A dynamically reconfigurable and upgradable active jamming device and method

Abstract

To address the limitations of existing active jamming systems in dynamically adjusting jamming strategies based on jamming effectiveness and electromagnetic environment perception, and their inability to adapt to the requirements of cognitive electronic warfare, this invention discloses a dynamically reconfigurable and upgradeable active jamming device and method. The device comprises a radio frequency (RF) layer, a waveform layer, a parameter layer, an evaluation and decision layer, and a computation layer. The RF layer and waveform layer are connected via RF cables and buses, while the waveform layer and parameter layer, the parameter layer and evaluation and decision layer, and the evaluation and decision layer and computation layer are all connected via buses. Each layer is responsible for handling only the tasks at its own level. This device possesses dynamic upgrade and reconfigurability capabilities, reducing system implementation costs. When facing new threat targets, this device can adjust the jamming scheme and jamming generation rules in real time based on changes in the threat target and the jamming effect, exhibiting dynamic iteration capabilities and ensuring the real-time nature and effectiveness of the jamming effect.

Description

Technical Field

[0001] This invention relates to the field of active radar jamming, and more particularly to an active jamming device and method that can be dynamically reconfigured and upgraded. Background Technology

[0002] In recent years, with the widespread application of microelectronics, digitalization, and intelligent technologies in radar, radar technology has developed rapidly, and technologies such as cognitive radar, digital array radar, software-defined radar, ultra-wideband radar, and SAR radar have emerged continuously. The new generation of radar sensing systems with cognitive capabilities will fully utilize their environmental perception capabilities, making transmission and reception a closed-loop system. This allows the system to adjust its operating mode, transmission parameters, and processing procedures in real time according to the surrounding environment (clutter, geographical environment, interference, etc.), greatly improving the performance of all aspects of the system.

[0003] Existing active jamming methods for radar mainly fall into two categories: suppression jamming and deception jamming. Current active jamming systems analyze detected radiation source signals to identify and locate the radiation source, determine its type and operating status, and then select an appropriate jamming mode based on a preset jamming strategy. This generates corresponding jamming waveforms and utilizes relevant radio frequency resources to interfere with the target radiation source. However, with the increasing intelligence and multi-functionality of radar systems, they will employ waveforms such as random phase-coded pulses, pulse Doppler, intra-pulse frequency modulation, alternating fixed and stepped frequencies, and mixtures of these waveforms. When facing complex radar signals from multiple systems, existing active jamming methods struggle to generate an effective jamming signal for reliable interference.

[0004] Specifically, traditional electronic jamming devices have pre-set jamming frequency bands and patterns, especially for suppression jamming, where the frequency bands and patterns are limited and must be set manually or through reconnaissance guidance. For deceptive or agile jamming, coherent gain jamming can be achieved by flexibly adjusting the received radar waveform, but the specific jamming pattern is also pre-set. Faced with complex and rapidly changing radar environments, traditional jamming devices cannot achieve optimal adaptive jamming that changes with the radar electromagnetic environment.

[0005] Cognitive electronic warfare technology, through closed-loop learning, enables systems to recognize their environment, giving adversaries the initiative in future electronic warfare. It represents a significant new electromagnetic spectrum countermeasure technology with immense development potential and broad application prospects. Cognitive electronic warfare offers an effective way to address the rapid development of radar systems and the increasing complexity of the electromagnetic environment, enabling rapid iterative upgrades to active jamming capabilities. However, current active jamming devices still employ superheterodyne or wide-open receiver structures designed for traditional active jamming methods, lacking a design tailored to cognitive electronic warfare. This makes existing structures ill-suited for the requirements of cognitive electronic warfare. Therefore, there is a need to develop a dynamically reconfigurable active jamming device that can rapidly upgrade and iterate alongside threat targets. Summary of the Invention

[0006] To address the problem that existing active jamming systems struggle to dynamically adjust jamming strategies based on jamming effectiveness and electromagnetic environment perception results, and are ill-suited to the requirements of cognitive electronic warfare, this invention discloses a dynamically reconfigurable and upgradeable active jamming device. The device comprises: a radio frequency (RF) layer, a waveform layer, a parameter layer, an evaluation and decision layer, and a computation layer. The RF layer and waveform layer are connected via RF cables and a bus. The waveform layer and parameter layer, the parameter layer and evaluation and decision layer, and the evaluation and decision layer and computation layer are all connected via a bus. Each layer is responsible for handling only the services of its own level.

[0007] The radio frequency (RF) layer comprises antenna modules and digital array modules. Antenna modules receive RF signals output from the digital array modules and transmit them into free space. Digital array modules include several T / R components of the same or different categories. T / R components of the same category use the same dimensions and electrical interfaces. Digital array modules perform low-noise amplification, filtering, down-conversion, and analog-to-digital conversion on the RF signals input from the antenna modules, and output the digital signal obtained after analog-to-digital conversion to the digital beamforming module. They also receive signals output from the digital beamforming module, perform digital-to-analog conversion, up-conversion, filtering, and power amplification on them, and then output the amplified signal to the antenna modules. All digital array modules use a uniform dimension and electrical interface.

[0008] The waveform layer includes a digital beamforming module, classic interference sources, and upgraded interference sources. The digital beamforming module receives the output signal from the digital array module, constructs a received signal vector using the received signal, performs a receive beamforming operation on the received signal vector to obtain an output signal, and sends this output signal to the radiation source parameter measurement module; the receive beamforming operation includes amplitude and phase weighting. The number of interfaces between the digital beamforming module in the waveform layer and the digital array module in the radio frequency layer is greater than the number of digital array modules actually installed in the system.

[0009] Classic jamming sources are used to generate classic jamming waveforms with proven jamming effects. Upgraded jamming sources are used to generate new types of jamming waveforms for new threat targets.

[0010] The classic interference source generates an interference waveform based on the interference parameter information output by the interference parameter generation module. The classic interference source includes an interference signal transmitter and a modulator. It compares the interference parameter information output by the interference parameter generation module with the interference parameter information in its interference mode mapping table. If the interference parameter information output by the interference parameter generation module contains interference parameter information not defined in the interference mode mapping table, this undefined interference parameter information is sent to the upgraded interference source. The upgraded interference source generates a basic interference waveform based on the received interference parameter information, modulates it, and sends it to the digital waveform forming module. If the interference parameter information output by the interference parameter generation module is already included in the interference mode mapping table, the classic interference source generates the interference waveform using its interference signal transmitter and modulator based on the corresponding interference parameter information in the interference mode mapping table.

[0011] The jamming signal generator includes a noise jamming source generator, a response jamming source generator, and a repeater jamming source generator. The noise jamming source generator and the response jamming source generator are implemented using digital frequency synthesis (DDS), while the repeater jamming source generator is implemented using digital radio frequency store-and-forward (DRFM). The jamming signal generator generates a basic jamming waveform based on the jamming signal parameter information in the jamming parameter information of the jamming mode mapping table. The modulator modulates the basic jamming waveform output by the jamming signal transmitter based on the jamming pattern information in the jamming parameter information of the jamming mode mapping table, obtaining the final jamming waveform, which is then output to the digital beamforming module. The digital beamforming module uses the received jamming waveform to form a waveform vector, performs transmit beamforming on the waveform vector, obtains an output signal, and sends the output signal to the digital array module. The transmit beamforming operation includes signal correction, amplitude, and phase weighting operations. The parameters for the transmit and receive beamforming operations of the waveform vector by the digital beamforming module are determined based on the target angle and motion parameter information obtained from the radiation source parameter measurement module.

[0012] The upgraded interference source generates a basic interference waveform using an arbitrary waveform transmitter and / or a radio frequency storage and transceiver as needed. A modulator is then used to modulate the basic interference waveform to obtain the interference waveform, which is output to the digital waveform forming module. The upgraded interference source utilizes parameters from the signal waveform in the time domain, frequency domain, code domain, spatial domain, Doppler domain, and transform domain to generate the basic interference waveform. The upgraded interference source can control more signal waveform parameters used to generate and modulate the basic interference waveform than it can control. The transform domain refers to the signal space domain composed of a complete set of orthogonal functions, including Walsh functions, elliptic spherical wave functions, wavelet functions, Legendre functions, etc. Once the interference effect of the basic interference waveform and its corresponding interference parameter information generated by the upgraded interference source is verified, the basic interference waveform and its corresponding interference parameter information are sent to the interference mode mapping table of the classic interference source for storage, thereby updating the interference mode mapping table.

[0013] The parameter layer includes a radiation source parameter measurement module, an interference parameter generation module, and a modulation dimension parameter update module.

[0014] The radiation source parameter measurement module processes the output signal received from the digital beamforming module to obtain the time-domain, frequency-domain, spatial-domain, and polarization-domain parameter information of the target signal, as well as the target motion parameter information. Based on the obtained target parameter information, it sorts and identifies the target, obtains the target identification result information, and sends the target parameter information to the target state and behavior recognition module. The target parameter information includes target signal parameter information, target motion parameter information, and target identification result information. The target signal parameter information includes the time-domain, frequency-domain, spatial-domain, and polarization-domain parameter information of the target signal.

[0015] The interference parameter generation module receives interference strategy information generated by the interference strategy generation module, determines whether the received interference strategy information is already included in the existing interference strategy information library of the interference parameter generation module, and if so, generates corresponding interference parameter information based on the interference strategy information and sends the generated interference parameter information to the classic interference source. If the received interference strategy information is not included in the existing interference strategy information library of the interference parameter generation module, it sends the received interference strategy information to the modulation dimension parameter update module. The interference strategy information library in the interference parameter generation module is updated in real time according to the update status of the interference rule library module. At the same time, relevant parameters of the interference waveform designed by the modulation dimension parameter update module, whose interference effect has been verified by actual testing, are added to its interference strategy information library to achieve real-time updating of the interference strategy information library.

[0016] The module that updates modulation dimension parameters designs an interference waveform based on the received interference strategy information, with the goal of optimizing the interference effect. It then obtains the relevant parameters of the interference waveform, uses these parameters as interference parameter information, and sends the interference parameter information to the classic interference source.

[0017] The module for updating modulation dimension parameters aims to optimize the interference effect and designs the interference waveform using an optimization method, such as reinforcement learning.

[0018] The evaluation decision layer includes a target status and behavior identification module, an interference strategy generation module, a dynamic threat database module, an interference rule database module, a real-time target threat and interference effect evaluation module, and a novel interference rule module.

[0019] The target status and behavior recognition module receives target parameter information from the radiation source parameter measurement module, classifies this information to obtain target status and behavior information, and then sends this information to the real-time comprehensive assessment module for target threat and interference effects and the dynamic threat database module. Target status information refers to the target's operational status, including search status, tracking status, identification status, calibration status, and data link status. Target behavior refers to changes in the target's status during operation due to internal operational needs or external electromagnetic environment influences.

[0020] The target state and behavior recognition module uses classification methods to obtain target state information and target behavior information. The classification methods include pattern classification methods and intelligent clustering methods.

[0021] The dynamic threat database module is used to store historical data of target status information, target behavior information, and target behavior feature information obtained by the target status and behavior recognition module. It also judges the target status information, target behavior information, and target behavior feature information received in real time. If the target status information, target behavior information, and target behavior feature information received in real time do not exist in the historical data, the target status information, target behavior information, and target behavior feature information received in real time are stored to complete the update of the dynamic threat database module.

[0022] The real-time comprehensive evaluation module for target threat and interference effect utilizes the received target status information and target behavior information to evaluate the target threat level and interference effect in real time, obtaining target threat level evaluation results and interference effect evaluation results respectively. Based on the target behavior information and interference effect evaluation results, target behavior feature information is obtained, and the obtained target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved. The real-time comprehensive evaluation module for target threat and interference effect evaluates the novelty of the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results with the historical data saved in its database. If the novelty is greater than a certain threshold, the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the novelty interference rule module, dynamic threat database module, and interference rule database module, and the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved as historical data in its database to update the database. Otherwise, the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the interference strategy generation module, dynamic threat database module, and interference rule database module.

[0023] The real-time comprehensive evaluation module for target threat and interference effect evaluates the target threat level and interference effect in real time, and obtains the target threat level evaluation result and interference effect evaluation result respectively. It is implemented using an artificial neural network.

[0024] The real-time comprehensive evaluation module for target threat and interference effect obtains target behavior feature information based on target behavior information and interference effect evaluation results, and uses classification methods or artificial neural networks to achieve this.

[0025] The interference strategy generation module is implemented using an artificial neural network. Based on the received target behavior feature information, target threat level assessment results, and interference effect assessment results, it uses machine learning methods to generate corresponding interference strategy information and sends the interference strategy information to the interference parameter generation module and the interference rule base module.

[0026] After updating the interference rule base module and the dynamic threat base module, the interference strategy generation module uses data from the interference rule base module, the dynamic threat base module, and the target threat and interference effect real-time comprehensive evaluation module as training data to train the artificial neural network module of the interference strategy generation module, thereby realizing the update of the interference strategy generation module.

[0027] The aforementioned interference rule base module is used to store interference strategies that have been effectively applied and to judge the interference strategies received in real time. If the interference strategy does not exist in the interference rule base module, then during the duration of subsequent active interference, the interference effect evaluation result of the interference strategy is judged based on the interference effect evaluation result received from the target threat and interference effect real-time comprehensive evaluation module. If the interference effect evaluation result is better than a certain threshold, then the interference strategy and the corresponding target behavior feature information, target threat level evaluation result and interference effect evaluation result are stored in the interference rule base module.

[0028] The new interference rule module determines the corresponding interference strategy generation rule based on the received target behavior feature information, target threat level assessment results, and interference effect assessment results. It then uses this interference strategy generation rule to generate corresponding interference strategy information and sends the interference strategy information to the interference parameter generation module and the interference rule library module.

[0029] The new interference rule module obtains interference strategy data from the interference rule base module based on the acquired target behavior feature information, target threat level assessment results, and interference effect assessment results. It uses the acquired data as a training dataset to reconstruct and train the artificial neural network model. The trained artificial neural network model is then used as the interference strategy generation rule. The received target behavior feature information, target threat level assessment results, and interference effect assessment results are input into the interference strategy generation rule to generate the corresponding interference strategy information.

[0030] The novel interference rule module is implemented using various methods, including probabilistic graphical models, knowledge graph models, and reinforcement learning models. This module possesses the ability to dynamically update the interference policy generation rules.

[0031] The computing layer includes a resource monitoring and allocation module and a computing resource module. The resource monitoring and allocation module receives computing requests from various modules in the evaluation and decision-making layer, and allocates and distributes corresponding computing tasks to the computing resource module according to the computing requests. After the computing resource module completes the computing tasks and obtains the computing results, it receives and integrates the corresponding computing results and sends them to the various modules in the evaluation and decision-making layer that made the computing requests. The resource monitoring and allocation module also monitors the status of all computing resources.

[0032] The second aspect of this invention discloses an active interference method that can be dynamically reconfigured and upgraded, which is implemented using a static module and a dynamic iterative upgrade module. The static module is a module that remains unchanged, while the dynamic iterative upgrade module is a module that is updated in real time as the target changes.

[0033] The static module analyzes the target signal to obtain target information. If the target information is not stored in the static module's database, it is stored in the static module's database and then passed to the dynamic iterative upgrade module for processing. The dynamic iterative upgrade module processes the received target information accordingly and generates an interference scheme corresponding to the target information. This interference scheme is then used to implement active interference. The static module evaluates the interference effect of the interference scheme generated by the dynamic iterative upgrade module and obtains the interference effect evaluation result. If the interference effect evaluation result is better than a set threshold, the interference scheme information is stored in the static module's database.

[0034] If the target information obtained by the static module from analyzing the target signal already exists in the static module's database, then the static module processes the target information to generate an interference scheme corresponding to the target information, and uses the interference scheme to implement active interference.

[0035] The dynamic iterative upgrade module includes modules for upgrading interference sources, updating modulation dimension parameters, and developing new interference rules. The static module includes other modules in the device. The new interference rule module and the interference strategy generation module are used to generate interference schemes. The static module includes an interference strategy generation module, a classic interference source module, an interference parameter generation module, a target state and behavior recognition module, and a real-time comprehensive evaluation module for target threat and interference effect. The real-time comprehensive evaluation module for target threat and interference effect is used to evaluate the interference effect of the interference schemes generated by the dynamic iterative upgrade module. The target state and behavior recognition module in the static module is used to analyze target signals to obtain target information. The database in the static module includes an interference mode mapping table for classic interference sources, an interference strategy information database for the interference parameter generation module, and a database for the real-time comprehensive evaluation module for target threat and interference effect.

[0036] As an optional implementation, in the second aspect of the present invention, the active interference method is implemented by the dynamically reconfigurable and upgradeable active interference device disclosed in the first aspect of the present invention.

[0037] The beneficial effects of this invention are as follows:

[0038] 1. This invention can upgrade the active interference capability without changing the system hardware structure by upgrading the software, and has the ability to be dynamically upgraded, thus reducing the system implementation cost;

[0039] 2. When faced with new threats, this system can dynamically generate corresponding interference signals in real time, and adjust the interference scheme and interference generation rules in real time according to changes in the threat and the interference effect. It has the ability to dynamically iterate, ensuring the real-time performance and effectiveness of the interference effect. Attached Figure Description

[0040] Figure 1 This is a block diagram illustrating the composition principle of an existing active interference system.

[0041] Figure 2 This is a diagram illustrating the composition of the dynamically reconfigurable and upgradable active interference device of the present invention. Detailed Implementation

[0042] To better understand the content of this invention, two embodiments are given here.

[0043] Figure 1 This is a block diagram illustrating the composition and operating principle of an existing active radar jamming system. For Figure 1 All active jamming systems are unable to dynamically adjust their jamming strategies based on the jamming effect and electromagnetic environment perception results. They cannot adapt to the dynamic feedback function requirements of cognitive electronic warfare, and therefore cannot fully realize the cognitive countermeasure function of cognitive electronic warfare. Furthermore, they cannot have the ability to be rapidly upgraded and iterated and dynamically reconfigured in response to the dynamic development of threat targets.

[0044] Example 1:

[0045] To address the problem that existing active jamming systems struggle to dynamically adjust jamming strategies based on jamming effectiveness and electromagnetic environment perception, and are ill-suited for the demands of cognitive electronic warfare, this invention discloses a dynamically reconfigurable and upgradeable active jamming device, whose composition is as follows: Figure 2 As shown, the system comprises: a radio frequency (RF) layer, a waveform layer, a parameter layer, an evaluation and decision layer, and a computation layer. The RF layer and the waveform layer are connected via RF cables and buses, while the waveform layer and the parameter layer, the parameter layer and the evaluation and decision layer, and the evaluation and decision layer and the computation layer are all connected via buses. Each layer is responsible for handling only the services of its own level, thus achieving decoupling between services at different levels. In the process of identifying radiation sources or generating active interference, the signal processing flow is passed layer by layer, and signals cannot be passed across layers. By designing the entire active interference system in a layered manner, the layers are loosely coupled, reducing the complexity of the system. With this architecture, the system can be dynamically upgraded layer by layer. During the upgrade process, only the parameters or operating modes of the layer to be upgraded need to be modified, while other layers remain unchanged. For example, if a new interference waveform needs to be added, only the classic interference source or the upgraded interference source in the waveform layer needs to be modified, while other layers remain unchanged.

[0046] The radio frequency (RF) layer comprises antenna modules and digital array modules. Antenna modules receive RF signals output from the digital array modules and transmit them into free space. Digital array modules include several T / R components of the same or different categories. T / R components processing signals in the same or similar frequency bands are grouped together, while those processing signals in significantly different frequency bands are grouped into different categories. T / R components of the same category use the same form factor and electrical interface to support subsequent expansion and upgrades of the system's RF capabilities. Digital array modules perform low-noise amplification, filtering, down-conversion, and analog-to-digital conversion on the RF signals input from the antenna modules. They output the digital signal obtained after analog-to-digital conversion to the digital beamforming module. Simultaneously, they receive signals output from the digital beamforming module, perform digital-to-analog conversion, up-conversion, filtering, and power amplification on them, and then output the amplified signal to the antenna modules. All digital array modules use a uniform form factor and electrical interface to facilitate flexible configuration according to subsequent interference requirements.

[0047] The waveform layer includes a digital beamforming module, classic interference sources, and upgraded interference sources. The digital beamforming module receives the output signal from the digital array module, constructs a received signal vector using the received signal, performs a receive beamforming operation on the received signal vector to obtain an output signal, and sends this output signal to the radiation source parameter measurement module. The receive beamforming operation includes amplitude and phase weighting. The number of interfaces between the digital beamforming module in the waveform layer and the digital array module in the RF layer is greater than the number of digital array modules actually installed in the system, to facilitate subsequent system upgrades.

[0048] The jamming source is a key component in an active radar jamming system responsible for generating jamming signals. The quality of the jamming signal generated by the jamming source often largely determines the jamming effect on the radar. An ideal jamming source is an arbitrary waveform generator, capable of generating jamming signals that perfectly meet the requirements of the active radar jamming system for jamming waveforms and patterns, and can change rapidly and arbitrarily. However, the implementation of such a system would be extremely complex, and it is often unnecessary in practical implementation.

[0049] Classic jamming sources are used to generate classic jamming waveforms whose jamming effects have been verified in practice. Upgraded jamming sources are used to generate new jamming waveforms for new threat targets. In terms of implementation, they are closer to the ideal jamming source than classic jamming sources, but they involve a trade-off between implementation complexity and the ideal jamming source.

[0050] The classic interference source generates an interference waveform based on the interference parameter information output by the interference parameter generation module. The classic interference source includes an interference signal transmitter and a modulator. It compares the interference parameter information output by the interference parameter generation module with the interference parameter information in its interference mode mapping table. If the interference parameter information output by the interference parameter generation module contains interference parameter information not defined in the interference mode mapping table, this undefined interference parameter information is sent to the upgraded interference source. The upgraded interference source generates a basic interference waveform based on the received interference parameter information, modulates it, and sends it to the digital waveform forming module. If the interference parameter information output by the interference parameter generation module is already included in the interference mode mapping table, the classic interference source generates the interference waveform using its interference signal transmitter and modulator based on the corresponding interference parameter information in the interference mode mapping table.

[0051] The jamming signal generator includes a noise jamming source generator, a response jamming source generator, and a repeater jamming source generator. The noise jamming source generator and the response jamming source generator are implemented using digital frequency synthesis (DDS), while the repeater jamming source generator is implemented using digital radio frequency store-and-forward (DRFM). The jamming signal generator generates a basic jamming waveform based on the jamming signal parameter information in the jamming parameter information of the jamming mode mapping table. The modulator modulates the basic jamming waveform output by the jamming signal transmitter based on the jamming pattern information in the jamming parameter information of the jamming mode mapping table, obtaining the final jamming waveform, which is then output to the digital beamforming module. The digital beamforming module uses the received jamming waveform to form a waveform vector, performs transmit beamforming on the waveform vector, obtains an output signal, and sends the output signal to the digital array module. The transmit beamforming operation includes signal correction, amplitude, and phase weighting operations. The parameters for the transmit and receive beamforming operations of the waveform vector by the digital beamforming module are determined based on the target angle and motion parameter information obtained from the radiation source parameter measurement module.

[0052] The upgraded interference source generates a basic interference waveform using an arbitrary waveform transmitter and / or a radio frequency storage and transceiver as needed. A modulator is then used to modulate the basic interference waveform to obtain the interference waveform, which is output to the digital waveform forming module. The upgraded interference source utilizes parameters from the signal waveform in the time domain, frequency domain, code domain, spatial domain, Doppler domain, and transform domain to generate the basic interference waveform. The upgraded interference source can control more signal waveform parameters used to generate and modulate the basic interference waveform than it can control. The transform domain refers to the signal space domain composed of a complete set of orthogonal functions, including Walsh functions, elliptic spherical wave functions, wavelet functions, Legendre functions, etc. Once the interference effect of the basic interference waveform and its corresponding interference parameter information generated by the upgraded interference source is verified, the basic interference waveform and its corresponding interference parameter information are sent to the interference mode mapping table of the classic interference source for storage, thereby updating the interference mode mapping table.

[0053] Table 1. Typical Radar Active Jamming Modulation Parameters and Jamming Pattern Mapping Table

[0054]

[0055]

[0056] Table 1 presents a typical mapping table of active radar jamming modulation parameters and jamming patterns. If the jamming parameter information output by the jamming parameter generation module is included in this table, then the jamming parameter information output by the jamming parameter generation module is the typical jamming modulation parameter in Table 1. The classic jamming source generates the corresponding jamming waveform according to the jamming pattern corresponding to the typical jamming modulation parameter in Table 1, and outputs the generated jamming waveform to the digital waveform forming module. If the jamming parameter information output by the jamming parameter generation module is not included in this table, then the upgraded jamming source generates the corresponding basic jamming waveform based on the jamming parameter information and modulates it to obtain the jamming waveform, which is then output to the digital waveform forming module. For example, the upgraded jamming source generates multiple jamming signals simultaneously based on parameters in various dimensions of the time domain, spatial domain, frequency domain, polarization domain, and energy domain, and quickly implements different modulations according to different timing requirements to achieve combined jamming.

[0057] The parameter layer includes a radiation source parameter measurement module, an interference parameter generation module, and a modulation dimension parameter update module.

[0058] The radiation source parameter measurement module processes the output signal received from the digital beamforming module to obtain the time-domain, frequency-domain, spatial-domain, and polarization-domain parameter information of the target signal, as well as the target motion parameter information. Based on the obtained target parameter information, it sorts and identifies the target, obtains the target identification result information, and sends the target parameter information to the target state and behavior recognition module. The target parameter information includes target signal parameter information, target motion parameter information, and target identification result information. The target signal parameter information includes the time-domain, frequency-domain, spatial-domain, and polarization-domain parameter information of the target signal.

[0059] The interference parameter generation module receives interference strategy information generated by the interference strategy generation module, determines whether the received interference strategy information is already included in the existing interference strategy information library of the interference parameter generation module, and if so, generates corresponding interference parameter information based on the interference strategy information and sends the generated interference parameter information to the classic interference source. If the received interference strategy information is not included in the existing interference strategy information library of the interference parameter generation module, it sends the received interference strategy information to the modulation dimension parameter update module. The interference strategy information library in the interference parameter generation module is updated in real time according to the update status of the interference rule library module. At the same time, relevant parameters of the interference waveform designed by the modulation dimension parameter update module, whose interference effect has been verified by actual testing, are added to its interference strategy information library to achieve real-time updating of the interference strategy information library.

[0060] The module that updates modulation dimension parameters designs an interference waveform based on the received interference strategy information, with the goal of optimizing the interference effect. It then obtains the relevant parameters of the interference waveform, uses these parameters as interference parameter information, and sends the interference parameter information to the classic interference source.

[0061] The module for updating modulation dimension parameters aims to optimize the interference effect and designs the interference waveform using an optimization method, such as reinforcement learning.

[0062] The evaluation decision layer includes a target status and behavior identification module, an interference strategy generation module, a dynamic threat database module, an interference rule database module, a real-time target threat and interference effect evaluation module, and a novel interference rule module.

[0063] The target status and behavior recognition module receives target parameter information from the radiation source parameter measurement module, classifies this information to obtain target status and behavior information, and then sends this information to the real-time comprehensive assessment module for target threat and interference effects and the dynamic threat database module. Target status information refers to the target's operational status, including search status, tracking status, identification status, calibration status, and data link status. Target behavior refers to changes in the target's status during operation due to internal operational needs or external electromagnetic environment influences.

[0064] The target state and behavior recognition module uses classification methods to obtain target state information and target behavior information. The classification methods include pattern classification methods and intelligent clustering methods.

[0065] The dynamic threat database module is used to store historical data of target status information, target behavior information, and target behavior feature information obtained by the target status and behavior recognition module. It also judges the target status information, target behavior information, and target behavior feature information received in real time. If the target status information, target behavior information, and target behavior feature information received in real time do not exist in the historical data, the target status information, target behavior information, and target behavior feature information received in real time are stored to complete the update of the dynamic threat database module.

[0066] The real-time comprehensive evaluation module for target threat and interference effect utilizes the received target status information and target behavior information to evaluate the target threat level and interference effect in real time, obtaining target threat level evaluation results and interference effect evaluation results respectively. Based on the target behavior information and interference effect evaluation results, target behavior feature information is obtained, and the obtained target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved. The real-time comprehensive evaluation module for target threat and interference effect evaluates the novelty of the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results with the historical data saved in its database. If the novelty is greater than a certain threshold, the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the novelty interference rule module, dynamic threat database module, and interference rule database module, and the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved as historical data in its database to update the database. Otherwise, the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the interference strategy generation module, dynamic threat database module, and interference rule database module.

[0067] The real-time comprehensive evaluation module for target threat and interference effect evaluates the target threat level and interference effect in real time, and obtains the target threat level evaluation result and interference effect evaluation result respectively. It is implemented using an artificial neural network.

[0068] The real-time comprehensive evaluation module for target threat and interference effect obtains target behavior feature information based on target behavior information and interference effect evaluation results, and uses classification methods or artificial neural networks to achieve this.

[0069] The interference strategy generation module is implemented using an artificial neural network. Based on the received target behavior feature information, target threat level assessment results, and interference effect assessment results, it uses machine learning methods to generate corresponding interference strategy information and sends the interference strategy information to the interference parameter generation module and the interference rule base module.

[0070] After updating the interference rule base module and the dynamic threat base module, the interference strategy generation module uses data from the interference rule base module, the dynamic threat base module, and the target threat and interference effect real-time comprehensive evaluation module as training data to train the artificial neural network module of the interference strategy generation module, thereby realizing the update of the interference strategy generation module.

[0071] The aforementioned interference rule base module is used to store interference strategies that have been effectively applied and to judge the interference strategies received in real time. If the interference strategy does not exist in the interference rule base module, then during the duration of subsequent active interference, the interference effect evaluation result of the interference strategy is judged based on the interference effect evaluation result received from the target threat and interference effect real-time comprehensive evaluation module. If the interference effect evaluation result is better than a certain threshold, then the interference strategy and the corresponding target behavior feature information, target threat level evaluation result and interference effect evaluation result are stored in the interference rule base module.

[0072] The new interference rule module determines the corresponding interference strategy generation rule based on the received target behavior feature information, target threat level assessment results, and interference effect assessment results. It then uses this interference strategy generation rule to generate corresponding interference strategy information and sends the interference strategy information to the interference parameter generation module and the interference rule library module.

[0073] The new interference rule module obtains interference strategy data from the interference rule base module based on the acquired target behavior feature information, target threat level assessment results, and interference effect assessment results. It uses the acquired data as a training dataset to reconstruct and train the artificial neural network model. The trained artificial neural network model is then used as the interference strategy generation rule. The received target behavior feature information, target threat level assessment results, and interference effect assessment results are input into the interference strategy generation rule to generate the corresponding interference strategy information.

[0074] The novel interference rule module can be implemented using probabilistic graphical models, knowledge graph models, and reinforcement learning models. Unlike the interference policy generation module, the novel interference rule module has the ability to dynamically update the interference policy generation rules.

[0075] The computing layer includes a resource monitoring and allocation module and a computing resource module. The resource monitoring and allocation module receives computing requests from various modules in the evaluation and decision-making layer, and allocates and distributes corresponding computing tasks to the computing resource module according to the computing requests. After the computing resource module completes the computing tasks and obtains the computing results, it receives and integrates the corresponding computing results and sends them to the various modules in the evaluation and decision-making layer that made the computing requests. The resource monitoring and allocation module also monitors the status of all computing resources.

[0076] Example 2:

[0077] An active interference method that can be dynamically reconfigured and upgraded is implemented using static modules and dynamic iterative upgrade modules. The static modules are modules that remain unchanged, while the dynamic iterative upgrade modules are modules that are updated in real time as the target changes.

[0078] The static module analyzes the target signal to obtain target information. If the target information is not stored in the static module's database, it is stored in the static module's database and then passed to the dynamic iterative upgrade module for processing. The dynamic iterative upgrade module processes the received target information accordingly and generates an interference scheme corresponding to the target information. This interference scheme is then used to implement active interference. The static module evaluates the interference effect of the interference scheme generated by the dynamic iterative upgrade module and obtains the interference effect evaluation result. If the interference effect evaluation result is better than a set threshold, the interference scheme information is stored in the static module's database.

[0079] If the target information obtained by the static module from analyzing the target signal already exists in the static module's database, then the static module processes the target information to generate an interference scheme corresponding to the target information, and uses the interference scheme to implement active interference.

[0080] The static module analyzes the target signal to obtain target information. If the target information is not stored in the static module's database, it is stored in the static module's database and then passed to the corresponding module in the dynamic iterative upgrade module for processing. The corresponding module in the dynamic iterative upgrade module processes the received target information accordingly and generates an interference scheme related to the target. The static module evaluates the interference effect of the interference scheme generated by the dynamic iterative upgrade module and obtains the interference effect evaluation result. If the interference effect evaluation result is better than a set threshold, the interference scheme information is stored in the database corresponding to the static module. If the target information received by the static module's database already exists in the database, the module corresponding to the target information in the static module processes the target information and generates an interference scheme related to the target.

[0081] The dynamic iterative upgrade module includes modules for upgrading interference sources, updating modulation dimension parameters, and developing new interference rules. The static module includes other modules in the device. The new interference rule module and the interference strategy generation module are used to generate interference schemes. The static module includes an interference strategy generation module, a classic interference source module, an interference parameter generation module, a target state and behavior recognition module, and a real-time comprehensive evaluation module for target threat and interference effect. The real-time comprehensive evaluation module for target threat and interference effect is used to evaluate the interference effect of the interference schemes generated by the dynamic iterative upgrade module. The target state and behavior recognition module in the static module is used to analyze target signals to obtain target information. The database in the static module includes an interference mode mapping table for classic interference sources, an interference strategy information database for the interference parameter generation module, and a database for the real-time comprehensive evaluation module for target threat and interference effect.

[0082] As an optional implementation method, in Embodiment 2 of the present invention, the active interference method is implemented by the dynamically reconfigurable and upgradeable active interference device disclosed in Embodiment 1 of the present invention.

[0083] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. An active interference method that can be dynamically reconfigured and upgraded, characterized in that, It is implemented using static modules and dynamic iterative upgrade modules. Static modules are modules that remain unchanged as the target changes, while dynamic iterative upgrade modules are modules that are updated in real time as the target changes. The target signal is analyzed using the static module to obtain target information. If the target information is not stored in the database of the static module, it is stored in the database of the static module and then handed over to the dynamic iterative upgrade module for processing. After processing the received target information using the dynamic iterative upgrade module, an interference scheme corresponding to the target information is generated, and active interference is implemented using the interference scheme. The interference effect of the interference scheme generated by the dynamic iterative upgrade module is evaluated using the static module, and the interference effect evaluation result of the interference scheme is obtained. If the interference effect evaluation result is better than the set threshold, the interference scheme information is saved into the database of the static module. If the target information obtained by the static module from analyzing the target signal already exists in the static module's database, then the static module processes the target information to generate an interference scheme corresponding to the target information, and uses the interference scheme to implement active interference. The dynamic iterative upgrade module includes an upgrade interference source module, an update modulation dimension parameter module, and a new interference rule module; the new interference rule module and the interference strategy generation module are used to generate interference schemes; the static module includes an interference strategy generation module, a classic interference source, an interference parameter generation module, a target state and behavior recognition module, and a real-time comprehensive evaluation module for target threat and interference effect; the real-time comprehensive evaluation module for target threat and interference effect is used to evaluate the interference effect of the interference schemes generated by the dynamic iterative upgrade module; the target state and behavior recognition module in the static module is used to analyze target signals to obtain target information; the database in the static module includes an interference mode mapping table for classic interference sources, an interference strategy information database for the interference parameter generation module, and a database for the real-time comprehensive evaluation module for target threat and interference effect.

2. A dynamically reconfigurable and upgradeable active interference device, used to implement the dynamically reconfigurable and upgradeable active interference method as described in claim 1, characterized in that, include: Radio frequency layer, waveform layer, parameter layer, evaluation and decision layer, and calculation layer; The radio frequency (RF) layer and the waveform layer are connected via RF cables and buses. The waveform layer and the parameter layer, the parameter layer and the evaluation and decision layer, and the evaluation and decision layer and the calculation layer are all connected via buses. Each layer is only responsible for processing the services of its own level.

3. The dynamically reconfigurable and upgradeable active interference device as described in claim 2, characterized in that, The radio frequency layer includes antenna modules and digital array modules; The waveform layer includes a digital beamforming module, classic interference sources, and upgraded interference sources; The parameter layer includes a radiation source parameter measurement module, an interference parameter generation module, and a modulation dimension parameter update module; The evaluation decision layer includes a target status and behavior identification module, an interference strategy generation module, a dynamic threat database module, an interference rule database module, a real-time target threat and interference effect evaluation module, and a novel interference rule module; The computing layer includes a resource monitoring and allocation module and a computing resource module.

4. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The classic jamming source is used to generate classic jamming waveforms whose jamming effects have been verified in practice; the upgraded jamming source is used to generate new jamming waveforms for new threat targets.

5. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The classic interference source compares the interference parameter information output by the interference parameter generation module with the interference parameter information in its interference mode mapping table. If the interference parameter information output by the interference parameter generation module contains interference parameter information not defined in the interference mode mapping table, the undefined interference parameter information is sent to the upgraded interference source. The upgraded interference source generates a basic interference waveform based on the received interference parameter information, modulates it, and sends it to the digital waveform forming module. If the interference parameter information output by the interference parameter generation module is already included in the interference mode mapping table, the classic interference source generates an interference waveform based on the corresponding interference parameter information in the interference mode mapping table, using its interference signal transmitter and modulator.

6. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The upgraded interference source uses an arbitrary waveform transmitter and / or radio frequency storage and transceiver to generate the basic interference waveform as needed, and uses a modulator to modulate the basic interference waveform to obtain the interference waveform. The generated interference waveform is then output to the digital waveform forming module. The upgraded interference source uses parameters in the time domain, frequency domain, code domain, spatial domain, Doppler domain, and transform domain of the signal waveform to generate the basic interference waveform. The number of signal waveform parameters that can be controlled by the upgraded interference source to generate the basic interference waveform and modulate the basic interference waveform is greater than the number of signal waveform parameters that can be controlled by the upgraded interference source. Once the interference effect of the basic interference waveform and its corresponding interference parameter information generated by the upgraded interference source is verified in practice, the basic interference waveform and its corresponding interference parameter information are sent to the interference mode mapping table of the classic interference source for storage, thereby completing the update of the interference mode mapping table.

7. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The interference parameter generation module receives interference strategy information generated by the interference strategy generation module, determines whether the received interference strategy information is already included in the existing interference strategy information library of the interference parameter generation module, and if it is, generates corresponding interference parameter information based on the interference strategy information and sends the generated interference parameter information to the classic interference source. If the received interference strategy information is not included in the existing interference strategy information library of the interference parameter generation module, it sends the received interference strategy information to the update modulation dimension parameter module. The interference strategy information library in the interference parameter generation module is updated in real time according to the update status of the interference rule library module. At the same time, the relevant parameters of the interference waveform designed by the update modulation dimension parameter module, whose interference effect has been verified by actual testing, are added to its interference strategy information library to achieve real-time updating of the interference strategy information library.

8. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The module that updates modulation dimension parameters designs an interference waveform based on the received interference strategy information, with the goal of optimizing the interference effect. It then obtains the relevant parameters of the interference waveform, uses these parameters as interference parameter information, and sends the interference parameter information to the classic interference source.

9. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The target status and behavior recognition module is used to receive target parameter information sent by the radiation source parameter measurement module, and to classify the target parameter information to obtain target status information and target behavior information. The obtained target status information and target behavior information are then sent to the target threat and interference effect real-time comprehensive evaluation module and the dynamic threat database module.

10. The dynamically reconfigurable and upgradeable active interference device as described in claim 9, characterized in that, The dynamic threat database module is used to store historical data of target status information, target behavior information, and target behavior feature information obtained by the target status and behavior recognition module. It also judges the target status information, target behavior information, and target behavior feature information received in real time. If the target status information, target behavior information, and target behavior feature information received in real time do not exist in the historical data, the target status information, target behavior information, and target behavior feature information received in real time are stored to complete the update of the dynamic threat database module.

11. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The real-time comprehensive evaluation module for target threat and interference effect utilizes the received target status information and target behavior information to evaluate the target threat level and interference effect in real time, obtaining target threat level evaluation results and interference effect evaluation results respectively. Based on the target behavior information and interference effect evaluation results, target behavior feature information is obtained, and the obtained target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved. The real-time comprehensive evaluation module for target threat and interference effect evaluates the novelty of the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results with the historical data saved in its database. If the novelty is greater than a certain threshold, the received target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the novelty interference rule module, dynamic threat database module, and interference rule database module, and the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are saved as historical data in its database to update the database. Otherwise, the target behavior feature information, target threat level evaluation results, and interference effect evaluation results are sent to the interference strategy generation module, dynamic threat database module, and interference rule database module.

12. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The interference strategy generation module is implemented using an artificial neural network. Based on the received target behavior feature information, target threat level assessment results, and interference effect assessment results, it uses machine learning methods to generate corresponding interference strategy information and sends the interference strategy information to the interference parameter generation module and the interference rule base module.

13. The dynamically reconfigurable and upgradeable active interference device as described in claim 12, characterized in that, After updating the interference rule base module and the dynamic threat base module, the interference strategy generation module uses data from the interference rule base module, the dynamic threat base module, and the target threat and interference effect real-time comprehensive evaluation module as training data to train the artificial neural network module of the interference strategy generation module, thereby realizing the update of the interference strategy generation module.

14. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The aforementioned interference rule base module is used to store interference strategies that have been effectively applied and to judge the interference strategies received in real time. If the interference strategy does not exist in the interference rule base module, then during the duration of subsequent active interference, the interference effect evaluation result of the interference strategy is judged based on the interference effect evaluation result received from the target threat and interference effect real-time comprehensive evaluation module. If the interference effect evaluation result is better than a certain threshold, then the interference strategy and the corresponding target behavior feature information, target threat level evaluation result and interference effect evaluation result are stored in the interference rule base module.

15. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The new interference rule module has the ability to dynamically update the interference strategy generation rules.

16. The dynamically reconfigurable and upgradeable active interference device as described in claim 3, characterized in that, The novel interference rule module determines the corresponding interference strategy generation rule based on the received target behavior feature information, target threat level assessment result, and interference effect assessment result, and uses the interference strategy generation rule to generate the corresponding interference strategy information, and sends the interference strategy information to the interference parameter generation module and the interference rule library module.

17. The dynamically reconfigurable and upgradeable active jamming device as described in claim 16, characterized in that, The new interference rule module obtains interference strategy data from the interference rule base module based on the acquired target behavior feature information, target threat level assessment results, and interference effect assessment results. It uses the acquired data as a training dataset to reconstruct and train the artificial neural network model. The trained artificial neural network model is then used as the interference strategy generation rule. The received target behavior feature information, target threat level assessment results, and interference effect assessment results are input into the interference strategy generation rule to generate the corresponding interference strategy information.

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