Unmanned aerial vehicle interference method and device, electronic equipment and storage medium
By acquiring and identifying UAV airspace information and dynamically determining interference strategies, the problems of low accuracy and resource waste in existing UAV interference technologies are solved, achieving efficient and accurate UAV interference effects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-03
AI Technical Summary
Existing drone jamming technologies suffer from low jamming accuracy, significant resource waste, and difficulty in dealing with unknown drone models or those using frequency hopping technology, making them ineffective in complex scenarios.
By acquiring detection information of the target airspace, identifying the information granularity, and dynamically determining the interference strategy under the feedback interference mode, including identifying the UAV model, communication frequency band or sub-channel, the interference strategy is adaptively selected, the target interference signal is constructed and applied to the target airspace.
It achieves high-precision UAV jamming in complex scenarios, improves jamming effectiveness, avoids impacting surrounding normal wireless equipment, and enhances resource utilization efficiency and system adaptability.
Smart Images
Figure CN121792001A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of drone countermeasures technology, and in particular to a drone jamming method, device, electronic device, and storage medium. Background Technology
[0002] With the widespread application of drone technology, the security risks it brings are becoming increasingly prominent, especially in sensitive areas such as airports and military-controlled zones, where unauthorized and reckless drone flights pose a serious threat to public safety. Currently, one of the common technical means to deal with drone threats is radio jamming, which interferes with the drone's communication links (such as flight control and image transmission) to force it to lose control, return to base, or land.
[0003] However, the above-mentioned solutions still have many shortcomings. While common full-band jamming schemes offer wide coverage, their jamming accuracy is low, easily causing collateral damage to nearby normal wireless equipment and resulting in significant resource waste. Furthermore, some fixed-frequency or targeted jamming schemes, although effective, require prior knowledge of the target drone's exact communication frequency, making them ineffective against unknown models or drones employing frequency hopping technology. Summary of the Invention
[0004] One objective of this application is to provide a drone jamming method, apparatus, electronic device, and storage medium to address the problem of poor effectiveness of current drone jamming technologies.
[0005] In a first aspect, embodiments of this application provide a method for jamming unmanned aerial vehicles (UAVs), comprising: Acquire detection information of the target airspace and determine the interference mode corresponding to the target airspace; By identifying the information granularity of the detected information, and determining the target interference strategy when the interference mode is feedback interference mode, the target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. Based on the aforementioned signal interference parameters, a target interference signal is constructed; The target interference signal is applied to the target airspace.
[0006] In conjunction with the first aspect, in one possible implementation, the step of identifying the information granularity of the detected information and determining the target interference strategy when the interference mode is a feedback interference mode includes: The information granularity of the detected information is identified; When the information granularity matches a preset target device category and the interference mode is a feedback interference mode, a preset interference strategy that matches the target device category is selected as the target interference strategy.
[0007] In conjunction with the first aspect, in one possible implementation, selecting a preset interference strategy that matches the target device category as the target interference strategy includes: Acquire a drone feature library, which includes various target device categories of drones and corresponding preset interference strategies for each target device category; When the information granularity successfully matches any target device category in the UAV feature library, a preset interference strategy corresponding to the successfully matched target device category is determined as the target interference strategy.
[0008] In conjunction with the first aspect, in one possible implementation, the predetermined interference strategy corresponding to the successfully matched target device category is used as the target interference strategy, including: Search the drone feature database for all preset interference strategies corresponding to the successfully matched device categories. If the device category matches a preset interference strategy, then the matched preset interference strategy will be used as the target interference strategy. If the device category matches multiple preset interference strategies, the signal interference parameters of the matched preset interference strategies are combined to obtain a comprehensive interference strategy, and the comprehensive interference strategy is used as the target interference strategy.
[0009] In conjunction with the first aspect, in one possible implementation, the method further includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication frequency band currently occupied by the UAV, a frequency band focusing jamming strategy is determined to target the currently occupied communication frequency band. The frequency band focusing jamming strategy is used to indicate suppressive jamming of the communication frequency band currently occupied by the UAV.
[0010] In conjunction with the first aspect, in one possible implementation, the method further includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication sub-channel currently occupied by the UAV, a channel tracking jamming strategy targeting the communication sub-channel is determined, and the channel tracking jamming strategy is determined as the target jamming strategy. The channel tracking jamming strategy includes jamming parameters for locking the communication sub-channel, and a jamming frequency dynamically adjusted according to changes in the communication sub-channel.
[0011] In a second aspect, embodiments of this application also provide a drone jamming device, comprising: The data acquisition module is used to acquire detection information of the target airspace and determine the interference mode corresponding to the target airspace; The information identification module is used to identify the information granularity of the detected information and determine the target interference strategy when the interference mode is feedback interference mode. The target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. A signal construction module is used to construct a target interference signal based on the signal interference parameters; The interference execution module is used to apply the target interference signal to the target airspace.
[0012] In a third aspect, embodiments of this application also provide an electronic device, including a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, the processor, when executing the one or more computer programs, causing the electronic device to implement the drone jamming method as described in the first aspect.
[0013] In a fourth aspect, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the UAV jamming method as described in the first aspect.
[0014] The embodiments of this application can achieve the following technical effects: This application's embodiments achieve feedback-based intelligent jamming by acquiring detection information of the target airspace and dynamically determining different target jamming strategies based on the information granularity of the detection information. Based on the linkage mechanism between detection information and jamming signals, the appropriate jamming strategy is adaptively selected according to different levels of information such as the UAV model, communication frequency band, or sub-channel, improving jamming accuracy. This effectively addresses complex scenarios such as rapid frequency hopping and multiple targets. Furthermore, by focusing on jamming resources, unnecessary impacts on surrounding normal wireless equipment are avoided, significantly improving the UAV jamming effect. Attached Figure Description
[0015] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 A schematic diagram of a drone jamming system provided in an embodiment of this application; Figure 2 A flowchart illustrating a drone jamming method provided in an embodiment of this application; Figure 3A schematic diagram of the frame of a drone jamming device provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.
[0018] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the system diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the system or the order in the flowchart. Moreover, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.
[0019] While some intelligent jamming systems exist in this field, capable of sensing UAV signals through detection devices, the coordination between jamming and detection devices remains insufficient, resulting in delayed jamming timing and slow response. Furthermore, their jamming strategies are simplistic, typically supporting only fixed jamming modes. They cannot flexibly adjust jamming parameters based on the specific UAV model and communication characteristics, nor can they distinguish between known and unknown targets and implement differentiated measures. Therefore, when facing complex scenarios involving multiple targets, multiple frequency bands, and rapid frequency hopping, their strike accuracy and countermeasure efficiency are both inadequate.
[0020] Therefore, in order to address the above shortcomings, please refer to... Figure 1 , Figure 1 This is a schematic diagram of a drone jamming system provided in an embodiment of this application.
[0021] like Figure 1 As shown, the detection device 10 is used to conduct radio detection of the airspace, identify UAV signals in the airspace, obtain detection information such as basic information of the UAV (such as manufacturer and model), communication frequency band (such as flight control and image transmission frequency band), current communication sub-channel, etc., and upload the information to the jamming device or control module in real time or near real time. The strategy management module 20 has a built-in UAV jamming strategy library. This UAV jamming strategy library, along with the detection information acquired by the detection device 10, is transmitted to the control module 30. The control module 30 selects the corresponding intelligent jamming mode (precise / frequency targeting / frequency tracking) and corresponding jamming parameters accordingly. At the same time, the control module 30 also supports user-specified jamming strategies.
[0022] According to the control command, the jamming device 40 generates and transmits jamming signals of different types and waveforms. After the jamming signals are transmitted to the target airspace, they interfere with each UAV in the airspace. The jamming signals can be full-band jamming, directional jamming or sub-channel level precision jamming.
[0023] Based on the above Figure 1 The drone jamming system shown is for reference only. Figure 2 This application provides a method for interfering with unmanned aerial vehicles (UAVs), which includes steps S10-S40: Step S10: Obtain the detection information of the target airspace and determine the interference mode corresponding to the target airspace; by Figure 1 Taking the system shown as an example, the detection device 10 continuously scans the target airspace across the entire frequency band or a specified frequency band (e.g., 400MHz-6GHz). When the detected signal energy exceeds a preset threshold, signal recording and acquisition are triggered.
[0024] In one preferred implementation, the acquired radio signals are sent to a digital signal processor for demodulation and analysis. By executing modulation identification algorithms (such as methods based on cyclostationary features), low-level features such as modulation scheme, symbol rate, and frame structure can be extracted. Simultaneously, the detection device 10 attempts to identify the source of transmission by comparing its signals with a pre-set radio frequency fingerprint database (such as the unique signal characteristics of various drone remote controllers and image transmission modules).
[0025] The above analysis results are formatted as structured data, which serves as the detection information in this embodiment. This detection information includes at least: Signal center frequency, bandwidth, pulse width, and period.
[0026] After receiving the detection information, the control module 30 performs mode selection to determine the appropriate interference mode for the target airspace.
[0027] As a preferred implementation, the mode selection can be based on the deterministic level of the detection information. For example, if the detection information contains a specific UAV model that has been successfully identified through feature matching, or if its communication protocol and real-time channel can be uniquely determined, then the control module determines that the activation conditions of the feedback interference mode are met.
[0028] Step S20: By identifying the information granularity of the detected information, and when the interference mode is feedback interference mode, the target interference strategy is determined. The target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. In this embodiment, the control module 30 parses the detected information and quantifies its information granularity into predefined levels. For example: Level L1 (coarse-grained): Only the presence of unknown radio frequency signals is confirmed; Level 2 (medium granularity): Identifies signals belonging to consumer-grade drone communication frequency bands (such as 2.4GHz, ISM band). Level 3 (Fine-grained): Identifies drone brand and series; Level 4 (Fine-grained): Identifies the specific model of the drone (e.g., "DJI Mavic 3") and its real-time operating frequency (e.g., 2.442GHz).
[0029] Simultaneously, the control module 30 determines the current interference mode, and only when the interference mode is a feedback interference mode, the control module 30 queries the policy management module 20 based on the granularity level (e.g., L4 level) and specific content (model, frequency point) of the detected information. The interference policy library of the policy management module 20 stores optimized interference parameter sets indexed by device model and communication mode.
[0030] For example, for "DJI Mavic 3's 2.4GHz image transmission mode", the corresponding strategy items may include: optimal interference waveform (a specific modulated noise), aiming frequency offset, recommended interference bandwidth (40MHz) and power control parameters.
[0031] Finally, the control module 30 combines the retrieved preset strategy entries with real-time parameters in the detection information (such as the precise current frequency point) to comprehensively calculate and ultimately determine the target interference strategy. This strategy is at least a set of instructions that includes all necessary signal interference parameters such as frequency, power, modulation, waveform, and timing.
[0032] In this embodiment, the interference feedback mode refers to a mode in which the interference strategy is adjusted in real time using information granularity as feedback information. In addition, when the interference mode is any other possible interference mode (such as user configuration, device pre-storage, historical recall, etc.), if the interference mode does not need to be combined with the identification of information granularity, then it is not necessary to combine information granularity to construct the target interference strategy.
[0033] Step S30: Construct the target interference signal based on the signal interference parameters; In this embodiment, the control module 30 sends the target jamming strategy to the digital control core of the jamming device 40 through necessary communication interfaces (such as Ethernet or a dedicated bus). The firmware of the jamming device 40 parses these parameters and configures them into the corresponding hardware units.
[0034] Based on this, the digital signal processor of the jamming device 40 calls its corresponding waveform generation function according to the waveform parameters in the strategy. For example, if the strategy is specified as targeting noise jamming, a pseudo-random sequence with a bandwidth consistent with the strategy requirements and a specific probability distribution (such as Gaussian distribution) is generated as the baseband jamming signal.
[0035] The baseband signal is converted into an analog signal by a digital-to-analog converter. This analog signal is then fed into the radio frequency link and mixed with the local oscillator signal in a mixer to shift the spectrum to the precise center frequency specified by the strategy (e.g., 2.442 GHz). Subsequently, the signal is amplified by an adjustable gain amplifier, with the output power strictly controlled by the power parameters in the strategy, ultimately forming a target interference signal that can propagate in space.
[0036] Step S40: Apply the target interference signal to the target airspace.
[0037] Specifically, the power amplifier in the final stage of the jamming device 40 feeds the radio frequency signal to the transmitting antenna.
[0038] Depending on the system design, the transmitting antenna can be an omnidirectional antenna to achieve area coverage, or a directional antenna (such as a parabolic antenna) to concentrate energy toward the location of the UAV, thereby radiating the target interference signal into the target airspace in the form of electromagnetic waves.
[0039] When a target jamming signal enters the passband of a drone's communication receiver, its parameters (frequency, modulation characteristics) are specifically designed to effectively increase the receiver's noise floor or cause the demodulator to lose lock. For example, in the drone's remote control link, the target jamming signal will cause control command packet loss or delay, triggering the drone to enter a fail-safe state (such as hovering, returning to home, or landing); while in the image transmission link, the target jamming signal will cause video transmission interruption.
[0040] Thus, by acquiring detection information of the target airspace and dynamically determining different target jamming strategies based on the information granularity of the detection information, feedback-based intelligent jamming is achieved. This embodiment establishes a linkage mechanism between detection and jamming, adaptively selecting different jamming strategies based on different levels of information such as UAV model, communication frequency band, or sub-channel, thereby achieving multi-level precise countermeasures from broad-spectrum suppression to channel-level strikes.
[0041] This embodiment not only significantly improves the accuracy and response speed of jamming, effectively dealing with complex scenarios such as rapid frequency hopping and multiple targets, but also avoids unnecessary impact on surrounding normal wireless equipment by focusing jamming resources, thereby improving resource utilization efficiency and enhancing the adaptability and effectiveness of the entire UAV countermeasure system.
[0042] In some embodiments, the interference mode further includes a feedforward interference mode, and the method further includes: When the interference mode is feedforward interference mode, a user configuration instruction or a preset default configuration instruction is obtained; a target interference strategy is determined according to the user configuration instruction or default configuration instruction, wherein the target interference strategy is used to indicate the frequency range, interference type and modulation waveform of the interference signal; a target interference signal is constructed according to the target interference strategy; and the target interference signal is applied to the target airspace to interfere with each UAV in the target airspace.
[0043] The control module 30 determines whether to activate the feedforward interference mode based on preset conditions (such as manual selection by the user or failure of the detection device to identify a valid target). In this mode, the control module 30 receives user configuration instructions issued by the operator through its human-machine interface; if no user instructions are received, it automatically retrieves the default configuration instructions preset for general scenarios from the control module 30.
[0044] Specifically, user configuration instructions or default configuration instructions directly specify the interference requirements.
[0045] For example, a user command might be: to implement jamming interference in the 5.8 GHz band; The control module 30 parses the instruction and converts it into a specific target interference strategy. The strategy clearly defines the frequency range of the interference signal (e.g., 5.725-5.850 GHz), the type of interference (e.g., broadband jamming interference), and the modulation waveform (e.g., noise FM waveform).
[0046] As a preferred implementation, the control module 30 provides default parameter support in this process, such as mapping "blocking interference" to specific bandwidth and waveform parameters.
[0047] As a preferred implementation, the interference process in this embodiment can be manually started / stopped by the user, or the interference can be triggered after the detection device detects the target.
[0048] The control module 30 sends the above strategy to the jamming device 40. The jamming device 40 generates a broadband noise jamming signal covering the specified frequency band according to the strategy, and radiates it to the target airspace through the antenna, indiscriminately suppressing all UAVs using the same frequency band in that airspace.
[0049] Furthermore, in this embodiment, determining a target interference strategy suitable for the target area by identifying the information granularity of the detected information includes: Identify the information granularity of the detected information; when the information granularity matches a preset target device category, select a preset interference strategy that matches the target device category as the target interference strategy.
[0050] Specifically, in the feedback interference mode, the strategy management module 20 analyzes the detection information reported by the detection device 10 and identifies its information granularity. For example, it determines the detection information as: "Signal feature matching successful, identified as 'DJI Matrice 300 RTK' drone."
[0051] The policy management module 20 uses the identified target device category (i.e., "DJI Matrice 300 RTK") as a keyword to query the radio frequency fingerprint database and retrieve all preset interference policies bound to that device category. If a dedicated policy entry for that model exists in the database, it is passed to the control module 30, which then selects the successfully matched preset policy as the target interference policy for this execution.
[0052] Furthermore, in this embodiment, selecting a preset interference strategy that matches the device category as the target interference strategy includes: A drone feature library is acquired, which includes target device categories of various drones and preset interference strategies corresponding to each target device category. When the information granularity successfully matches any target device category in the drone feature library, the preset interference strategy corresponding to the successfully matched target device category is determined as the target interference strategy.
[0053] Based on this embodiment, the policy management module 20 maintains at least one UAV feature library. This library is essentially a relational database or feature-policy mapping table, where each record contains at least two types of key fields: The first is the target device category defined by the characteristics of UAV signals (such as specific bandwidth, pulse width, and period); the second is the preset interference strategy corresponding to the category (including frequency, waveform, timing suggestions, etc.).
[0054] The strategy management module 20 performs similarity calculations or exact matching between the input features and the records in the feature library. When the matching degree exceeds the set threshold, it is considered a successful match.
[0055] Subsequently, the strategy management module 20 transmits the preset interference strategy associated with the successfully matched record to the control module 30, and the control module 30 adopts this strategy as the target interference strategy.
[0056] Furthermore, in this embodiment, the preset interference strategy corresponding to the successfully matched target device category is used as the target interference strategy, including: The system queries the UAV feature database for all preset interference strategies corresponding to the successfully matched device category. If the device category matches one preset interference strategy, the matched preset interference strategy is used as the target interference strategy. If the device category matches multiple preset interference strategies, the system performs a union of the signal interference parameters of the multiple matched preset interference strategies to obtain a comprehensive interference strategy, and uses the comprehensive interference strategy as the target interference strategy.
[0057] In this embodiment, after the interference strategy matching is successful, if the result transmitted by the strategy management module 20 shows that the device category has multiple preset interference strategies (for example, different interference strategies for its remote control link, image transmission link, and GPS navigation link respectively), then the control module 30 will perform strategy fusion, that is, perform a union operation on the signal interference parameters of multiple strategies.
[0058] Specifically, the forms of union operations include, but are not limited to: The frequency range union is used to calculate the total coverage area of the frequency range across all strategies. The power is set to the maximum value, based on the highest recommended transmit power among all strategies; The waveform and modulation integration may employ a composite waveform that can cover multiple interference requirements, or time-division multiplexing different waveforms.
[0059] By combining the above parameters, a new comprehensive jamming strategy is finally generated. This strategy aims to attack multiple potential communication links of the target UAV simultaneously, thereby improving the reliability and robustness of the jamming. The control module 30 ultimately determines this comprehensive strategy as the target jamming strategy for this execution.
[0060] Furthermore, the method in this embodiment also includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication frequency band currently occupied by the UAV, a frequency band focusing jamming strategy is determined to target the currently occupied communication frequency band. The frequency band focusing jamming strategy is used to indicate suppressive jamming of the communication frequency band currently occupied by the UAV.
[0061] Specifically, in the feedback interference mode, if the control module 30 determines that the information granularity of the detection information does not match any device category in the UAV feature library (i.e., the specific model cannot be identified), but the detection information provided by the detection device 10 contains reliable measurement results of the communication frequency band currently occupied by the UAV (e.g., it is clearly measured that its strong signal is concentrated in the 1.570-1.580 GHz frequency band).
[0062] At this point, control module 30 activates the frequency band focusing interference strategy. This strategy abandons interference targeting the device model and instead focuses on effectively suppressing the exact frequency band that has been detected. Therefore, the strategy parameters will be set as follows: the interference center frequency is the center of the measured frequency band, the interference bandwidth is slightly wider than the measured frequency band, and high-power continuous wave or noise modulation is used for suppressive interference.
[0063] According to this strategy, jamming device 40 concentrates its energy to transmit within the specific frequency band in order to quickly cut off the communication of the drone in this frequency band.
[0064] Furthermore, the method in this embodiment also includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication sub-channel currently occupied by the UAV, a channel tracking jamming strategy targeting the communication sub-channel is determined. The channel tracking jamming strategy includes jamming parameters for locking the sub-channel and jamming frequency dynamically adjusted according to changes in the sub-channel.
[0065] In the feedback interference mode, if the policy management module 20 determines that the detection information does not match the specific device category, but the detection information provided by the detection device 10 contains the accurate information of the communication sub-channel currently occupied by the drone, and the detection device 10 can continuously track the changes of the sub-channel (for example, identifying that the target is using the Wi-Fi protocol and is hopping between channels 36, 40, and 44).
[0066] At this point, the policy management module 20 activates the channel tracking interference policy, which includes at least the following: The interference parameters (such as frequency and modulation settings accurate to the sub-channel width) are used to lock the current sub-channel; and a dynamic adjustment mechanism for the interference frequency is established, which creates a real-time control loop from the detection device 10 to the control module 30 and then to the interference device 40.
[0067] Specifically, the jamming device 40 first jams the current sub-channel according to a strategy. Simultaneously, the detection device 10 continuously monitors the target channel. Once a change in the target's communication sub-channel is detected, the detection device 10 immediately reports the new channel information to the control module 30. The control module 30 then generates updated jamming parameters and sends them to the jamming device 40 to adjust its jamming frequency and relock onto the new sub-channel, achieving continuous and precise jamming.
[0068] Furthermore, in other embodiments, the detection device 10 can simultaneously capture multiple different drone signals when detecting target airspace. Through parallel signal processing and feature recognition channels, the detection device 10 separates and identifies multiple independent detection information units. For example, it can simultaneously identify "Target A: DJI Mavic 3, using 2.4GHz image transmission" and "Target B: Unknown model homemade drone, using 915MHz frequency hopping remote control link".
[0069] Based on this, the strategy management module 20 receives and processes the multi-target detection information mentioned above, and determines the most suitable interference mode and strategy for each target in parallel according to the threat level of each target (which can be determined based on preset rules such as model, heading, speed, etc.) and the different information granularity.
[0070] For example, for target A that has been accurately identified, the feedback interference mode in the above embodiments is used to call its model-specific fine interference strategy; while for target B whose frequency band characteristics are only identified, the frequency band focusing interference strategy in the above embodiments is used.
[0071] Under the control of the control module 30, the jamming device 40 uses any of the following schemes to cause interference: On the one hand, if the jamming device has a single transmission channel, the control module (30) will generate a time-division multiplexed integrated jamming timing sequence. For example, within a millisecond-level time slice, a 2.4 GHz precision jamming signal is transmitted against target A; while in the next time slice, it quickly switches to the 915 MHz band and transmits a broadband suppression signal against target B, that is, synchronous jamming against the two targets is achieved through high-speed switching.
[0072] On the other hand, if the jamming device is equipped with a multi-channel active phased array antenna, it can generate two independent beams simultaneously through digital beamforming technology. One beam points towards target A and transmits a 2.4 GHz precision jamming signal, while the other beam points towards target B and transmits a 915 MHz suppression signal.
[0073] In other embodiments, while or after the jamming device 40 transmits a target jamming signal to act on the target airspace, the detection device 10 continuously monitors the status of the target UAV and collects evaluation information for assessing the jamming effect, such as whether the target UAV signal disappears, whether the signal strength is significantly weakened, whether the communication protocol is abnormal (such as a surge in retransmission rate), and the UAV's behavioral response (such as whether it starts returning to home, hovers, or loses control).
[0074] The control module 30 compares the evaluation information with the expected interference effect. If the comparison result shows that the interference effect is not as expected (for example, the target UAV signal is still stable), the signal interference parameters are adaptively adjusted based on the original target interference strategy.
[0075] For example, if the preset targeting frequency jamming effect is not good for a certain model of drone, you can try to widen the jamming bandwidth from 20MHz to 40MHz, or switch to another modulation waveform (such as switching from continuous wave jamming to sweep frequency jamming).
[0076] If fine-tuning the parameters is ineffective, the control module 30 may determine that the current strategy is not applicable to the actual target and then activate a backup strategy. For example, switching from "quasi-targeting jamming mode" to "channel tracking jamming mode" or "wider band focusing jamming mode".
[0077] Meanwhile, the strategy management module 20 can associate the detection information, interference strategy and evaluation information during this interference process and store them as experience data in the feature library or strategy library. When encountering signals with the same characteristics in the future, the strategy that has been verified to be effective can be tried first.
[0078] Based on this embodiment, not only can actions be taken based on initial detection information, but strategies can also be iterated based on the jamming effect, thereby effectively addressing the challenges brought about by UAV firmware upgrades, the emergence of new models, or complex electromagnetic countermeasures environments, and significantly improving the reliability and intelligence of jamming.
[0079] Please refer to Figure 3 This application also proposes a drone jamming device, comprising: The data acquisition module 210 is used to acquire detection information of the target airspace and determine the interference mode corresponding to the target airspace; Information recognition module 220 is used to identify the information granularity of the detected information and determine the target interference strategy when the interference mode is feedback interference mode. The target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. The signal construction module 230 is used to construct a target interference signal based on the signal interference parameters; The interference execution module 240 is used to apply the target interference signal to the target airspace.
[0080] As a feasible implementation, the information identification module 220, when determining a target interference strategy suitable for the target area by identifying the information granularity of the detected information, is specifically used for: Identify the information granularity of the detected information; when the information granularity matches a preset target device category, select a preset interference strategy that matches the target device category as the target interference strategy.
[0081] As a feasible implementation, the information identification module 220, when selecting a preset interference strategy that matches the target device category as the target interference strategy, is specifically used for: A drone feature library is acquired, which includes target device categories of various drones and preset interference strategies corresponding to each target device category. When the information granularity successfully matches any target device category in the drone feature library, the preset interference strategy corresponding to the successfully matched target device category is determined as the target interference strategy.
[0082] As a feasible implementation, the information identification module 220, when determining the preset interference strategy corresponding to the successfully matched target device category as the target interference strategy, is specifically used for: The system queries the UAV feature database for all preset interference strategies corresponding to the successfully matched device category. If the device category matches one preset interference strategy, the matched preset interference strategy is used as the target interference strategy. If the device category matches multiple preset interference strategies, the system performs a union of the signal interference parameters of the multiple matched preset interference strategies to obtain a comprehensive interference strategy, and uses the comprehensive interference strategy as the target interference strategy.
[0083] As one possible implementation, the information recognition module 220 is also used for: When the information granularity does not match the device category of the UAV, and the detection information includes the communication frequency band currently occupied by the UAV, a frequency band focusing jamming strategy is determined to target the currently occupied communication frequency band. The frequency band focusing jamming strategy is used to indicate suppressive jamming of the communication frequency band currently occupied by the UAV.
[0084] As one possible implementation, the information recognition module 220 is also used for: When the information granularity does not match the device category of the UAV, and the detection information includes the communication sub-channel currently occupied by the UAV, a channel tracking jamming strategy targeting the communication sub-channel is determined. The channel tracking jamming strategy includes jamming parameters for locking the sub-channel and jamming frequency dynamically adjusted according to changes in the sub-channel.
[0085] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the device described above can be found in the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0086] Furthermore, see Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. This electronic device can serve as the detection device 10, policy management module 20, control module 30, and interference device 40 in the above embodiments. The electronic device 60 includes one or more processors 61 and a memory 62. The memory 62 is connected to one or more processors 61, for example, via a bus.
[0087] Processor 61 is configured to support the electronic device in performing the corresponding functions in the methods described in the above method embodiments. Processor 61 may be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.
[0088] Memory 62 is used to store program code, etc. Memory 62 may include volatile memory (VM), such as random access memory (RAM); memory 62 may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory 62 may also include combinations of the above types of memory.
[0089] The memory 62 can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the UAV jamming method in the embodiments of this application. The processor 61 executes various functional applications and data processing of the UAV jamming method by running the non-volatile software programs, instructions, and modules stored in the memory 62, that is, it realizes the functions of each module or unit of the UAV jamming method provided in the above method embodiments.
[0090] The memory 62 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function. The data storage area may store data created based on the use of the UAV jamming method, etc. In some embodiments, the memory 62 may optionally include memory remotely located relative to the processor 61, which can be connected to the processor 61 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0091] One or more modules are stored in memory 62. When executed by one or more processors 61, they perform the UAV interference method in any of the above method embodiments. For example, they perform the method steps described in the above method embodiments to realize the functions of the modules described in the above system embodiments.
[0092] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to perform the drone jamming method as described in the foregoing embodiments.
[0093] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.
[0094] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.
Claims
1. A method for jamming unmanned aerial vehicles (UAVs), characterized in that, The method includes: Acquire detection information of the target airspace and determine the interference mode corresponding to the target airspace; By identifying the information granularity of the detected information, and determining the target interference strategy when the interference mode is feedback interference mode, the target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. Based on the aforementioned signal interference parameters, a target interference signal is constructed; The target interference signal is applied to the target airspace.
2. The UAV jamming method according to claim 1, characterized in that, The step of identifying the information granularity of the detected information and determining the target interference strategy when the interference mode is a feedback interference mode includes: The information granularity of the detected information is identified; When the information granularity matches a preset target device category and the interference mode is a feedback interference mode, a preset interference strategy that matches the target device category is selected as the target interference strategy.
3. The UAV jamming method according to claim 2, characterized in that, The step of selecting a preset interference strategy that matches the target device category as the target interference strategy includes: Acquire a drone feature library, which includes various target device categories of drones and corresponding preset interference strategies for each target device category; When the information granularity successfully matches any target device category in the UAV feature library, a preset interference strategy corresponding to the successfully matched target device category is determined as the target interference strategy.
4. The UAV jamming method according to claim 3, characterized in that, The preset interference strategy corresponding to the target device category that has been successfully identified and matched is used as the target interference strategy, including: Search the drone feature database for all preset interference strategies corresponding to the successfully matched device categories. If the device category matches a preset interference strategy, then the matched preset interference strategy will be used as the target interference strategy. If the device category matches multiple preset interference strategies, the signal interference parameters of the matched preset interference strategies are combined to obtain a comprehensive interference strategy, and the comprehensive interference strategy is used as the target interference strategy.
5. The UAV jamming method according to claim 4, characterized in that, The method further includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication frequency band currently occupied by the UAV, a frequency band focusing jamming strategy targeting the currently occupied communication frequency band is determined, and the frequency band focusing jamming strategy is used as the target jamming strategy. The frequency band focusing jamming strategy is used to indicate suppressive jamming of the communication frequency band currently occupied by the UAV.
6. The UAV jamming method according to claim 2, characterized in that, The method further includes: When the information granularity does not match the device category of the UAV, and the detection information includes the communication sub-channel currently occupied by the UAV, a channel tracking jamming strategy targeting the communication sub-channel is determined, and the channel tracking jamming strategy is determined as the target jamming strategy. The channel tracking jamming strategy includes jamming parameters for locking the communication sub-channel, and a jamming frequency dynamically adjusted according to changes in the communication sub-channel.
7. A drone jamming device, characterized in that, The device includes: The data acquisition module is used to acquire detection information of the target airspace and determine the interference mode corresponding to the target airspace; The information identification module is used to identify the information granularity of the detected information and determine the target interference strategy when the interference mode is the feedback interference mode. The target interference strategy is used to indicate the signal interference parameters for interfering with each UAV in the target airspace. A signal construction module is used to construct a target interference signal based on the signal interference parameters; The interference execution module is used to apply the target interference signal to the target airspace.
8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, the processor causing the electronic device to implement the drone jamming method as described in any one of claims 1-6 when executing the one or more computer programs.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the unmanned aerial vehicle jamming method as described in any one of claims 1-6.