a transport sequence, including: Read the dependency descriptors of each encapsulation segment; For each encapsulation segment, based on the predecessor dependency field recorded in the dependency descriptor, the encapsulation segment to which the predecessor dependency field belongs is found in the field dependency graph and used as the parent node encapsulation segment of the current encapsulation segment. Based on the subsequent dependent field recorded in the dependency descriptor, the encapsulation segment to which the subsequent dependent field belongs is found in the field dependency graph and used as the child node encapsulation segment of the current encapsulation segment. Based on the association between the parent node encapsulation segment and the child node encapsulation segment of all encapsulation segments, a transmission dependency tree is generated. In the transmission dependency tree, there are directed edges between the parent node encapsulation segment and the child node encapsulation segment, and the direction of the directed edges is from the parent node encapsulation segment to the child node encapsulation segment. Calculate the dependency level depth of each encapsulation segment in the transport dependency tree. For multiple encapsulation segments with the same dependency level depth, calculate the intra-layer priority based on the sum of the dependency weights of the fields contained in each of the multiple encapsulation segments in the field dependency graph. The transmission dependency tree is topologically sorted based on the dependency level depth and the intra-layer priority to generate a transmission sequence.

[0044] After generating the encapsulation segments, the dependencies between them need to be explicitly organized into a transport dependency tree based on the existing topology information in the field dependency graph to support subsequent ordered transport scheduling. Each encapsulation segment carries a dependency descriptor during the encapsulation phase. This descriptor records, in a structured form, the set of predecessor dependent fields and the set of successor dependent fields for all fields within the current encapsulation segment. Predecessor dependent fields refer to other fields that a field in the current encapsulation segment depends on semantically or in terms of data flow; these fields typically belong to other encapsulation segments. Successor dependent fields refer to fields that a field in the current encapsulation segment references or depends on by fields in other encapsulation segments. The dependency descriptor is directly derived from the edge information of the field dependency graph during encapsulation, ensuring consistency with the graph structure.

[0045] After reading the dependency descriptors of each encapsulation segment, a parent-child node lookup process is performed for each encapsulation segment. For the current encapsulation segment, all predecessor dependency fields recorded in its dependency descriptor are traversed, and the encapsulation segments to which these predecessor dependency fields belong are located in the field dependency graph. These encapsulation segments are marked as the parent encapsulation segments of the current encapsulation segment. The meaning of a parent encapsulation segment is that the current encapsulation segment must wait for the parent encapsulation segment to complete its transmission before the receiving end can guarantee that the predecessor field data required by the receiving end to parse the current encapsulation segment is ready. Similarly, the successor dependent fields recorded in the dependency descriptor are traversed, and the encapsulation segments to which these fields belong are found in the field dependency graph. These are marked as child encapsulation segments of the current encapsulation segment, indicating that the transmission of the child encapsulation segment logically depends on the prior completion of the current encapsulation segment.

[0046] After identifying the parent-child relationships of all encapsulation segments, the associations between all parent and child encapsulation segments are aggregated to generate a transport dependency tree. The transport dependency tree is a directed acyclic graph structure where each directed edge points from a parent encapsulation segment to a child encapsulation segment, representing the sequence of transmission constraints. The root encapsulation segment of the tree is one without any parent node, meaning its internal fields do not depend on fields in any other encapsulation segment. In actual emergency data messages, the root encapsulation segment typically contains basic metadata fields such as message header identifier fields, timestamp fields, and message type fields. These fields are prerequisites for parsing all subsequent business fields. If multiple independent encapsulation segments without parent nodes are found during the construction process, a virtual root encapsulation segment is used as a unified entry point, and these encapsulation segments are all mounted as children of the virtual root node. This ensures that the transport dependency tree has a unique root node, facilitating unified calculation of subsequent hierarchical depth.

[0047] After the transport dependency tree is constructed, the dependency level depth is calculated for each encapsulation segment in the tree. The dependency level depth is defined as the number of edges on the longest directed path from the root node encapsulation segment to the current encapsulation segment. The dependency level depth of the root node encapsulation segment is 0, the dependency level depth of its direct child node encapsulation segments is 1, and so on. If an encapsulation segment has multiple parent node encapsulation segments (i.e., the fields of this encapsulation segment depend on multiple predecessor fields from different encapsulation segments), the maximum value of the dependency level depths of all parent node encapsulation segments plus 1 is taken as the dependency level depth of this encapsulation segment. This ensures that the current encapsulation segment is scheduled for transmission only after all predecessor encapsulation segments have been transmitted. The dependency level depth is calculated using a breadth-first traversal, expanding downwards from the root node. The dependency level depth of each encapsulation segment can only be finally determined after the depths of all its parent nodes are determined.

[0048] Within the same dependency level depth, multiple encapsulation segments may exist. These segments are independent of each other in terms of transmission constraints and can theoretically be transmitted in parallel. However, in a serial link scenario, the transmission order within the layer needs to be determined. For multiple encapsulation segments with the same dependency level depth, the sum of the dependency weights of all fields within each encapsulation segment in the field dependency graph is used as the basis for calculating the intra-layer priority. Let a certain encapsulation segment P... k The set of fields contained within is F k The intra-layer priority score L of this encapsulation segment k Defined as: ; Among them W uv Let v be the dependency weight of the dependency edge in the field dependency graph with field u as the source node, v be the target field node that has a dependency relationship with field u, and u be a field in the field set of this encapsulation segment. Intra-layer priority score L kThe higher the value, the more crucial the fields within that encapsulation segment are in supporting data relationships within the overall data packet. Other fields are more dependent on them, therefore they should be transmitted first to reduce parsing blockages at the receiving end caused by waiting for critical fields. Within the same dependency level, according to L... k Sort the encapsulation segments from largest to smallest, L k If they are the same, the number of the encapsulated segment is used as the secondary sorting key to ensure the determinism of the sorting result.

[0049] Based on dependency level depth and intra-layer priority, a topological sort is performed on the transmission dependency tree to generate the final transmission sequence. The execution logic of the topological sort is as follows: starting from the root node encapsulation segment with a dependency level depth of 0, processing is performed layer by layer in ascending order of level depth. Within the same level, encapsulation segments are added to the transmission sequence in descending order of intra-layer priority score. If an encapsulation segment has multiple parent nodes distributed across different levels, the transmission position of the encapsulation segment is determined by its dependency level depth, ensuring that it is arranged after all parent node encapsulation segments. The final generated transmission sequence is a linearly ordered list of encapsulation segments. Encapsulation segments at the beginning of the list have higher scheduling priority during transmission. The receiving end can gradually restore the parsing order of each field according to the same dependency tree structure, ensuring that when link bandwidth is limited or some encapsulation segments are lost, priority is given to restoring high-importance core field data, improving information availability in emergency command scenarios.

[0050] After the transmission sequence is generated, it will directly guide the scheduling of encapsulation segments on the satellite communication link. The transmission sequence records the sequential number and corresponding hierarchical information of each encapsulation segment, which is convenient for tracking the arrival status of each encapsulation segment in the subsequent transmission status monitoring stage. When the transmission status index is lower than the preset threshold, the importance score is dynamically adjusted based on the position characteristics of the encapsulation segment in the transmission dependency tree, giving priority to ensuring that encapsulation segments with shallow dependency level depth and high intra-layer priority receive retransmission resources.

[0051] Based on the dependency level depth and the intra-level priority, the transmission dependency tree is topologically sorted to generate a transmission sequence, including: Traverse all encapsulation segments in the transport dependency tree and divide all encapsulation segments into multiple level groups according to the dependency level depth value. The encapsulation segments in the level group have the same dependency level depth value. For each level group, the dependency correlation degree between the encapsulated segments within the level group is calculated. The dependency correlation degree is used to quantify the tightness of the cross-encapsulated segment dependency relationship between the fields contained in the encapsulated segments within the level group in the field dependency relationship graph. The encapsulation segments within the hierarchical group are clustered and grouped according to the dependency correlation degree to obtain multiple cluster subgroups. Within each cluster subgroup, the encapsulation segments are arranged according to the intra-layer priority value, which serves as the basis for determining the arrangement position of the encapsulation segment within the cluster subgroup. The expansion order of each level group is determined according to the dependency level depth value, and the encapsulation segments in each cluster subgroup are added to the candidate transmission sequence in order of their arrangement position. The transmission sequence is obtained by verifying that the dependency relationship between adjacent encapsulation segments in the candidate transmission sequence satisfies the constraint that the fields contained in the subsequent encapsulation segment depend on the fields contained in the preceding encapsulation segment.

[0052] After the transport dependency tree is constructed, it needs to be topologically sorted to generate the final transport sequence. The core objective of topological sorting is to ensure that each encapsulation segment is transported after the encapsulation segments it depends on, while making full use of intra-layer priority information to optimize the transport order so that the more important encapsulation segments are transported as early as possible.

[0053] Traverse all encapsulation segment nodes in the transport dependency tree, reading the dependency depth value calculated for each encapsulation segment when constructing the transport dependency tree. The dependency depth value reflects the position of the encapsulation segment in the dependency chain: the root node has a depth value of 0, its direct dependent child nodes have a depth value of 1, and so on. Group all encapsulation segments with the same dependency depth value into the same level group, thus dividing all encapsulation segments in the transport dependency tree into several level groups. Encapsulation segments within each level group are at the same depth in terms of dependency relationships, and theoretically, they can be processed in parallel after all encapsulation segments in the preceding level group have been transmitted. The number of level groups is equal to the maximum depth of the transport dependency tree plus one, and the number of encapsulation segments in each level group depends on the width distribution of the tree structure.

[0054] For each level group, the dependency correlation degree between encapsulated segments within the group is calculated. The dependency correlation degree is used to quantify the strength of the cross-encapsulated segment dependency relationship between the fields contained in two encapsulated segments within the same level group in the field dependency relationship graph. Specifically, for any two encapsulated segments K within the level group... a With K b Statistical K a The set of fields included and K b The number of field pairs in the included field sets that have direct or indirect dependency edges in the field dependency graph, combined with the weight W of the corresponding dependency edge. uv We perform a weighted summation to obtain the dependency degree A between the two encapsulation segments. ab The calculation method is as follows: ; in, and They are respectively encapsulation segment K a With K b The set of fields included, W uv Let U be the weight of the dependency edge from field U to field V. This is an indicator function that takes the value 1 when the condition inside the parentheses is true, and 0 otherwise. In other words, The value is 1 if a dependency path (u, v) exists, and 0 otherwise. A dependency path (u, v) indicates that there is a dependency edge in the field dependency graph pointing from field u to field v. The higher the dependency correlation, the closer the semantic relationship between the two encapsulation segments, and they should be preferentially arranged to be transmitted in adjacent positions to reduce the waiting delay during reassembly at the receiving end.

[0055] Based on the dependency correlation matrix calculated between each pair of encapsulated segments within a hierarchical group, the encapsulated segments within the hierarchical group are clustered. The clustering process employs an agglomeration strategy based on a correlation threshold: encapsulated segments with a dependency correlation higher than a preset clustering threshold are grouped into the same subgroup, and this process is repeated until no further merging is possible. For encapsulated segments with low dependency correlation and sparse association with other encapsulated segments, they are grouped into a separate subgroup. After clustering, all encapsulated segments within a hierarchical group are divided into several subgroups, and the encapsulated segments within each subgroup have strong semantic internal correlation.

[0056] Within each cluster subgroup, the priority value L of the encapsulation segment is used as the basis for classification. k Encapsulation segments are sorted in descending order, with those having higher intra-layer priority values ​​appearing first and thus having priority in the candidate transmission sequence. Intra-layer priority value L k This comprehensively reflects the importance score of fields within the encapsulation segment and the weight of dependencies across encapsulation segments. Therefore, encapsulation segments with higher intra-layer priority often carry more critical business fields and should be transmitted first within the same layer to ensure the priority arrival of core data in emergency communication scenarios. When two encapsulation segments within the same cluster have intra-layer priority values ​​L... k When they are equal, the ascending order of the encapsulation segment index number K is used as the secondary sorting basis to ensure the determinism and repeatability of the sorting result.

[0057] The unfolding order of each level group is determined by the ascending order of dependency level depth values, that is, the level group with the smallest dependency level depth value (i.e., closest to the root node) is unfolded first, and the subgroups within it are unfolded according to the overall priority of the subgroup (based on the highest intra-level priority value L within the subgroup). k The segments are arranged in descending order (using the group as the representative), and the encapsulated segments within each cluster are added to the candidate transmission sequence in the order they are arranged. After the current level group is expanded, the next level group is processed until the encapsulated segments of all levels have been added to the candidate transmission sequence.

[0058] After candidate transmission sequences are generated, dependency constraint verification is performed. All adjacent encapsulation segment pairs in the candidate transmission sequence are traversed, and it is checked whether the field set contained in the subsequent encapsulation segment has a dependency relationship with the fields contained in the preceding encapsulation segment in the field dependency graph. If a subsequent encapsulation segment depends on an encapsulation segment that has not yet appeared in a preceding position, the constraint-violating encapsulation segment pair is identified, and its position is locally adjusted: the dependent encapsulation segment is moved forward in the sequence until all dependency constraints are satisfied. During the local adjustment process, the relative order of priority within the layer is maintained, and position swapping is only performed when constraint conflicts must be resolved, to minimize interference with the priority ranking result. After constraint verification and local adjustment, the candidate transmission sequence is transformed into a final transmission sequence that satisfies the topological ordering constraints.

[0059] The final transmission sequence takes into account information from three dimensions: dependency level depth, intra-layer priority, and cluster correlation. This ensures the correctness of the transmission order of encapsulated segments in terms of dependency semantics, and also arranges semantically related encapsulated segments in a clustering strategy. This helps the receiver to start local reassembly as soon as some encapsulated segments arrive, reducing data reassembly delay in emergency command scenarios and improving the emergency response efficiency of satellite communication links in network outage environments.

[0060] The encapsulated segments are transmitted via the satellite communication link according to the transmission sequence. The transmission status of each encapsulated segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulated segments, including: The encapsulated segments are transmitted sequentially through the satellite communication link in the order determined by the transmission sequence, and transmission status parameters are collected in real time during the transmission of each encapsulated segment. The transmission status index of each encapsulation segment is calculated based on the transmission status parameters. The transmission status index is used to quantitatively characterize the stability of the transmission quality of the encapsulation segment in the satellite communication link. Determine whether the transmission status indicator is lower than a preset threshold. When the transmission status indicator is lower than the preset threshold, extract the encapsulation segment features of the encapsulation segment whose transmission status indicator is lower than the preset threshold. A transmission impact factor is calculated based on the characteristics of the encapsulation segment, and an importance adjustment is calculated based on the transmission impact factor. The importance adjustment is positively correlated with the transmission impact factor. The importance adjustment amount is added to the original importance score of the encapsulation segment whose transmission status index is lower than the preset threshold to generate the adjusted importance score.

[0061] Following the predetermined transmission sequence, each encapsulated segment is transmitted sequentially via the satellite communication link. During the transmission of each encapsulated segment, transmission status parameters related to its transmission process are collected in real time, including but not limited to raw observations such as link signal-to-noise ratio, bit error rate, retransmission count, end-to-end delay, and packet loss rate. These parameters reflect the actual carrying capacity of the current satellite communication link for each encapsulated segment from different dimensions and serve as the fundamental data source for subsequent calculations of transmission status indicators. To ensure real-time acquisition, an independent status acquisition channel is established for the transmission process of each encapsulated segment, with the acquisition period aligned with the transmission time slot of the encapsulated segment, ensuring that complete transmission status parameter records are obtained for each encapsulated segment before its transmission is completed.

[0062] Based on the collected transmission status parameters, the transmission status index corresponding to each encapsulation segment is calculated. The transmission status index is a scalar value obtained by comprehensively weighting and fusing multiple original transmission status parameters, used to quantitatively characterize the transmission quality stability of the encapsulation segment in the satellite communication link. Specifically, the normalized signal-to-noise ratio score, the inverse mapping value of the bit error rate, the penalty term for retransmission count, and the weighted attenuation term of delay are linearly combined according to preset weights to obtain the transmission status index M. k , where k is the index number of the encapsulation segment (consistent with existing parameters). M k The value range of M is normalized to the interval [0, 1]. A higher value indicates a more stable transmission quality for the encapsulation segment, while a lower value indicates a worse transmission quality for the encapsulation segment under the current link conditions. By analyzing M... k Continuous monitoring allows for dynamic understanding of the quality changes of each encapsulation segment during actual transmission.

[0063] After obtaining the transmission status index M of each encapsulation segment k Then, it is compared with a preset threshold T. th Comparison and judgment, preset threshold T th Pre-configured based on the minimum data reliability requirements in emergency command scenarios, when the M of a certain encapsulation segment... k Below T th When this occurs, the encapsulation segment is determined to be in an abnormal transmission quality state, and its importance score needs to be dynamically adjusted to guide the optimization of subsequent transmission strategies. For M... k Not lower than T th For encapsulation segments, their importance scores remain unchanged, and subsequent transmission tasks continue to be executed according to the original transmission sequence. For encapsulation segments that trigger threshold judgment conditions, the encapsulation segment feature extraction process is initiated to provide input for subsequent importance adjustment calculations.

[0064] If any transmission status indicator falls below a preset threshold, then for the encapsulation segment with the transmission status indicator below the preset threshold, its encapsulation segment features are extracted. These features include multi-dimensional attribute descriptions: first, the distribution of business types of the fields contained within the encapsulation segment, i.e., whether the encapsulation segment carries location information fields, command control fields, or status report fields, etc.; second, the data volume of the encapsulation segment, i.e., the byte length of the encapsulation segment; third, the depth of the encapsulation segment in the transmission dependency tree, i.e., the number of hops from the root node of the transmission dependency tree; and fourth, the position number of the encapsulation segment in the transmission sequence, i.e., its relative position in the overall transmission order. These four types of features comprehensively characterize the inherent attributes of the encapsulation segment from four perspectives: business attributes, data scale, structural position, and transmission order, providing multi-dimensional input for the accurate calculation of transmission impact factors. If no transmission status indicator falls below the preset threshold, the transmission status of each encapsulation segment can be monitored.

[0065] Based on the extracted encapsulation segment characteristics, the transmission impact factor E is calculated. k Transmission Influence Factor E k This reflects the potential impact of transmission failure or quality degradation in this encapsulation segment on the overall emergency data transmission task. During calculation, the average weight of the service type of the fields within the encapsulation segment is denoted as B. k The normalized value of the encapsulation segment's hierarchy depth is denoted as H. k The normalized value of the position of the encapsulated segment in the transmission sequence is denoted as O. k Let Z be the log-normalized value of the length of the encapsulated segment in bytes. k Transmission Influence Factor E k E is obtained by weighted summation of the above characteristic components. k =λ1B k +λ2H k +λ3O k +λ4Z k λ1, λ2, λ3, and λ4 are the weight coefficients corresponding to each feature component, satisfying λ1 + λ2 + λ3 + λ4 = 1, and each weight coefficient is greater than zero. E k The larger the value, the more significant the impact of the encapsulation segment on the overall transmission task, and the more retransmission resources or priority resources need to be allocated to ensure its reliable transmission.

[0066] Based on the transmission impact factor E k Calculate the importance adjustment amount ΔR k Importance adjustment amount ΔR k With transmission influence factor E k There is a positive correlation; that is, the larger the transmission impact factor of the encapsulation segment, the greater its importance adjustment, thus obtaining a higher priority guarantee in subsequent transmission resource allocation. Specifically, ΔR k By Ek Multiply by the adjustment coefficient μ to obtain ΔR. k =μ·E k , where μ is a preset adjustment ratio coefficient, configured according to the severity of the emergency scenario and the sufficiency of link resources, typically ranging from [0.1, 0.5]. When link resources are extremely scarce, the value of μ can be appropriately reduced to avoid excessive compression of transmission resources in other encapsulation segments due to a significant increase in importance score; when link conditions are relatively relaxed, the value of μ can be appropriately increased to more fully guarantee the transmission reliability of high-impact encapsulation segments.

[0067] Adjust the importance amount ΔR k The original importance score is superimposed onto the corresponding encapsulation segment to generate an adjusted importance score. ,Right now ,in This is the original importance score calculated for this encapsulation segment based on the field dependency graph in the initial stage. The adjusted importance score is... The data will be fed back to the transmission scheduling module for dynamically updating the transmission priority order of the encapsulation segments and reconstructing the transmission sequence. This also allows encapsulation segments with poor transmission quality and significant service impact to receive higher retransmission priority and more channel resource allocation in subsequent transmissions. Through this closed-loop importance scoring dynamic adjustment mechanism, the entire satellite communication gateway control process can adaptively adjust transmission strategies when link conditions deteriorate, maximizing the reliable transmission of critical emergency data and effectively improving the robustness and availability of emergency command communications in network outage environments.

[0068] A second aspect of the present invention provides a satellite communication gateway control system, comprising: The data acquisition unit is used to acquire emergency data messages sent by local business terminals; The field processing unit is used to extract the target business fields in the emergency data message to generate a field dependency graph, score the importance of each field based on the field dependency graph, and encapsulate the target business fields into multiple encapsulation segments according to the importance scores. The link establishment unit is used to calculate the predicted signal quality values ​​of multiple candidate frequency bands based on antenna attitude parameters and electromagnetic interference characteristics, and to perform signal scanning in each candidate frequency band in order of the predicted signal quality values ​​to establish a satellite communication link. A transmission sequence unit is used to construct a transmission dependency tree from the multiple encapsulation segments based on the field dependency graph, and to perform topological sorting on the transmission dependency tree to obtain a transmission sequence. The transmission monitoring unit is used to send the encapsulation segment through the satellite communication link according to the transmission sequence, monitor the transmission status of each encapsulation segment, and adjust the importance score based on the characteristics of the encapsulation segment when the transmission status index is lower than a preset threshold.

[0069] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0070] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0071] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A satellite communication gateway control method, characterized in that, include: Obtain emergency data messages sent by local service terminals; Extract the target business fields from the emergency data message to generate a field dependency graph. Based on the field dependency graph, score the importance of each field. Then, segment and encapsulate the target business fields according to the importance scores to obtain multiple encapsulation segments. Based on antenna attitude parameters and electromagnetic interference characteristics, predictive signal quality values ​​for multiple candidate frequency bands are calculated. Signal scanning is then performed sequentially in each candidate frequency band according to the order of the predicted signal quality values ​​to establish a satellite communication link. Based on the field dependency graph, the multiple encapsulation segments are constructed into a transport dependency tree, and the transport dependency tree is topologically sorted to obtain a transport sequence; The encapsulation segment is transmitted through the satellite communication link according to the transmission sequence. The transmission status of each encapsulation segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulation segment. The process involves extracting target business fields from the emergency data message to generate a field dependency graph, assigning importance scores to each field based on the field dependency graph, and then segmenting and encapsulating the target business fields according to the importance scores to obtain multiple encapsulation segments, including: Parse the header and payload of the emergency data message to extract the target business fields that carry business semantics; The semantic tags and data type attributes of each field are extracted by traversing the target business fields. The semantic tags are matched against a preset field association rule library. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated. For each field in the field dependency graph, calculate the influence range value of the field in the dependency propagation path and the dependency depth value of the field in the dependency propagation path, and calculate the dependency strength coefficient of each field based on the influence range value and the dependency depth value. Based on the dependency strength coefficient and the position weight of the target business field in the emergency data message, an importance score is given to each field; The target business fields are sorted according to the importance score, and the sorted target business fields are sequentially divided according to the preset encapsulation segment length threshold to generate multiple encapsulation segments. The step of constructing a transport dependency tree from the multiple encapsulation segments based on the field dependency graph, and then performing topological sorting on the transport dependency tree to obtain a transport sequence includes: Read the dependency descriptors of each encapsulation segment; For each encapsulation segment, based on the predecessor dependency field recorded in the dependency descriptor, the encapsulation segment to which the predecessor dependency field belongs is found in the field dependency graph and used as the parent node encapsulation segment of the current encapsulation segment. Based on the subsequent dependent field recorded in the dependency descriptor, the encapsulation segment to which the subsequent dependent field belongs is found in the field dependency graph as the child node encapsulation segment of the current encapsulation segment. Based on the association between the parent node encapsulation segment and the child node encapsulation segment of all encapsulation segments, a transmission dependency tree is generated. In the transmission dependency tree, there are directed edges between the parent node encapsulation segment and the child node encapsulation segment, and the direction of the directed edges is from the parent node encapsulation segment to the child node encapsulation segment. Calculate the dependency level depth of each encapsulation segment in the transport dependency tree. For multiple encapsulation segments with the same dependency level depth, calculate the intra-layer priority based on the sum of the dependency weights of the fields contained in each of the multiple encapsulation segments in the field dependency graph. The transmission dependency tree is topologically sorted based on the dependency level depth and the intra-layer priority to generate a transmission sequence.

2. The method according to claim 1, characterized in that, The target business fields are traversed to extract semantic tags and data type attributes for each field. Based on the semantic tags, a preset field association rule base is matched. Based on the matching results, the dependency edges and dependency weights between each field are determined, and a field dependency graph is generated, including: Traverse the target business fields, parse the field name and field value format of each field, extract keywords representing business meaning from the field name as semantic tags, and identify data type attributes from the field value format; The semantic tags of the target business field are matched one by one with the association rules in the field association rule base. When the semantic tag of any target business field is consistent with the source semantic tag of the association rule, the target business field corresponding to the target semantic tag defined by the association rule is found, and a dependency edge is established between the target business field and the target business field corresponding to any target semantic tag. The direction of the dependency edge is determined by the dependency direction defined by the association rule. The dependency weight is calculated based on the compatibility of the data type attributes of any target business field with the target business field corresponding to the target semantic tag; Generate a field dependency graph based on all target business fields, the dependent edges, and the dependent weights.

3. The method according to claim 1, characterized in that, Based on antenna attitude parameters and electromagnetic interference characteristics, predictive signal quality values ​​for multiple candidate frequency bands are calculated. Signal scanning is then performed sequentially in each candidate frequency band according to the order of these predicted signal quality values ​​to establish a satellite communication link. This includes: The spatial geometric relationship between the antenna beam coverage area and the preset satellite orbit position is calculated based on the antenna attitude parameters. Spectral analysis of electromagnetic signals in the environment is performed to identify the frequency distribution of interference sources and the intensity of interference signals in each frequency band, generating electromagnetic interference characteristics. For each candidate frequency band, the antenna gain correction coefficient is calculated based on the spatial geometric relationship, and the interference suppression factor is calculated based on the interference signal strength corresponding to the candidate frequency band in the electromagnetic interference characteristics. Based on the antenna gain correction coefficient and the interference suppression factor, the predicted signal quality value of the candidate frequency band is calculated, and multiple candidate frequency bands are sorted according to the predicted signal quality value to generate a frequency band scanning sequence. Signal scanning operations are performed sequentially in each candidate frequency band according to the frequency band scanning sequence. When a satellite signal that meets the signal strength threshold is detected in any candidate frequency band, the center frequency and signal characteristic parameters of that candidate frequency band are recorded. Configure the operating parameters of the radio frequency transceiver module of the communication gateway based on the center frequency and signal characteristic parameters, and establish a satellite communication link in any candidate frequency band.

4. The method according to claim 1, characterized in that, Based on the dependency level depth and the intra-level priority, the transmission dependency tree is topologically sorted to generate a transmission sequence, including: Traverse all encapsulation segments in the transport dependency tree and divide all encapsulation segments into multiple level groups according to the dependency level depth value. The encapsulation segments in the level group have the same dependency level depth value. For each level group, the dependency correlation degree between the encapsulated segments within the level group is calculated. The dependency correlation degree is used to quantify the tightness of the cross-encapsulated segment dependency relationship between the fields contained in the encapsulated segments within the level group in the field dependency relationship graph. The encapsulation segments within the hierarchical group are clustered and grouped according to the dependency correlation degree to obtain multiple cluster subgroups. Within each cluster subgroup, the encapsulation segments are arranged according to the intra-layer priority value, which serves as the basis for determining the arrangement position of the encapsulation segment within the cluster subgroup. The expansion order of each level group is determined according to the dependency level depth value, and the encapsulation segments in each cluster subgroup are added to the candidate transmission sequence in order of their arrangement position. The transmission sequence is obtained by verifying that the dependency relationship between adjacent encapsulation segments in the candidate transmission sequence satisfies the constraint that the fields contained in the subsequent encapsulation segment depend on the fields contained in the preceding encapsulation segment.

5. The method according to claim 1, characterized in that, The encapsulated segments are transmitted via the satellite communication link according to the transmission sequence. The transmission status of each encapsulated segment is monitored. When the transmission status index is lower than a preset threshold, the importance score is adjusted based on the characteristics of the encapsulated segments, including: The encapsulated segments are transmitted sequentially through the satellite communication link in the order determined by the transmission sequence, and transmission status parameters are collected in real time during the transmission of each encapsulated segment. The transmission status index of each encapsulation segment is calculated based on the transmission status parameters. The transmission status index is used to quantitatively characterize the stability of the transmission quality of the encapsulation segment in the satellite communication link. Determine whether the transmission status indicator is lower than a preset threshold. When the transmission status indicator is lower than the preset threshold, extract the encapsulation segment features of the encapsulation segment whose transmission status indicator is lower than the preset threshold. A transmission impact factor is calculated based on the characteristics of the encapsulation segment, and an importance adjustment is calculated based on the transmission impact factor. The importance adjustment is positively correlated with the transmission impact factor. The importance adjustment amount is added to the original importance score of the encapsulation segment whose transmission status index is lower than the preset threshold to generate the adjusted importance score.

6. A satellite communication gateway control system, used to implement the method as described in any one of claims 1-5, characterized in that, include: The data acquisition unit is used to acquire emergency data messages sent by local business terminals; The field processing unit is used to extract the target business fields in the emergency data message to generate a field dependency graph, score the importance of each field based on the field dependency graph, and encapsulate the target business fields into multiple encapsulation segments according to the importance scores. The link establishment unit is used to calculate the predicted signal quality values ​​of multiple candidate frequency bands based on antenna attitude parameters and electromagnetic interference characteristics, and to perform signal scanning in each candidate frequency band in order of the predicted signal quality values ​​to establish a satellite communication link. A transmission sequence unit is used to construct a transmission dependency tree from the multiple encapsulation segments based on the field dependency graph, and to perform topological sorting on the transmission dependency tree to obtain a transmission sequence. The transmission monitoring unit is used to send the encapsulation segment through the satellite communication link according to the transmission sequence, monitor the transmission status of each encapsulation segment, and adjust the importance score based on the characteristics of the encapsulation segment when the transmission status index is lower than a preset threshold.

7. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 5.

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