Anti-drone jamming device

Abstract

The application provides a UAV countermeasure jamming device, and relates to the technical field of UAVs.The device comprises a monitoring and locking module for locking a target UAV; a signal analysis module for obtaining target signal characteristics and obtaining a target jamming signal; a jamming transmission module for activating a transmission device to transmit the target jamming signal to the target UAV and obtaining target jamming records; a jamming evaluation module for obtaining a target jamming effect; a countermeasure analysis module for obtaining a countermeasure jamming evaluation function to perform analysis and obtain a target countermeasure index; and a countermeasure quantization module for quantizing the countermeasure capability of a target countermeasure jamming device. The application can solve the problem that the existing countermeasure jamming process of a UAV cannot be monitored and evaluated in real time, and the performance of a UAV countermeasure jamming device cannot be effectively quantized, thereby improving the precision, effectiveness and intelligent level of UAV countermeasure jamming.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to UAV counter-jamming devices. Background Technology

[0002] With the rapid development of drone technology, drones are increasingly used in military and civilian fields, and the security threats they pose are becoming more prominent. Illegal intrusion, reconnaissance, and interference are frequent occurrences, posing potential risks to important facilities and public safety. To effectively address these threats, researchers have developed various counter-drone technologies, mainly divided into active countermeasures and passive detection technologies. Active countermeasures interfere with the communication and navigation systems of drones, preventing their normal operation or forcing them to land. Common jamming methods include full-band jamming, directional jamming, and scanning jamming. These technologies can, to a certain extent, achieve countermeasures and control over drones. However, existing drone jamming countermeasures technologies have some problems and shortcomings. On the one hand, the assessment of jamming effects is not accurate and scientific enough. Current assessment methods are mostly based on experience or simple indicators, making it difficult to comprehensively and objectively reflect the actual effect of jamming. On the other hand, the intelligence level of counter-jamming equipment needs to be improved. Existing equipment has limitations in adapting to the signal modes and protocol types of different drone models, failing to achieve precise and efficient jamming. Furthermore, for drones that do not rely on external communication for flight control, such as drones with autonomous control capabilities, the control effect of radio countermeasures systems is poor.

[0003] In summary, existing technologies for countering UAV jamming have several technical problems, including difficulty in accurately locating and identifying target UAVs, inability to select appropriate jamming signals based on their signal characteristics, lack of real-time monitoring and effectiveness evaluation methods during the jamming process, and inability to effectively quantify the performance of UAV jamming countermeasures equipment. Summary of the Invention

[0004] The purpose of this application is to provide a drone counter-jamming device to solve the technical problems of existing technologies in the process of drone jamming countermeasures, such as difficulty in accurately locating and identifying target drones, inability to select appropriate jamming signals based on their signal characteristics, lack of real-time monitoring and effect evaluation methods in the jamming process, and inability to effectively quantify the performance of drone counter-jamming equipment.

[0005] In view of the above problems, this application provides a drone counter-jamming device. The drone counter-jamming device includes: a monitoring and locking module for capturing and locking a target drone through a monitoring device; a signal analysis module for acquiring target signal characteristics of the target drone and matching these characteristics in a jamming database to obtain a target jamming signal; a jamming transmission module for activating a transmission device and transmitting the target jamming signal to the target drone through the transmission device, and monitoring and obtaining target jamming records in real time; a jamming evaluation module for evaluating and analyzing the target jamming records to obtain the target jamming effect; a counter-jamming analysis module for acquiring a counter-jamming evaluation function and performing counter-jamming analysis on the target jamming effect based on the counter-jamming evaluation function to obtain a target counter-jamming index; and a counter-jamming quantification module for quantifying the counter-jamming capability of the target counter-jamming device mounted on the target drone using the target counter-jamming index.

[0006] Preferably, the signal analysis module is further configured to: read predetermined communication indicators; collect features of the target UAV based on the predetermined communication indicators to obtain target communication signal features; read predetermined navigation indicators; collect features of the target UAV based on the predetermined navigation indicators to obtain target navigation signal features; and the target communication signal features and the target navigation signal features constitute the target signal features.

[0007] Preferably, the predetermined communication indicators include at least frequency band, signal type, modulation method, coding method, and communication protocol.

[0008] Preferably, the predetermined navigation indicators include at least a satellite navigation system, a positioning method, and a navigation mode.

[0009] Preferably, the signal analysis module is further configured to: extract a first interference signal from the interference database and obtain a first data group of the first interference signal; based on the predetermined communication index and the predetermined navigation index, traverse and match in the first data group to obtain a first signal feature of the first interference signal; perform similarity analysis on the target signal feature and the first signal feature to obtain a first similarity; if the first similarity reaches a predetermined similarity threshold, then the first interference signal is used as the target interference signal.

[0010] Preferably, the signal analysis module is further configured to: extract a first interference simulation record from the first data group; read a predetermined interference effect index, and extract the first interference simulation record based on the predetermined interference effect index to obtain a first interference effect parameter; perform a weighted calculation on the normalized first interference effect parameter to obtain a first interference effect coefficient; and adjust the first similarity using the first interference effect coefficient as the adjustment weight.

[0011] Preferably, the predetermined interference effect indicators include at least the signal strength degradation rate, data transmission interruption frequency, bit error rate, and navigation deviation rate.

[0012] Preferably, the interference evaluation module is further configured to: obtain an interference effect benchmark, and perform a weighted calculation on the interference effect benchmark using the first interference effect coefficient as the interference effect evaluation weight to obtain the target interference effect.

[0013] Preferably, the interference evaluation module is further configured to: determine whether the target interference effect meets the predetermined interference constraint; if the predetermined interference constraint is not met, adjust the target interference signal.

[0014] Preferably, the countermeasure analysis module is further configured to: the expression of the countermeasure interference evaluation function is:

[0015] ;

[0016] It is the target countermeasure index, This refers to the target interference effect. It is the first interference effect parameter. Parameters The first interference effect parameters have a total of One parameter, and It is an integer greater than or equal to 4. The first one is the one mentioned Parameters The weighting coefficients.

[0017] In summary, the technical solution provided in this application has the following technical effects or advantages:

[0018] The system employs a monitoring and locking module to capture and lock onto a target drone using monitoring equipment; a signal analysis module to acquire the target drone's signal characteristics and match these characteristics against an interference database to obtain a target interference signal; an interference transmission module to activate a transmission device and transmit the target interference signal to the target drone, while simultaneously monitoring the interference records in real time; an interference evaluation module to evaluate and analyze the interference records to determine the interference effect; a countermeasure analysis module to obtain a countermeasure evaluation function and perform countermeasure analysis on the interference effect based on this function to obtain a target countermeasure index; and a countermeasure quantification module to quantify the countermeasure capability of the countermeasure equipment mounted on the target drone using the target countermeasure index. In other words, the system first uses monitoring equipment to capture and lock onto the target drone, then acquires its signal characteristics and matches them against an interference database to obtain a target interference signal. Next, it activates a transmission device to transmit the interference signal to the target drone and monitors the interference records in real time. Afterward, it evaluates and analyzes the interference records to obtain the interference effect, and then performs countermeasure analysis based on the countermeasure evaluation function to obtain a target countermeasure index. Ultimately, this index quantifies the countermeasure capabilities of the anti-jamming equipment on the target drone. It achieves precise positioning and identification of the target drone, selects appropriate jamming signals based on its signal characteristics, and transmits them in real time. Simultaneously, through real-time monitoring and scientific evaluation of the jamming effect, the jamming strategy is adjusted promptly. Finally, the performance of the drone's anti-jamming equipment is quantified using an anti-jamming evaluation function. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of the anti-jamming device for unmanned aerial vehicles (UAVs) in this application.

[0020] Figure 2 This is a flowchart illustrating the method execution corresponding to the anti-jamming device for unmanned aerial vehicles (UAVs) in this application.

[0021] Explanation of reference numerals in the attached figures:

[0022] The module includes a monitoring and locking module 11, a signal analysis module 12, an interference transmission module 13, an interference assessment module 14, a countermeasure analysis module 15, and a countermeasure quantification module 16. Detailed Implementation

[0023] This application provides a drone counter-jamming device, solving the technical problems of existing technologies in drone jamming countermeasures, such as difficulty in accurately locating and identifying target drones, inability to select appropriate jamming signals based on their signal characteristics, lack of real-time monitoring and effect evaluation methods during jamming implementation, and inability to effectively quantify the performance of drone counter-jamming equipment. It achieves accurate location and identification of target drones, selects appropriate jamming signals based on their signal characteristics and transmits them in real time, and adjusts the jamming strategy in a timely manner through real-time monitoring and scientific evaluation of the jamming effect. Finally, it uses a counter-jamming evaluation function to quantify the performance of the drone counter-jamming equipment.

[0024] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0025] Please see the appendix Figure 1 and attached Figure 2 This application provides a drone counter-jamming device, wherein the drone counter-jamming device specifically includes the following modules:

[0026] The monitoring and locking module 11 is used to capture and lock onto the target drone through a monitoring device;

[0027] Specifically, with the rapid development of drone technology, effectively capturing and locking onto target drones has become a key requirement in many fields such as security and the military. The technical solution of capturing and locking onto target drones through surveillance equipment aims to accurately locate targets, providing a solid foundation for subsequent monitoring, tracking, or countermeasures, and ensuring precise control of drones in complex and ever-changing environments.

[0028] First, the surveillance equipment, acting as the front-end "sentinel" of the entire system, works by utilizing advanced sensor technologies, such as optics, radar, or other detection methods, to perform comprehensive, all-around scanning and monitoring of the designated area. When a target drone enters its monitoring range, the equipment can quickly detect its presence. For example, in a low-altitude security scenario at an airport, surveillance equipment installed around the airport can monitor an airspace with a radius of 5 kilometers in real time. If an unauthorized drone intrudes, the equipment can detect its presence within 0.1 seconds. Then, the system initiates a locking procedure, using intelligent algorithms to analyze the drone's flight trajectory, speed, shape, and other multi-dimensional characteristics. This allows for accurate differentiation of the target drone from other objects, such as birds and aircraft, in complex environments, ensuring accurate locking. During this process, the surveillance equipment continuously tracks the target drone. Even if it attempts to evade monitoring through rapid changes of direction, ascents, or descents, the equipment can maintain a stable lock on the target thanks to its high-precision tracking algorithm, buying valuable time for subsequent handling measures.

[0029] In summary, the technical solution of capturing and locking onto target drones through monitoring equipment accurately locates the target drones, providing a solid foundation for subsequent monitoring, tracking, or countermeasures. This ensures precise control of drones in complex and ever-changing environments and effectively improves the efficiency and security of drone management in related fields.

[0030] Signal analysis module 12 is used to acquire the target signal features of the target UAV and to traverse and match the target signal features in the interference database to obtain the target interference signal;

[0031] Specifically, by acquiring the signal characteristics of the target UAV and matching the target jamming signal in the jamming database, the aim is to achieve precise jamming of the UAV, improve the effectiveness and targeting of countermeasures, and provide a scientific basis for adjusting subsequent jamming strategies.

[0032] First, after capturing and locking onto the target UAV using surveillance equipment, a specialized signal receiving and processing module extracts its unique signal characteristics from the UAV's communication, navigation, or control systems. This process typically involves multiple levels, including signal spectrum analysis, modulation pattern identification, and protocol parsing, to ensure the acquired signal characteristics are sufficiently representative and discriminative. For example, a short-time Fourier transform algorithm is used to convert the detected signal into a time-spectrum matrix, followed by binarization filtering and noise reduction to more clearly extract the UAV's image transmission or frequency-hopping signal characteristics. Then, the acquired target signal characteristics are traversed and matched against a pre-built interference database. The interference database stores a large number of known UAV models and their corresponding interference signal templates. Intelligent algorithms compare the target signal characteristics against these templates one by one to quickly find matching target interference signals. This matching process relies not only on basic information such as signal frequency and bandwidth but also comprehensively considers various parameters such as signal modulation characteristics and pulse repetition intervals to improve the accuracy and reliability of the matching. During the matching process, advanced algorithms such as deep learning networks can be used to perform online learning and knowledge base updates on the real-time acquired interference data, thereby continuously improving the system's adaptability and robustness.

[0033] In summary, by accurately acquiring the signal characteristics of the target UAV and efficiently matching them in the interference database, the accurate acquisition of the target interference signal was successfully achieved, providing a solid foundation for subsequent interference operations. This not only improves the accuracy and effectiveness of interference but also lays an important cornerstone for the intelligent development of UAV countermeasure technology.

[0034] The jamming transmission module 13 is used to activate the transmission device and transmit the target jamming signal to the target UAV through the transmission device, and to monitor and obtain the target jamming record in real time;

[0035] Specifically, by activating the transmitting equipment, the target jamming signal is transmitted to the target drone, and the target jamming record is monitored in real time. This aims to achieve effective jamming and precise control of the drone, and improve the pertinence and effectiveness of countermeasures.

[0036] First, after capturing and locking onto the target drone and acquiring its signal characteristics, the corresponding transmitting device is activated. This transmitting device retrieves a suitable target jamming signal from a jamming database based on the target drone's signal characteristics and its environment. For example, in a low-altitude security scenario at an airport, when an unauthorized drone is detected, a jamming signal matching the drone's signal characteristics is quickly selected from a database of various jamming signal templates. Then, the transmitting device transmits the target jamming signal to the target drone at an appropriate power and frequency, interfering with its communication link, navigation system, or control system, preventing it from receiving or processing commands normally. During this process, the transmitting device continuously monitors the transmission status and effect of the jamming signal, for example, by detecting parameters such as the intensity and frequency shift of the reflected signal to determine in real time whether the jamming signal was successfully transmitted and received by the target drone. Next, the system analyzes and processes the target jamming records obtained in real time. This includes recording and analyzing parameters such as the jamming signal's intensity, duration, and transmission frequency, as well as monitoring the drone's response, such as whether the drone experiences signal loss or abnormal flight. By analyzing this data, operators can promptly understand the effectiveness of the interference, providing a basis for adjusting subsequent interference strategies. For example, if a drone experiences a brief signal loss after receiving an interference signal but quickly resumes normal communication, operators can determine that the strength or frequency of the current interference signal may not be sufficient to continuously and effectively interfere with the drone, requiring further adjustments and optimizations.

[0037] In summary, by activating the transmitting equipment and accurately transmitting target jamming signals, while simultaneously monitoring the jamming effect in real time, effective jamming and precise control of the target UAV were successfully achieved, providing strong support for improving the practical effectiveness of UAV countermeasures technology.

[0038] Interference assessment module 14 is used to assess and analyze the target interference record to obtain the target interference effect;

[0039] Specifically, by evaluating and analyzing target interference records, the aim is to scientifically and comprehensively measure the actual effectiveness of interference measures, providing a solid basis for subsequent adjustments to interference strategies and system optimization. First, target interference records are collected, containing key data such as the strength, frequency, and duration of the interference signal, as well as the drone's response. For example, in an airport security drill, the system recorded the entire process of transmitting interference signals to a simulated intrusion drone, including the initial strength of the interference signal (-30dBm), the frequency range of 2.4GHz to 2.5GHz, the duration of 10 seconds, and the changes in the drone's flight state after receiving the interference signal. Then, a series of evaluation algorithms are used to analyze this data, such as calculating the loss of the interference signal during propagation using a signal strength attenuation model, and judging the degree of impact of the interference on its control system by combining the changes in the drone's flight attitude. Furthermore, environmental factors, such as weather conditions and terrain, are considered to have a potential impact on the interference effect. By establishing a multi-factor comprehensive evaluation model, the interference effect can be quantified more accurately. In a specific example, researchers found that in rainy conditions, the interference effect of the same intensity of interference signal on drones is reduced by about 20%. This finding further improves the environmental factor correction mechanism of the evaluation model. In summary, through in-depth evaluation and analysis of target interference records, accurate quantification and scientific evaluation of the interference effect have been achieved.

[0040] Countermeasure analysis module 15 is used to obtain a countermeasure interference evaluation function and perform countermeasure analysis on the target interference effect based on the countermeasure interference evaluation function to obtain a target countermeasure index;

[0041] Specifically, by obtaining the counter-jamming evaluation function and conducting counter-jamming analysis on the target jamming effect based on the function, the target counter-jamming index is finally obtained. This aims to achieve a scientific evaluation and quantification of the performance of UAV counter-jamming equipment, providing a solid basis for adjusting counter-jamming strategies and improving equipment.

[0042] First, after jamming the target drone, the system collects jamming records, which include key data such as the strength, frequency, and duration of the jamming signal, as well as the drone's response. Then, the system obtains a counter-jamming evaluation function. This function is typically a mathematical model that comprehensively considers multiple factors, such as the attenuation of the jamming signal, the duration of the drone's communication interruption, and the degree of flight attitude deviation. These factors are combined through specific weights and calculation methods to form a quantitative index that comprehensively reflects the effectiveness of the counter-jamming. In a specific example, the counter-jamming evaluation function can be expressed as: Target Counter-Jack Index = α × Jamming Signal Attenuation Rate + β × Communication Interruption Duration + γ × Flight Attitude Deviation, where α, β, and γ are the weighting coefficients of each factor, and α + β + γ = 1. Next, the system performs a counter-jamming analysis based on this evaluation function, substituting the data from the actual jamming records into the function for calculation to obtain a specific target counter-jamming index. This index can intuitively reflect the jamming effect of counter-jamming equipment on target drones. The higher the index, the better the jamming effect, and vice versa, the less effective the jamming effect, and the need to further optimize the counter-jamming strategy.

[0043] In summary, through in-depth evaluation and analysis of the target jamming effect, the performance of UAV counter-jamming equipment has been accurately quantified and scientifically evaluated, providing key support for the continuous optimization and intelligent development of UAV counter-jamming technology.

[0044] Countermeasure quantification module 16 is used to quantify the countermeasure capability of the target countermeasure jamming equipment carried on the target UAV through the target countermeasure index.

[0045] Specifically, the target countermeasure index quantifies the countermeasure capabilities of the anti-jamming equipment mounted on the target drone, aiming to scientifically evaluate the performance of this equipment. First, after evaluating and analyzing the effect of the target jamming, a specific target countermeasure index is obtained. This index is calculated using a scientific evaluation function, comprehensively considering various factors such as the strength, frequency, and duration of the jamming signal, as well as the drone's response. Then, this index is applied to quantify the performance of the anti-jamming equipment mounted on the target drone. In a specific example, a high target countermeasure index indicates that the equipment has strong anti-jamming and recovery capabilities when facing interference; conversely, a low index indicates that its performance needs improvement. For instance, multiple experiments have shown that when the target countermeasure index reaches 80 points or higher, the drone can quickly recover stable flight after being jammed, while below 50 points, the drone may experience flight abnormalities or even crash. Therefore, this index provides a direct understanding of the actual performance of the anti-jamming equipment.

[0046] In summary, by applying the target countermeasure index, the performance of UAV countermeasure jamming equipment has been accurately quantified and scientifically evaluated, providing key support for the continuous optimization and intelligent development of UAV countermeasure technology.

[0047] Furthermore, the signal analysis module is also used for:

[0048] Read the predefined communication indicators;

[0049] Based on the predetermined communication indicators, feature collection is performed on the target UAV to obtain target communication signal features;

[0050] Read the pre-defined navigation indicators;

[0051] Based on the predetermined navigation indicators, feature collection is performed on the target UAV to obtain target navigation signal features;

[0052] The target communication signal features and the target navigation signal features together constitute the target signal features.

[0053] Furthermore, the predetermined communication indicators include at least frequency band, signal type, modulation method, coding method, and communication protocol.

[0054] Furthermore, the predetermined navigation indicators include at least a satellite navigation system, a positioning method, and a navigation mode.

[0055] Specifically, by reading predetermined communication and navigation indicators, the target UAV is subjected to feature collection, and the target communication signal features and target navigation signal features are ultimately integrated into target signal features, aiming to comprehensively and accurately obtain the signal characteristics of the UAV.

[0056] First, predetermined communication indicators are read. These indicators include at least the frequency band, signal type, modulation method, encoding method, and communication protocol. For example, in a common consumer drone scenario, the frequency band might be concentrated at 2.4GHz or 5.8GHz, the signal type is a digital signal, the modulation method might be QPSK or OFDM, the encoding method might be convolutional code or Turbo code, and the communication protocol follows a specific drone communication standard. Then, based on these predetermined communication indicators, feature collection is performed on the target drone. Using specialized signal receiving and processing equipment, the signals emitted by the drone during communication are captured, and feature information conforming to the above indicators is extracted to obtain the target communication signal characteristics. Next, predetermined navigation indicators are read. These indicators include at least the satellite navigation system, positioning method, and navigation mode. Taking the satellite navigation system as an example, it might be GPS, BeiDou, or Galileo; the positioning method might be autonomous positioning or differential positioning; and the navigation mode might include waypoint navigation, route navigation, etc. Based on these predetermined navigation indicators, the system again performs feature collection on the target drone, obtaining its relevant signal characteristics during navigation, such as the satellite signal reception frequency, positioning accuracy, and navigation data update rate, thereby obtaining the target navigation signal characteristics. Finally, the target's communication signal characteristics are integrated with its navigation signal characteristics to form a complete target signal profile. This integration process ensures that the system can comprehensively understand the signal characteristics of the target UAV from multiple dimensions, providing a rich and accurate data foundation for subsequent analysis and processing.

[0057] In summary, by systematically collecting and integrating the communication and navigation signal characteristics of UAVs, a comprehensive acquisition of the signal characteristics of target UAVs was successfully achieved, providing crucial support for the precise implementation of UAV monitoring, tracking, and countermeasure technologies.

[0058] Furthermore, the signal analysis module is also used for:

[0059] Extract the first interference signal from the interference database and obtain the first data group of the first interference signal;

[0060] Based on the predetermined communication index and the predetermined navigation index, the first signal feature of the first interference signal is obtained by traversing and matching in the first data group.

[0061] A similarity analysis is performed between the target signal features and the first signal features to obtain a first similarity.

[0062] If the first similarity reaches a predetermined similarity threshold, then the first interference signal is used as the target interference signal.

[0063] Specifically, the system first extracts a first interference signal from an interference database and obtains its first data set. This database typically stores various known UAV models and their corresponding interference signal templates, accumulated through extensive experiments and practical applications. For example, the database may contain interference signal data from different types of UAVs, such as common consumer-grade UAVs, industrial-grade UAVs, and military reconnaissance UAVs. Then, based on predetermined communication and navigation indicators, a traversal matching process is performed within the first data set. These indicators cover key characteristics of UAV communication and navigation, such as communication frequency band, signal type, modulation method, encoding method, and communication protocol, as well as navigation satellite system, positioning method, and navigation mode. The system uses intelligent algorithms to compare the signal features in the first data set one by one, searching for the parts that match the target signal features, thereby obtaining the first signal feature of the first interference signal. In a specific example, if the target UAV's communication frequency band is 2.4GHz and the modulation method is QPSK, and a certain interference signal template in the database happens to have the same frequency band and modulation method, then the signal feature of that template will be extracted as the first signal feature. Next, a similarity analysis is performed between the target signal feature and the first signal feature to obtain the first similarity score. This analysis process typically employs specific similarity calculation algorithms, such as cosine similarity and Euclidean distance, to quantify the degree of similarity between the two signals. If the first similarity reaches a predetermined similarity threshold, for example, 85%, it indicates that the first interference signal has a high degree of matching with the signal characteristics of the target UAV and can effectively interfere with the target UAV's communication and navigation systems. Therefore, this first interference signal is considered the target interference signal. In a specific example, after similarity calculation, if the first similarity reaches 90%, which is higher than the set 85% threshold, then the first interference signal is determined to be the target interference signal and used in subsequent interference transmission steps.

[0064] In summary, by performing precise matching and similarity analysis on signals in the interference database, the accurate acquisition of target interference signals was successfully achieved.

[0065] Furthermore, the signal analysis module is also used for:

[0066] Extract the first interference simulation record from the first data group;

[0067] Read the predetermined interference effect index, and extract the first interference simulation record based on the predetermined interference effect index to obtain the first interference effect parameter;

[0068] The first interference effect parameter after normalization is weighted and calculated to obtain the first interference effect coefficient;

[0069] The first similarity is adjusted using the first interference effect coefficient as the adjustment weight.

[0070] Furthermore, the predetermined interference effect indicators include at least the signal strength degradation rate, data transmission interruption frequency, bit error rate, and navigation deviation rate.

[0071] Specifically, the system first extracts the first interference simulation record from the first data group in the interference database. These simulation records typically contain data under various interference scenarios, such as different environmental conditions, UAV models, and interference intensity. Then, predetermined interference effect indicators are read, including at least the signal strength degradation rate, data transmission interruption frequency, bit error rate, and navigation deviation rate. Based on these indicators, the system iterates through the first interference simulation record to obtain the first interference effect parameters. For example, in a simulated interference scenario, the signal strength degradation rate is 30%, the data transmission interruption frequency is 5 times per minute, the bit error rate is 2%, and the navigation deviation rate is 10 meters. Next, the normalized first interference effect parameters are weighted to obtain the first interference effect coefficients. Normalization is used to unify parameters of different dimensions and magnitudes to the same scale for easier comprehensive calculation. Weighting is performed by assigning different weights to each interference effect indicator based on its importance; for example, the signal strength degradation rate has a weight of 0.4, the data transmission interruption frequency has a weight of 0.3, the bit error rate has a weight of 0.2, and the navigation deviation rate has a weight of 0.1. Through weighted calculation, a coefficient comprehensively reflecting the interference effect is obtained, namely the first interference effect coefficient. Finally, the previously obtained first similarity is adjusted using this coefficient as the adjustment weight. For example, if the first similarity is 80% and the first interference effect coefficient is 0.85, then the adjusted similarity is 80% × 0.85 = 68%. This adjustment process fully considers the actual performance of the interference effect, ensuring that when selecting target interference signals, not only the matching degree of signal features is considered, but also the actual effect of interference, thereby improving the accuracy and effectiveness of countermeasures.

[0072] In summary, through in-depth mining and analysis of interference simulation records, combined with quantitative evaluation of predetermined interference effect indicators, the optimization and adjustment of interference signal selection was successfully achieved.

[0073] Furthermore, the interference evaluation module is also used to: obtain an interference effect benchmark, and perform a weighted calculation on the interference effect benchmark using the first interference effect coefficient as the interference effect evaluation weight to obtain the target interference effect.

[0074] Specifically, the target interference effect is obtained by acquiring an interference effect benchmark and then weighting the benchmark with a first interference effect coefficient. First, the interference effect benchmark is acquired. This benchmark is typically a pre-set standard value that reflects the ideal interference effect, taking into account various factors such as the type of drone, flight status, and environmental conditions. For example, in a standard test scenario, for a certain model of consumer drone, the interference effect benchmark might be set as follows: in an open area with no obstructions, the interference signal reduces the drone's signal strength by 80%, the data transmission interruption frequency is 10 times per minute, the bit error rate is 5%, and the navigation deviation rate is 20 meters. Then, the interference effect benchmark is weighted using the previously calculated first interference effect coefficient as the evaluation weight. The first interference effect coefficient is obtained by weighting the normalized first interference effect parameters and reflects the degree of deviation between the actual interference effect and the ideal interference effect. In a specific example, if the first interference effect coefficient is 0.85 and the interference effect benchmark is 100 points, then the target interference effect is 100 × 0.85 = 85 points. This score directly reflects the gap between the actual interference effect and the ideal effect, providing operators with a clear reference. In summary, through weighted calculation of the interference effect benchmark, the precise quantification and scientific evaluation of the UAV interference effect have been successfully achieved.

[0075] Furthermore, the interference assessment module is also used for:

[0076] Determine whether the target interference effect meets the predetermined interference constraint;

[0077] If the predetermined interference constraint is not met, the target interference signal is adjusted.

[0078] Specifically, the system determines whether the target interference effect meets a predetermined interference constraint; if not, it adjusts the target interference signal. First, the target interference effect is obtained by weighting a benchmark interference effect using a first interference effect coefficient as the weight. Then, this target interference effect is compared with the predetermined interference constraint. The predetermined interference constraint is a standard set according to actual countermeasure requirements; for example, a minimum interference score of 80 out of 100 is required for it to be considered effective. If the target interference effect does not meet this predetermined constraint, the system automatically initiates the interference signal adjustment process. In a specific example, if the target interference effect is 75 points, below the predetermined interference constraint of 80 points, the system determines that the current interference signal is insufficient to effectively counter the target drone. Next, the system adjusts the target interference signal. Adjustment methods may include changing parameters such as the interference signal's strength, frequency, and modulation method, or switching to a more suitable interference signal template. For example, the system might increase the strength of the jamming signal from -30dBm to -25dBm to enhance the jamming effect; or change the frequency of the jamming signal from 2.4GHz to 5.8GHz to match the communication characteristics of the target UAV in different frequency bands. Furthermore, the system may dynamically adjust the parameters of the jamming signal based on real-time feedback from the target UAV. For instance, if the system detects that the UAV's communication system has developed adaptability to jamming on a certain frequency band, it will promptly switch to another frequency band to continue jamming, ensuring the effectiveness of the jamming measures. In summary, through real-time judgment of the target jamming effect and dynamic adjustment of the jamming signal, precise control of the UAV jamming countermeasure process has been successfully achieved.

[0079] Furthermore, the countermeasure analysis module is also used for:

[0080] The expression for the anti-interference evaluation function is:

[0081] ;

[0082] It is the target countermeasure index, This refers to the target interference effect. It is the first interference effect parameter. Parameters The first interference effect parameters have a total of One parameter, and It is an integer greater than or equal to 4. The first one is the one mentioned Parameters The weighting coefficients.

[0083] Specifically, the expression for the anti-interference evaluation function is: ; It is the target countermeasure index, This refers to the target interference effect. It is the first interference effect parameter. Parameters The first interference effect parameters have a total of One parameter, and It is an integer greater than or equal to 4, meaning it must include at least the parameters corresponding to the signal strength degradation rate, data transmission interruption frequency, bit error rate, and navigation deviation rate. The first one is the one mentioned Parameters The weighting coefficients.

[0084] In summary, the UAV counter-jamming device provided in this application has the following technical effects:

[0085] The system employs a monitoring and locking module to capture and lock onto the target drone using monitoring equipment; a signal analysis module to acquire the target signal characteristics of the drone and match these characteristics against an interference database to obtain the target interference signal; an interference transmission module to activate the transmission device and transmit the target interference signal to the target drone, while simultaneously monitoring and recording the interference in real time; an interference evaluation module to evaluate and analyze the interference records to determine the interference effect; a countermeasure analysis module to acquire a countermeasure evaluation function and perform countermeasure analysis on the interference effect based on the function to obtain a target countermeasure index; and a countermeasure quantification module to quantify the countermeasure capability of the anti-interference device mounted on the drone using the target countermeasure index. This system achieves precise positioning and identification of the target drone, selects and transmits appropriate interference signals based on its signal characteristics, monitors and scientifically evaluates the interference effect, adjusts the interference strategy accordingly, and ultimately quantifies the performance of the drone's anti-interference device using the countermeasure evaluation function.

[0086] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0087] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A drone counter-jamming device, applied in an airport airspace protection zone, characterized in that, The UAV counter-jamming device includes: A monitoring and locking module is used to capture and lock onto a target drone via monitoring equipment, wherein the target drone is an unauthorized drone in an airport airspace protection zone; The signal analysis module is used to acquire the target signal features of the target UAV and to match the target signal features in an interference database to obtain the target interference signal. An interference transmission module is used to activate a transmission device and transmit the target interference signal to the target UAV through the transmission device, and to monitor and obtain the target interference record in real time; An interference assessment module is used to evaluate and analyze the target interference records to obtain the target interference effect; The countermeasure analysis module is used to obtain the countermeasure interference evaluation function, and to perform countermeasure analysis on the target interference effect based on the countermeasure interference evaluation function to obtain the target countermeasure index; The countermeasure quantification module is used to quantify the countermeasure capability of the target countermeasure jamming device carried on the target UAV through the target countermeasure index. The signal analysis module is also used for: Extract the first interference signal from the interference database and obtain the first data group of the first interference signal; Based on predetermined communication indicators and predetermined navigation indicators, the first signal characteristics of the first interference signal are obtained by traversing and matching in the first data group. A similarity analysis is performed between the target signal features and the first signal features to obtain a first similarity. If the first similarity reaches a predetermined similarity threshold, then the first interference signal is used as the target interference signal; The countermeasure analysis module is also used for: The expression for the anti-interference evaluation function is: ； It is the target countermeasure index, This refers to the target interference effect. It is the first interference effect parameter. Parameters The first interference effect parameters have a total of One parameter, and It is an integer equal to 4. The first one is the one mentioned Parameters Weighting coefficients; The signal analysis module is also used for: Extract the first interference simulation record from the first data group; Read the predetermined interference effect index, and extract the first interference simulation record based on the predetermined interference effect index to obtain the first interference effect parameter; The first interference effect parameter after normalization is weighted and calculated to obtain the first interference effect coefficient; The first similarity is adjusted using the first interference effect coefficient as the adjustment weight; The predetermined interference effect indicators include signal strength degradation rate, data transmission interruption frequency, bit error rate, and navigation deviation rate; The interference evaluation module is further configured to: obtain an interference effect benchmark, and perform weighted calculation on the interference effect benchmark using the first interference effect coefficient as the interference effect evaluation weight to obtain the target interference effect; The interference assessment module is also used for: Determine whether the target interference effect meets the predetermined interference constraint; If the predetermined interference constraint is not met, the target interference signal is adjusted.

2. The UAV counter-jamming device as described in claim 1, characterized in that, The signal analysis module is also used for: Read the predefined communication indicators; Based on the predetermined communication indicators, feature collection is performed on the target UAV to obtain target communication signal features; Read the pre-defined navigation indicators; Based on the predetermined navigation indicators, feature collection is performed on the target UAV to obtain target navigation signal features; The target communication signal features and the target navigation signal features together constitute the target signal features.

3. The UAV counter-jamming device as described in claim 2, characterized in that, The predetermined communication indicators include frequency band, signal type, modulation method, coding method, and communication protocol.

4. The UAV counter-jamming device as described in claim 2, characterized in that, The predetermined navigation indicators include satellite navigation system, positioning method, and navigation mode.

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