Cognitive anti-interference method for hierarchical linkage of unmanned clusters

Abstract

The invention provides a cognitive anti-interference method for hierarchical linkage of an unmanned cluster, relates to the technical field of measurement and control communication, and solves the problem of limitation of the unmanned cluster due to high interference intensity and high threat interference level. In the method, according to an interference cognition evaluation result of the unmanned cluster, a three-level cognition anti-interference strategy is adopted to complete efficient protection of external electromagnetic interference signals, so that a measurement and control link of the unmanned cluster returns to normal; in the three-level cognitive anti-interference strategy, the in-terminal passive suppression strategy independently executes passive interference suppression by the interior of each terminal, the inter-terminal autonomous protection strategy cooperatively executes active interference avoidance by all terminals in the unmanned cluster, and the station-terminal combined protection strategy performs data linkage by the measurement and control station and the unmanned cluster; and performing cognitive strong interference protection processing based on a decision result of the measurement and control station. According to the method, the characteristics of the unmanned cluster are combined, the interference perception and cognition ability of the unmanned cluster is enhanced, and the anti-interference ability of the unmanned cluster in a severe electromagnetic environment is improved.

Description

Technical Field

[0001] The present invention relates to the field of measurement, control and communication technology, and is applied to the interference protection process of unmanned clusters in complex electromagnetic environments, and specifically to a cognitive anti-interference method for hierarchical linkage of unmanned clusters. Background Art

[0002] Unmanned swarm technology, especially swarm systems composed of tiny unmanned platforms, has become a key technology field that countries around the world are competing to develop in recent years. This type of system is composed of various types of micro-unmanned equipment such as drones, cruise missiles, unmanned vehicles, and unmanned boats. It relies on the basic mission capabilities of a single platform and achieves overall functional improvement through efficient collaborative interaction between platforms. These swarm systems are built based on an open system architecture and artificial intelligence technology. They have the advantages of strong anti-destruction, low cost, and distributed functions, and are widely used in military and civilian fields.

[0003] In complex confrontation environments, unmanned swarms can perform a series of tasks such as collaborative search, jamming, attack, reconnaissance and strike. Their characteristics include high density, strong coordination and flexibility, as well as significant cost-effectiveness and robustness, thus providing a scale effect and excellent mission completion capability. However, under the complex electromagnetic environment, ensuring the reliable transmission of business data has become one of the main challenges faced by unmanned swarms.

[0004] Current anti-interference measures are mostly focused on the optimization of measurement and control communication systems, such as traditional methods such as frequency hopping, spread spectrum, and time-frequency and spatial interference suppression, which have matured to a large extent. With the advancement of technology, combined with research in cognitive radio, game theory, and artificial intelligence, adaptive anti-interference and intelligent anti-interference technologies have also been deeply explored. However, existing anti-interference strategies usually do not fully consider the unique attributes of individual platforms in unmanned swarms.

[0005] Take drones as an example. The unmanned swarm often operates at low altitudes and approaches targets to perform tasks, so it is easier to be detected by the target and suffer targeted interference. Being close to the target means that the received interference signal strength is higher and the interference threat is more serious. At the same time, the individuals in the unmanned swarm are usually resource-constrained micro-platforms with limited load, power consumption and computing power, which makes it difficult to deploy advanced hardware such as phased array antennas, limiting its interference suppression capabilities in the airspace.

[0006] Given the greater threat that unmanned swarms face in the same harsh electromagnetic environment, existing anti-interference technologies need to go beyond traditional anti-interference means for measurement and control links, and the direction of development is to introduce hierarchical perception and decision-making mechanisms. This will enable unmanned swarms to enhance their ability to recognize interference and implement more proactive and flexible anti-interference strategies to ensure high-reliability measurement and control communications under strong interference conditions. To this end, it is necessary to develop corresponding new anti-interference solutions, especially designed for the characteristics of unmanned swarms, to meet their special needs in complex electromagnetic environments. Summary of the invention

[0007] In view of the current status of the background technology, the purpose of the present invention is to solve the limitation problem that the unmanned cluster is close to the target, the interference intensity is large, and the interference threat level is high. Therefore, a cognitive anti-interference method of hierarchical linkage of unmanned cluster is proposed to improve the anti-interference ability of unmanned cluster measurement and control equipment in harsh electromagnetic environments. Through its three-level cognitive anti-interference strategy, the present invention combines the characteristics of the unmanned cluster platform to enhance its interference perception and cognitive ability, and can achieve active and flexible anti-interference effects.

[0008] The present invention adopts the following technical solutions to achieve the purpose: A cognitive anti-interference method for hierarchical linkage of unmanned clusters, for each unmanned system terminal in the unmanned cluster, evaluates the interference threat level corresponding to each terminal according to the strength of the external electromagnetic interference signal, and obtains the interference cognitive evaluation result of the unmanned cluster; based on the interference cognitive evaluation result, a three-level cognitive anti-interference strategy is used to complete the interference suppression of the external electromagnetic interference signal, so that the measurement and control link of the unmanned cluster returns to normal; Among them, the three-level cognitive anti-interference strategy includes the first-level intra-terminal passive suppression strategy, the second-level inter-terminal autonomous protection strategy, and the third-level station-end joint protection strategy; the intra-terminal passive suppression strategy is performed by each terminal independently to suppress passive interference, the inter-terminal autonomous protection strategy is performed by all terminals in the unmanned cluster to collaboratively perform active interference avoidance, and the station-end joint protection strategy is performed by the measurement and control station and the unmanned cluster to link data, and perform cognitive strong interference protection processing based on the decision results of the measurement and control station.

[0009] Specifically, in the first-level passive suppression strategy within the terminal, each terminal in the unmanned cluster is configured with a preset passive cognitive anti-interference strategy. Each terminal makes independent decisions by autonomously sensing external electromagnetic interference signals and completes passive interference suppression based on the time-frequency domain. In the second-level terminal-to-terminal autonomous protection strategy, each terminal in the unmanned cluster uses autonomous collaboration to enable the unmanned cluster to perform distributed perception. The cluster head of the unmanned cluster completes centralized decision-making and uses link optimization to achieve active interference avoidance. In the third-level station-side joint protection strategy, the unmanned cluster sends the relevant data obtained by distributed perception to the measurement and control station. The measurement and control station determines the corresponding decision results based on the resource status of its own measurement and control system and sends them to the unmanned cluster. The unmanned cluster completes the cognitive strong interference protection processing based on the decision results.

[0010] Preferably, the interference cognitive evaluation result of the unmanned cluster is divided into a weak level and a strong level according to a preset threshold; when the interference cognitive evaluation result of the unmanned cluster is a weak level, only the first-level end-to-end passive suppression strategy is adopted to complete the interference suppression of the external electromagnetic interference signal through the passive interference suppression method, so that the measurement and control link of the unmanned cluster is restored to normal; When the interference cognition assessment result of the unmanned cluster is a strong level, the cluster head of the unmanned cluster summarizes the result information of distributed perception and centralized decision-making, and chooses to adopt the second-level end-to-end autonomous protection strategy or the third-level station-end joint protection strategy according to whether the uplink between the unmanned cluster and the measurement and control station is available. After the corresponding strategy is executed, it is judged whether the performance of the measurement and control link meets the preset requirements, so as to complete the recovery of the measurement and control link or make a new anti-interference decision.

[0011] Furthermore, in the first-level intra-terminal passive suppression strategy, all terminals in the unmanned cluster are subject to interference below the preset threshold. Each terminal independently makes its own anti-interference decision based on the interference perception results and measurement and control link performance evaluation results obtained internally, and completes passive interference suppression.

[0012] Specifically, the process of the first-level intra-end passive suppression strategy is as follows: Each terminal in the unmanned cluster makes anti-interference decisions based on its own interference perception results and measurement and control link performance evaluation results. It selects passive protection measures that match the current external electromagnetic interference signal based on the type of external electromagnetic interference signal and its own configured passive cognitive anti-interference strategy. Passive protection measures include time domain, frequency domain and transform domain interference suppression measures. Subsequently, each terminal performs corresponding passive interference suppression processing measures at the terminal baseband through passive protection means according to the decision result obtained by its own anti-interference decision; After the passive interference suppression measures are executed, the terminal performs measurement and control link performance evaluation again to determine the effectiveness of the passive interference suppression measures; If the measurement and control link performance evaluation shows that the measurement and control link performance has met the preset requirements, it means that the measurement and control link has returned to normal and passive interference suppression is completed; if the measurement and control link performance evaluation shows that the measurement and control link performance still does not meet the preset requirements, the anti-interference decision of the terminal is re-made, new passive protection measures are selected, and new passive interference suppression processing measures are implemented until the measurement and control link performance meets the preset requirements.

[0013] Furthermore, in the second-level terminal-to-terminal autonomous protection strategy, all terminals in the unmanned cluster are subject to interference higher than the preset threshold, and the measurement and control links between all terminals and the measurement and control stations are disconnected. At this time, the cluster head of the unmanned cluster summarizes the interference perception results of each terminal, makes a centralized anti-interference decision, and obtains the measurement and control link optimization result; the cluster head of the unmanned cluster then sends the measurement and control link optimization result to all other terminals and measurement and control stations in the unmanned cluster. All terminals and measurement and control stations in the unmanned cluster modify the corresponding measurement and control link parameters based on the measurement and control link optimization result to complete active interference avoidance.

[0014] Specifically, the process of the second-level terminal-to-terminal autonomous protection strategy is as follows: each terminal in the unmanned cluster sends its own interference perception results and measurement and control link performance evaluation results to the cluster head of the unmanned cluster. After receiving the corresponding information data, the cluster head aggregates and integrates the results to obtain the overall interference situation of the unmanned cluster and the cluster measurement and control link performance; The cluster head of the unmanned cluster makes a centralized anti-interference decision based on the overall interference situation and the cluster measurement and control link performance, and sends the measurement and control link optimization result to all other terminals in the unmanned cluster, and sends the measurement and control link optimization result to the measurement and control station in the form of broadcast; all terminals of the unmanned cluster and the measurement and control station execute link switching processing measures to rebuild the measurement and control link based on the measurement and control link optimization result; then, each terminal evaluates its own measurement and control link performance again to determine the effectiveness of the link switching processing measures; If the measurement and control link performance evaluation shows that the measurement and control link performance has met the preset requirements, it means that the measurement and control link has returned to normal and active interference avoidance is completed; if the measurement and control link performance evaluation shows that the measurement and control link performance still does not meet the preset requirements, a centralized anti-interference decision is made again until the measurement and control link performance meets the preset requirements.

[0015] Furthermore, in the third-level station-side joint protection strategy, all terminals in the unmanned cluster are subject to interference higher than the preset threshold, but there is at least one terminal that still maintains a measurement and control link with the measurement and control station. At this time, these terminals that still maintain the measurement and control link send the distributed perception results of the unmanned cluster and the measurement and control link performance evaluation results corresponding to these terminals to the measurement and control station. The measurement and control station makes intelligent anti-interference decisions based on the resource status of its own measurement and control system and obtains decision results. The measurement and control station sends the decision results to these terminals that still maintain the measurement and control link, which share the results with the unmanned cluster and execute corresponding measures to complete the cognitive strong interference protection processing.

[0016] Specifically, after the intelligent anti-interference decision is made, the measures corresponding to the decision results include passive interference suppression measures and link parameter reconstruction measures; the passive interference suppression measures include time domain interference suppression, frequency domain interference suppression and transform domain interference suppression; the link parameter reconstruction measures are to establish a new measurement and control link, and the measurement and control station determines the frequency, bandwidth, information rate, spread spectrum code rate, modulation mode, code type and transmission power in the new measurement and control link based on the resource status of its own measurement and control system.

[0017] Specifically, the process of the third-level station-side joint protection strategy is as follows: each terminal in the unmanned cluster sends its own interference perception results and measurement and control link performance evaluation results to the measurement and control station through the terminal that still maintains the measurement and control link. After the measurement and control station receives the corresponding information data, it aggregates and integrates the results; The measurement and control station makes intelligent anti-interference decisions based on the interference perception results of each terminal and the measurement and control link performance evaluation results, combined with the preset requirements of the measurement and control link performance, and the measurement and control station's own hardware resource usage and spectrum resource usage, and obtains corresponding protection measures that match the current external electromagnetic interference signal as the decision result; the corresponding protection measures include passive interference suppression measures and link parameter reconstruction measures. The measurement and control station sends the obtained passive interference suppression measures or link parameter reconstruction measures to the terminals that still maintain the measurement and control link, and then these terminals share them with the unmanned cluster. All terminals in the unmanned cluster perform interference suppression or link reconstruction under the action of the corresponding protection measures, thereby completing cognitive strong interference protection processing.

[0018] In summary, due to the adoption of this technical solution, the beneficial effects of the present invention are as follows: The goal of the present invention is to ensure that unmanned cluster measurement and control equipment can effectively resist interference in harsh electromagnetic environments. By achieving this goal, the present invention provides unmanned clusters with stable and reliable measurement and control communication capabilities, which can maintain efficient operation even under strong interference conditions.

[0019] The present invention introduces a three-level cognitive anti-interference strategy. This strategy is specially optimized for complex electromagnetic environments, so that the anti-interference performance of unmanned cluster measurement and control equipment is improved. By adopting this layered cognitive method, the present invention not only enhances the perception and recognition capabilities of interference signals, but also realizes a more active and flexible anti-interference mechanism, thereby ensuring that the unmanned cluster can still maintain its normal operating performance and achieve mission objectives when facing complex electromagnetic environments.

[0020] The present invention makes full use of the characteristics of the unmanned swarm platform and strengthens the interference perception and cognitive functions of related systems. Through comprehensive analysis of internal and external information of the unmanned swarm, the present invention can more accurately adjust the system's operating mode according to the current electromagnetic environment conditions and respond to potential or actual interference threats in the most optimized way. This intelligent processing method enables the unmanned swarm to have higher reliability and adaptability when performing tasks.

[0021] In addition, the present invention emphasizes the importance of station-side cooperation and combines active and passive related protection strategies to build a comprehensive cognitive anti-interference system, effectively improving the protection level against strong interference signals. The application of this method not only strengthens the overall anti-interference capability of the unmanned cluster, but also ensures that a stable measurement and control communication link can be maintained under any circumstances, providing a solid guarantee for the successful operation of the unmanned cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of the overall process of the method of the present invention; Figure 2 It is a flow chart of the first-level cognitive anti-interference strategy (passive inhibition within the terminal) in the present invention; Figure 3 It is a flow chart of the second-level cognitive anti-interference strategy (autonomous protection between terminals) in the present invention; Figure 4 It is a flow chart of the third-level cognitive anti-interference strategy (station-side joint protection) in the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The core of the cognitive anti-interference method of unmanned cluster hierarchical linkage proposed in the present invention is to adopt a three-level cognitive anti-interference strategy to complete the interference suppression of external electromagnetic interference signals, thereby improving the anti-interference capability of unmanned cluster measurement and control equipment in complex electromagnetic environments.

[0026] The first-level cognitive anti-interference strategy is the intra-terminal passive suppression strategy: each terminal in the unmanned cluster uses its own internal cognitive anti-interference strategy, and the terminal performs autonomous perception and rapid decision-making to achieve passive interference suppression based on the time and frequency domain.

[0027] The second-level cognitive anti-interference strategy is the terminal-to-terminal autonomous protection strategy: autonomous collaboration of unmanned clusters, distributed cluster perception, centralized decision-making, and active interference avoidance through link optimization; The third-level cognitive anti-interference strategy is the station-side joint protection strategy: the ground station and the unmanned cluster are linked, the cluster has distributed perception, and the station-side makes precise decisions, combining active and passive methods to achieve cognitive strong interference protection.

[0028] The three-level cognitive anti-interference strategy and its corresponding decision-making process constructed by the present invention in combination with the characteristics of the unmanned cluster platform and the dynamic changes of the measurement and control link can further enhance the interference perception and cognitive capabilities of the unmanned cluster, achieve fast and stable anti-interference strategy optimization and active and flexible anti-interference effects, and improve the anti-interference capability of the unmanned cluster measurement and control equipment in complex electromagnetic environments.

[0029] The details of the method of the present invention will be described in detail from the aspects of various embodiments below, wherein Embodiment 1 is an overview of the overall implementation process of the method of the present invention.

[0030] Example 1 like Figure 1 As shown in the figure, a cognitive anti-interference method for hierarchical linkage of unmanned clusters is adopted, which adopts a three-level cognitive anti-interference strategy. The unmanned cluster will automatically select three anti-interference strategies, namely, passive suppression within the terminal, autonomous protection between terminals, and joint protection between stations, based on the interference perception results of each terminal and the link performance evaluation results, to achieve efficient and reliable interference protection. The implementation steps of the specific process are as follows: S1: Interference perception and link performance evaluation of each terminal. Each terminal in the unmanned cluster receives external electromagnetic interference signals, completes interference detection, identification and parameter analysis, and performs link performance evaluation based on parameters such as the received link lock status and bit error rate to obtain the interference threat level of the terminal.

[0031] S2: Determine the interference threat level of the terminal. If the interference threat level of the terminal is "weak", proceed to step S3; if the interference threat level of the terminal is "strong", proceed to step S4.

[0032] S3: Passive suppression within the terminal. In each terminal, based on the interference perception results and link performance evaluation results, independent anti-interference decisions are made to complete passive interference suppression, and the measurement and control link returns to normal.

[0033] S4: Report the results to the cluster head. Each terminal sends the interference perception and link evaluation results to the cluster head of the unmanned cluster; the cluster head is an individual preset in the unmanned cluster for coordinating and managing each terminal. It is also an unmanned system terminal and can be designated as the head node or leader of the unmanned cluster according to actual conditions.

[0034] S5: The cluster head completes the aggregation of perception results and link evaluation results. After receiving the interference perception and link performance evaluation results of each terminal, the cluster head of the unmanned cluster aggregates and fuses the results to obtain the overall interference situation of the unmanned cluster and the cluster link performance.

[0035] S6: Determine whether the cluster link performance meets the preset requirements. If the cluster link performance meets the preset requirements, proceed to step S12; if the cluster link performance still does not meet the preset requirements, proceed to step S7.

[0036] S7: Determine whether the cluster uplink is available. According to the link performance evaluation results sent by each terminal, determine the availability of the uplink measurement and control link between each terminal in the unmanned cluster and the measurement and control station; if there is an available measurement and control link, proceed to step S9; if the measurement and control links of all terminals in the unmanned cluster are unavailable, proceed to step S8.

[0037] S8: Autonomous protection between terminals. The cluster head of the unmanned cluster makes a centralized anti-interference decision based on the distributed perception results, obtains the link optimization result, and sends the link optimization result to other terminals and measurement and control stations in the unmanned cluster. After that, all terminals and measurement and control stations modify the link parameters at the same time.

[0038] S9: Joint protection at the station end. The unmanned cluster sends the distributed perception results and link performance evaluation results to the measurement and control station. The measurement and control station conducts a comprehensive analysis based on the resource status of the measurement and control system, and makes intelligent anti-interference decisions to obtain the decision results of passive interference suppression processing or active link parameter adjustment, and sends the decision results to the unmanned cluster. The unmanned cluster performs cognitive strong interference protection processing based on the decision results.

[0039] S10: Determine whether there is no response for a long time. If after the cognitive strong interference protection process, the measurement and control station or each terminal of the unmanned cluster still does not respond within the preset time, then go to step S11; if there is a normal measurement and control operation response, then go to step S12.

[0040] S11: The measurement and control station and all terminals load the preset parameters. When the measurement and control station or the terminals of the unmanned cluster do not respond for a long time, it is determined that the measurement and control links between the measurement and control station and all terminals in the unmanned cluster are disconnected. At this time, the measurement and control station and each terminal are loaded with the same measurement and control link parameters agreed in advance, and the initial link recovery measures are executed. After the measurement and control link is restored, the decision optimization is performed.

[0041] S12: The measurement and control link is restored. After the unmanned cluster completes the three-level cognitive anti-interference strategy, the measurement and control link returns to normal.

[0042] Example 2 Based on Example 1, this example introduces the first-level passive suppression strategy in detail. This strategy adopts a passive suppression protection mode when the interference of any terminal in the unmanned cluster is weak, so as to restore the corresponding measurement and control link without affecting other terminals in the unmanned cluster. Figure 2 The hint, Figure 2 The dotted box content represents the overview of the relevant content of the overall process in Example 1, and the following is a detailed process introduction of step S3.

[0043] S31: Terminal anti-interference decision. Each terminal in the unmanned cluster makes an anti-interference decision based on the interference perception results and the measurement and control link performance evaluation results. Depending on the type of interference, it automatically selects the most suitable passive protection method that matches the current external electromagnetic interference signal, which may include various interference suppression methods such as time domain, frequency domain and transform domain.

[0044] S32: Interference suppression processing. Each terminal performs corresponding passive interference suppression processing measures at the terminal baseband through passive protection means according to the decision result obtained by its own anti-interference decision.

[0045] S33: Measurement and control link performance evaluation: After executing the passive interference suppression processing measure, each terminal performs measurement and control link performance evaluation again to determine the effectiveness of the passive interference suppression processing measure.

[0046] S34: Determine whether the measurement and control link performance meets the requirements. If the measurement and control link performance evaluation shows that the measurement and control link performance meets the preset requirements, proceed to step S35; if the measurement and control link performance still does not meet the preset requirements, return to step S31 and re-make the anti-interference decision of the terminal.

[0047] S35: The measurement and control link is restored. At this point, the measurement and control link performance has met the preset requirements, the passive suppression of external electromagnetic interference is completed, and the link is restored to normal.

[0048] Example 3 Based on any of the above embodiments, this embodiment introduces the second-level terminal autonomous protection strategy in detail. When the unmanned cluster is subject to strong interference and all terminals are interfered with, resulting in the disconnection of the measurement and control link, the strategy adopts the terminal autonomous protection mode to restore the measurement and control link through link optimization. Figure 3 The specific process is shown in Figure 2. Figure 3 The dotted box content represents the overview of the relevant content of the overall process in Example 1, and the following is a detailed process introduction of step S8.

[0049] S81: Cluster head anti-interference decision. After each terminal in the unmanned cluster completes interference perception and measurement and control link performance evaluation, it reports to the cluster head of the unmanned cluster, and the cluster head completes the fusion of the interference perception results and the measurement and control link performance evaluation results. In this embodiment, the cluster head makes a centralized anti-interference decision based on the overall interference situation of the unmanned cluster. At this time, the unmanned cluster is subject to strong interference. The cluster head automatically selects the best measurement and control link from the measurement and control link library based on parameters such as interference intensity, interference frequency band, and interference type to avoid the interference frequency band and output the best measurement and control link code. Since the computing resources and storage resources of the unmanned cluster are limited, the link optimization decision space is small, which can improve the speed and success rate of cluster head decision-making.

[0050] S82: Broadcasting and sending link optimization results to the measurement and control station. After completing the centralized anti-interference decision, the cluster head sends the optimal measurement and control link code obtained by the decision to other terminals through the shared collaborative link in the unmanned cluster, and also sends it to the measurement and control station through broadcasting.

[0051] S83: Each terminal and the measurement and control station reestablishes the link. After receiving and confirming the best measurement and control link code, the other terminals and measurement and control stations in the unmanned cluster immediately switch the currently interfered measurement and control link to the preferred measurement and control link, and complete the reconstruction of the new measurement and control link.

[0052] S84: Measurement and control link performance evaluation: After executing the above link switching processing measures, each terminal performs measurement and control link performance evaluation again to determine the effectiveness of the autonomous protection between terminals.

[0053] S85: Determine whether the measurement and control link performance meets the requirements. If the measurement and control link performance evaluation shows that the measurement and control link performance meets the preset requirements, proceed to step S86; if the measurement and control link performance still does not meet the preset requirements, return to step S81 and re-perform the centralized anti-interference decision of the cluster head.

[0054] S86: The measurement and control link is restored. At this point, the measurement and control link performance has met the preset requirements, the end-to-end autonomous protection against external electromagnetic interference is completed, and the link is restored to normal.

[0055] Example 4 Based on any of the above embodiments, this embodiment introduces the third-level terminal autonomous protection strategy in detail. When the unmanned cluster is subject to strong interference, but only some terminals are interfered with, resulting in the disconnection of the measurement and control link, the strategy adopts a station-side joint protection method, through cluster distributed perception, station-side precise decision-making, combined with active and passive methods to achieve cognitive strong interference protection processing. Figure 4 The specific process is shown in Figure 2. Figure 4 The dotted box content represents the overview of the relevant content of the overall process in Example 1, and the following is a detailed process introduction of step S9.

[0056] S91: The perception and link evaluation results are sent to the measurement and control station. The unmanned cluster sends the interference perception results of each terminal and the measurement and control link performance evaluation results to the measurement and control station.

[0057] S92: The measurement and control station completes the aggregation of perception and link evaluation results. The measurement and control station receives and determines the interference perception results and measurement and control link performance evaluation results corresponding to each terminal, aggregates and integrates the corresponding information data, and obtains the overall interference situation and measurement and control link status of the unmanned cluster.

[0058] S93: Intelligent anti-interference decision-making of the measurement and control station. The measurement and control station uses deep reinforcement learning and other decision-making methods based on the interference perception results of each terminal and the measurement and control link performance evaluation results, combined with the preset requirements of the measurement and control link performance, as well as the measurement and control station's own hardware resource usage and spectrum resource usage, to make intelligent anti-interference decisions and obtain the most suitable and matching protection measures for the current external electromagnetic interference signal as the decision result.

[0059] In this embodiment, the measures corresponding to the decision results include passive interference suppression measures and link parameter reconstruction measures; the passive interference suppression measures include time domain interference suppression, frequency domain interference suppression and transform domain interference suppression; the link parameter reconstruction measures are to establish a new measurement and control link, and the measurement and control station determines the frequency, bandwidth, information rate, spread spectrum code rate, modulation mode, code type and transmission power in the new measurement and control link based on the resource status of its own measurement and control system.

[0060] S94: Determine the anti-interference means. If the measure corresponding to the decision result obtained by the intelligent anti-interference decision is a passive interference suppression measure, then proceed to step S95; if the measure corresponding to the decision result obtained by the intelligent anti-interference decision is a link parameter reconstruction measure, then proceed to step S97.

[0061] S95: Passive interference suppression measures are reported to the unmanned cluster. The measurement and control station sends the decision result corresponding to the passive interference suppression measure to the unmanned cluster, and the unmanned cluster sends it to each terminal through its internal shared collaborative link.

[0062] S96: The terminal starts the passive interference suppression means. After receiving and confirming the decision result, each terminal starts to execute the passive interference suppression measures and then enters step S99.

[0063] S97: Reporting the link parameter reconstruction measures to the unmanned cluster. The measurement and control station sends the decision result of the corresponding link parameter reconstruction measures to the unmanned cluster, and the unmanned cluster sends it to each terminal through its internal shared collaborative link.

[0064] S98: The terminal and the measurement and control station rebuild the measurement and control link. After receiving and confirming the decision result, each terminal modifies the measurement and control link parameters in the radio frequency and baseband, and rebuilds the measurement and control link.

[0065] S99: Measurement and control link performance evaluation. After executing the above-mentioned cognitive strong interference protection process, each terminal performs measurement and control link performance evaluation again to determine the effectiveness of the station-side joint protection.

[0066] S910: Determine whether the measurement and control link performance meets the requirements. If the measurement and control link performance evaluation shows that the measurement and control link performance has met the preset requirements, proceed to step S911; if the measurement and control link performance still does not meet the preset requirements, return to step S91 and re-perform the intelligent anti-interference decision of the measurement and control station in the station-side joint protection.

[0067] S911: The measurement and control link is restored. At this point, the measurement and control link performance has met the preset requirements, the station-side joint protection against external electromagnetic interference has been completed, and the link has returned to normal.

Claims

1. A cognitive anti-interference method for unmanned cluster hierarchical linkage, characterized by: For each unmanned system terminal in the unmanned cluster, the interference threat level of each terminal is evaluated according to the strength of the external electromagnetic interference signal, and the interference cognitive evaluation result of the unmanned cluster is obtained; based on the interference cognitive evaluation result, a three-level cognitive anti-interference strategy is used to suppress the interference of the external electromagnetic interference signal, so that the measurement and control link of the unmanned cluster can be restored to normal; Among them, the three-level cognitive anti-interference strategy includes the first-level intra-terminal passive suppression strategy, the second-level inter-terminal autonomous protection strategy, and the third-level station-end joint protection strategy; the intra-terminal passive suppression strategy is performed by each terminal independently to suppress passive interference, the inter-terminal autonomous protection strategy is performed by all terminals in the unmanned cluster to collaboratively perform active interference avoidance, and the station-end joint protection strategy is performed by the measurement and control station and the unmanned cluster to link data, and perform cognitive strong interference protection processing based on the decision results of the measurement and control station.

2. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 1 is characterized by: In the first-level passive suppression strategy, each terminal in the unmanned cluster is configured with a preset passive cognitive anti-interference strategy. Each terminal makes independent decisions by autonomously sensing external electromagnetic interference signals and completes passive interference suppression based on the time-frequency domain. In the second-level terminal-to-terminal autonomous protection strategy, each terminal in the unmanned cluster uses autonomous collaboration to enable the unmanned cluster to perform distributed perception. The cluster head of the unmanned cluster completes centralized decision-making and uses link optimization to achieve active interference avoidance. In the third-level station-side joint protection strategy, the unmanned cluster sends the relevant data obtained by distributed perception to the measurement and control station. The measurement and control station determines the corresponding decision results based on the resource status of its own measurement and control system and sends them to the unmanned cluster. The unmanned cluster completes the cognitive strong interference protection processing based on the decision results.

3. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 2 is characterized by: The interference cognitive assessment results of the unmanned cluster are divided into weak and strong levels according to the preset threshold. When the interference cognitive assessment result of the unmanned cluster is a weak level, only the first-level passive suppression strategy is used to suppress the external electromagnetic interference signal through passive interference suppression, so that the measurement and control link of the unmanned cluster can be restored to normal. When the interference cognition assessment result of the unmanned cluster is a strong level, the cluster head of the unmanned cluster summarizes the result information of distributed perception and centralized decision-making, and chooses to adopt the second-level end-to-end autonomous protection strategy or the third-level station-end joint protection strategy according to whether the uplink between the unmanned cluster and the measurement and control station is available. After the corresponding strategy is executed, it is judged whether the performance of the measurement and control link meets the preset requirements, so as to complete the recovery of the measurement and control link or make a new anti-interference decision.

4. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 3 is characterized by: In the first-level intra-terminal passive suppression strategy, all terminals in the unmanned cluster are subject to interference below the preset threshold. Each terminal independently makes its own anti-interference decision based on the interference perception results and measurement and control link performance evaluation results obtained internally, and completes passive interference suppression.

5. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 4 is characterized in that: The process of the first-level intra-terminal passive suppression strategy is as follows: Each terminal in the unmanned cluster makes anti-interference decisions based on its own interference perception results and measurement and control link performance evaluation results. It selects passive protection measures that match the current external electromagnetic interference signal based on the type of external electromagnetic interference signal and its own configured passive cognitive anti-interference strategy. Passive protection measures include time domain, frequency domain and transform domain interference suppression measures. Subsequently, each terminal performs corresponding passive interference suppression processing measures at the terminal baseband through passive protection means according to the decision result obtained by its own anti-interference decision; After the passive interference suppression measures are executed, the terminal performs measurement and control link performance evaluation again to determine the effectiveness of the passive interference suppression measures; If the measurement and control link performance evaluation shows that the measurement and control link performance has met the preset requirements, it means that the measurement and control link has returned to normal and passive interference suppression is completed; If the measurement and control link performance evaluation shows that the measurement and control link performance still does not meet the preset requirements, the anti-interference decision of the terminal is re-made, new passive protection measures are selected, and new passive interference suppression processing measures are implemented until the measurement and control link performance meets the preset requirements.

6. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 3 is characterized by: In the second-level terminal-to-terminal autonomous protection strategy, all terminals in the unmanned cluster are subject to interference higher than the preset threshold, and the measurement and control links between all terminals and the measurement and control stations are disconnected. At this time, the cluster head of the unmanned cluster summarizes the interference perception results of each terminal, makes a centralized anti-interference decision, and obtains the measurement and control link optimization result; the cluster head of the unmanned cluster then sends the measurement and control link optimization result to all other terminals and measurement and control stations in the unmanned cluster. All terminals and measurement and control stations in the unmanned cluster modify the corresponding measurement and control link parameters based on the measurement and control link optimization result to complete active interference avoidance.

7. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 6 is characterized in that: The process of the second-level terminal-to-terminal autonomous protection strategy is as follows: each terminal in the unmanned cluster sends its own interference perception results and measurement and control link performance evaluation results to the cluster head of the unmanned cluster. After receiving the corresponding information data, the cluster head aggregates and integrates the results to obtain the overall interference situation of the unmanned cluster and the cluster measurement and control link performance; The cluster head of the unmanned cluster makes a centralized anti-interference decision based on the overall interference situation and the cluster measurement and control link performance, and sends the measurement and control link optimization result to all other terminals in the unmanned cluster. At the same time, the measurement and control link optimization result is sent to the measurement and control station in the form of broadcast; All terminals and the measurement and control stations of the unmanned cluster execute link switching processing measures to rebuild the measurement and control link based on the measurement and control link optimization results; then, each terminal performs its own measurement and control link performance evaluation again to determine the effectiveness of the link switching processing measures; If the measurement and control link performance evaluation shows that the measurement and control link performance has met the preset requirements, it means that the measurement and control link has returned to normal and active interference avoidance is completed; If the measurement and control link performance evaluation shows that the measurement and control link performance still does not meet the preset requirements, a centralized anti-interference decision is made again until the measurement and control link performance meets the preset requirements.

8. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 3 is characterized by: In the third-level station-side joint protection strategy, all terminals in the unmanned cluster are subject to interference higher than the preset threshold, but there is at least one terminal that still maintains a measurement and control link with the measurement and control station. At this time, these terminals that still maintain the measurement and control link send the distributed perception results of the unmanned cluster and the measurement and control link performance evaluation results corresponding to these terminals to the measurement and control station. The measurement and control station makes intelligent anti-interference decisions based on the resource status of its own measurement and control system and obtains decision results. The measurement and control station sends the decision results to these terminals that still maintain the measurement and control link, which share the results with the unmanned cluster and execute corresponding measures to complete the cognitive strong interference protection processing.

9. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 8 is characterized by: After the intelligent anti-interference decision is made, the measures corresponding to the decision results include passive interference suppression measures and link parameter reconstruction measures; passive interference suppression measures include time domain interference suppression, frequency domain interference suppression and transform domain interference suppression; link parameter reconstruction measures are to establish a new measurement and control link. The measurement and control station determines the frequency, bandwidth, information rate, spread spectrum code rate, modulation mode, code type and transmission power in the new measurement and control link based on the resource status of its own measurement and control system.

10. The cognitive anti-interference method of unmanned cluster hierarchical linkage according to claim 8 is characterized in that: The process of the third-level station-side joint protection strategy is as follows: each terminal in the unmanned cluster sends its own interference perception results and measurement and control link performance evaluation results to the measurement and control station through the terminal that still maintains the measurement and control link. After the measurement and control station receives the corresponding information data, it aggregates and integrates the results; The measurement and control station makes intelligent anti-interference decisions based on the interference perception results of each terminal and the measurement and control link performance evaluation results, combined with the preset requirements of the measurement and control link performance, and the measurement and control station's own hardware resource usage and spectrum resource usage, and obtains corresponding protection measures that match the current external electromagnetic interference signal as the decision result; the corresponding protection measures include passive interference suppression measures and link parameter reconstruction measures. The measurement and control station sends the obtained passive interference suppression measures or link parameter reconstruction measures to the terminals that still maintain the measurement and control link, and then these terminals share them with the unmanned cluster. All terminals in the unmanned cluster perform interference suppression or link reconstruction under the action of the corresponding protection measures, thereby completing cognitive strong interference protection processing.

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