229 results about "Electronic countermeasure" patented technology

The invention discloses an SDR-oriented heterogeneous task scheduling and transmission system and method.The system comprises a heterogeneous platform composed of an ARM and an FPGA, a dynamic scheduling decision engine is arranged in the ARM and receives a task feature vector and a platform state parameter set as input, and the dynamic scheduling decision engine evaluates income and cost of task allocation to the ARM or the FPGA for execution to make a task allocation decision; the data generated in the task execution process or the execution completion result are interacted and synchronized between the ARM and the FPGA through the heterogeneous shared memory area HSM. The method realizes reduction of signal processing pipeline delay, improvement of data throughput and optimization of system power consumption, and is suitable for communication, electronic countermeasure and other scenes needing high-performance real-time signal processing.

The invention relates to the technical field of radar electronic countermeasures, and particularly discloses a radar radiation source open set identification method (ARPLAD) based on countermeasure reciprocity point learning. The method comprises the steps that adaptive noise reduction and feature extraction are conducted on radar signals through a feature extraction network fusing a DRSN module and an ECA module, channel-level adaptive noise reduction is achieved through the DRSN by means of a soft threshold function, and key features are strengthened through dynamic weight distribution by means of the ECA; an adversarial reciprocity point learning framework is adopted, reciprocity points are set for each known class to serve as out-of-class space representation, and known and unknown class feature spaces are separated by maximizing the distance between known class samples and the corresponding reciprocity points; introducing a central loss function to compress intra-class feature distribution, and constructing a weighted total loss function optimization network in combination with an open space limitation function; and calculating a class self-adaptive threshold value based on the training sample, and comparing the maximum distance from the sample to each reciprocity point with the threshold value during testing to judge known and unknown classes.

The invention relates to a detection-interference integrated unmanned aerial vehicle electromagnetic interference device, which belongs to the technical field of electronic countermeasure, and comprises an integrated design of an antenna module, a radio frequency front end module, a digital signal processing module and a main control module, the radio frequency front-end module comprises a detection receiving channel and an interference transmitting channel to process signal conversion, the digital signal processing module executes signal detection and analysis, intelligent interference decision and anti-self-interference signal processing based on a self-adaptive filtering algorithm, and the main control module is responsible for overall control and power supply. According to the invention, the technical problems of large response delay, complex system cooperation and incapability of continuous reconnaissance in the interference process of traditional anti-unmanned aerial vehicle equipment are solved. Real-time signal cancellation is achieved through the normalized least mean square algorithm, the reconnaissance capability is kept while interference is applied, the method has the advantages of being rapid in response, accurate in interference, low in power consumption and the like, and the countering efficiency is remarkably improved.

A portable multifunctional AI enabling electronic countermeasure system relates to the technical field of electronic countermeasure, and comprises a host housing, the bottom of the host housing is provided with a tripod, and the surface of the host housing is provided with a plurality of broadband antennas and a reference omnidirectional antenna; a plurality of transceiving front-end assemblies, a receiving front-end assembly and a signal processing unit are arranged in the host shell, the transceiving front-end assemblies are electrically connected with the broadband antennas in a one-to-one correspondence manner, and the reference omnidirectional antenna is electrically connected with the receiving front-end assembly; the plurality of transceiving front-end assemblies and the receiving front-end assembly are electrically connected with the signal processing unit; the signal processing unit is used for processing the radio frequency signals output by the plurality of transceiving front-end assemblies and the receiving front-end assembly by adopting an AI algorithm model to generate corresponding interference signals, and the interference signals are sent to the broadband antenna through the plurality of transceiving front-end assemblies; the method is used for solving the problems of weak interference capability and slow deployment speed in the prior art.

The invention discloses an adaptive electronic countermeasure interference source dynamic scheduling method based on spectrum sensing, and the method comprises the following steps: S1, collecting broadband spectrum data in an electromagnetic environment in real time through a broadband receiver, and transmitting the broadband spectrum data to a plurality of parallel shallow convolutional neural networks for feature extraction; s2, extracting the frequency characteristic, the power intensity, the signal-to-noise ratio and the current interference source state of the target signal in real time, and constructing a multi-dimensional state space; s3, constructing a multi-head depth Q network model based on the multi-dimensional state space, and outputting a decision instruction through parallel training; s4, combining the decision instruction into an interference decision instruction and sending the interference decision instruction to an interference source in real time; s5, the interference source executes the interference task and feeds back the interference effect; and S6, dynamically adjusting network parameters according to interference effect feedback. The method improves the interference decision precision and response efficiency, and is suitable for electronic countermeasure tasks in a complex electromagnetic environment.

The invention discloses a signal reconnaissance, positioning and interference method based on deep learning, and belongs to the technical field of electronic countermeasures. The method comprises the following steps: deploying distributed reconnaissance nodes to obtain broadband electromagnetic signals; generating a spectrogram through time-frequency transformation, and identifying a fixed frequency / frequency hopping signal based on a deep learning model; fusing multi-node reconnaissance results to realize target situation awareness; the optimal positioning cluster is selected through dynamic networking, and the target position is calculated in combination with the arrival angle and time difference information; generating an optimal interference strategy based on the target situation and the position trajectory; networking cooperative interference is implemented; behavior parameters are collected in real time, the interference effect is evaluated through a machine learning model, and the strategy is dynamically adjusted. According to the method, the technical effects of high-efficiency and self-adaptive signal reconnaissance, positioning and interference in a complex electromagnetic environment are achieved.

The invention provides a system for precise targeting in GPS-denied environments using a plurality of Computer-Readable Image Markers (CRIMs) and imaging devices. CRIMs, such as Apriltags, are deployed around a target area by an aerial vehicle. Each CRIM includes a unique code and an anchor that absorbs moisture to stabilize its position. High-altitude imaging devices capture the CRIMs' positions relative to the target, and this data is processed to create a map for autonomous navigation. An attack drone uses this map, identifying unmoved CRIMs to adjust its course and engage the target accurately, even in contested environments with electronic countermeasures. The method leverages robust image recognition, reducing computational load and enhancing reliability. The system offers a cost-effective solution for military and humanitarian applications where GPS is compromised.

The invention discloses a multichannel broadband receiver, and belongs to the technical field of microwave radio frequency and electronic control, the multichannel broadband receiver comprises a multichannel down-conversion assembly, a local oscillator power component, a power interface control panel and a VPX connector, the down-conversion assembly adopts a cavity-divided integrated structure, multiple identical radio frequency links are arranged in the same cavity in parallel, and the VPX connector is connected with the local oscillator power component. Down conversion from a 2-18GHz radio frequency signal to a 1.3-2.3 GHz intermediate frequency signal is realized through two-stage frequency mixing; the power supply interface control board takes an FPGA as a core, integrates the functions of multi-path power supply conversion, driving isolation, state monitoring and the like, and realizes channel gain power failure storage and calling, BIT self-inspection, nanosecond rapid turn-off and multi-parameter real-time monitoring through software and hardware cooperation. Through collaborative innovation of the structure, circuit and control, high integration, high channel consistency, high isolation and high intelligence of the multi-channel receiver are realized, and the multi-channel receiver is suitable for the fields of high-performance radars, electronic countermeasures and the like.

The present invention discloses an electronic countermeasure offline decision-making method, system, device and storage medium. Due to the fact that in a complex electromagnetic environment, the radar state information obtained by the jammer is partially observable and has deviations, the jamming strategy obtained by the general decision-making method is often difficult to guarantee performance when deployed in a real environment due to its limitations. Therefore, the solution provided by the present invention models the electromagnetic environment into an opponent intelligent agent, and the jammer intelligent agent and the opponent intelligent agent are interactively trained to obtain the final jammer intelligent agent. This can better make radar jamming decisions, making the jammer's decision-making in a complex electromagnetic environment more efficient and safe.

The invention belongs to the technical field of electronic countermeasure and target positioning, and relates to a TDOA radiation source tracking and trajectory prediction method based on EKF. The method comprises the following steps: S1, setting N sensor nodes to measure a TDOA observation value; s2, establishing a radiation source motion state space model; s3, calculating a Jacobian matrix to linearize the nonlinear observation equation; s4, executing an EKF prediction and updating step, and updating state estimation by using a TDOA observation value; s5, predicting a future trajectory based on the current state; and S6, performing loop execution to realize continuous tracking. According to the method, the nonlinear problem of TDOA positioning is solved through the EKF algorithm, high-precision tracking and trajectory prediction of the high-speed moving radiation source are achieved, good robustness and real-time performance are achieved, the algorithm complexity is moderate, and the method is suitable for accurate positioning of the moving radiation source in an electronic countermeasure system.

The invention relates to the technical field of radars, in particular to a low-interception-probability radar waveform design method and device, and the method comprises the steps: obtaining a preset MDP tuple; constructing a Markov decision model framework based on a preset MDP tuple, wherein the Markov decision model framework comprises a design framework corresponding to the power adopted for constructing a radar waveform and the complexity of a radar waveform intra-pulse modulation pattern; performing reinforcement learning on the Markov decision model framework in a strategy optimization direction taking maximization of long-term accumulated rewards as a target to obtain a reinforcement learning optimization model of radar waveform design; and solving the reinforcement learning optimization model of the radar waveform design by using a model-free Q-learning algorithm to obtain the design parameters of the radar wave, thereby realizing the intelligent design of the low-interception probability radar waveform in the complex electronic countermeasure environment, and improving the concealment and detection performance balance capability of the radar in the unknown countermeasure environment.

The invention discloses a radar interference robust identification method based on a double-branch residual fusion network, and belongs to the field of radar interference identification. The problems that multi-dimensional information of interference characteristics is difficult to comprehensively capture and weak or variant interference in a complex environment is difficult to accurately recognize in an existing method are solved. The method comprises the steps that radar receiving signals are acquired, and a scrambling signal set is constructed; performing time-frequency processing on the interference signal to generate a time-frequency graph; the method comprises the following steps of: constructing a double-branch residual fusion network which comprises a time domain branch used for respectively carrying out one-dimensional convolution operation on a real part one-dimensional sequence and an imaginary part one-dimensional sequence of a radar signal, and extracting time domain features; the time-frequency domain branch is used for taking the time-frequency graph as input and extracting time-frequency features through the multiple residual modules and the DBB multi-branch convolution module in sequence; the self-adaptive feature fusion module is used for carrying out weighted fusion on the sum to generate fusion features; and inputting the fusion features into a full connection layer, and outputting a radar interference category identification result. The method is mainly used in electronic countermeasure field.

The invention relates to the technical field of electronic countermeasures, in particular to an unmanned aerial vehicle group dynamic interception method and system based on distributed interference array collaboration. According to the method, an interference node cluster with autonomous logic association is dynamically deployed in a defense domain, and an elastically reconfigurable distributed interference field domain is formed through a software defined radio architecture; time-varying spectrum features are extracted through an adversarial neural network, and a dynamic threat fingerprint database is constructed; generating an interference vector with frequency band following and power self-adaption based on the dynamic threat fingerprint database, and updating the feature weight of the dynamic threat fingerprint database in real time according to interference efficiency feedback; and according to the situation evolution trend of the dynamic threat fingerprint database, a hierarchical interference wave sequence is generated based on a multi-agent consensus protocol, and a space-time coupled interception chain is formed. Through the method, the whole-process dynamic confrontation capability of the unmanned aerial vehicle group is realized, the efficient interception performance is maintained in a complex electromagnetic environment, and meanwhile, the interference risk on legal communication is reduced.

The invention discloses a spectrum signal detecting and positioning method and system based on unsupervised reinforcement learning, and belongs to the technical field of wireless spectrum sensing and electronic countermeasure. In order to solve the problems of low-power and low-SNR signal automatic detection and positioning in a complex electromagnetic environment, the method comprises the steps of nonlinear normalized spectrum mapping, anchor frame heuristic initialization, multi-source state coding and attention fusion, PPO-based continuous action reinforcement learning, a multi-dimensional learnable reward function and a multi-round dynamic detection strategy. And adaptive detection and track positioning of the frequency spectrum signal are realized. According to the method, high-precision detection and time-frequency track positioning of various types of signals in a low SNR environment can be realized without manual labeling, and the robustness and universality of spectrum sensing are improved.

The invention discloses a semi-supervised radiation source individual identification method based on multi-round clustering and pseudo label updating, which is characterized in that on the basis of a structured slice of a radiation source signal, a deep neural network is adopted to carry out feature extraction and classification prediction on a sample, and network training is carried out through multi-round change trajectory clustering and a pseudo label stability judgment mechanism; the method comprises the following steps: setting a trigger condition of pseudo-label generation as stable convergence of training loss, tracking a historical prediction trend of a sample, screening out a sample set with consistent category evolution trajectory and discrimination as a pseudo-label candidate, expanding a supervised data volume through a pseudo-label iteration updating strategy and a training sample set dynamic reconstruction mechanism, and obtaining a pseudo-label generation result. And finally, based on a joint loss optimization strategy, realizing comprehensive identification of all unknown samples in continuous iteration. According to the method, the adaptive capacity of the identification model to unknown category and weak label data is improved, and the method is suitable for complex wireless environments such as electronic countermeasure, frequency spectrum monitoring and signal traceability needing high-robustness identification capacity.

The invention discloses a radar communication integrated radiation source simulation system and method. The system comprises an upper computer control unit, a signal processing unit, an up-conversion unit and an antenna unit. An unknown radar or communication signal is analyzed by adopting a signal characteristic analysis method based on phase difference, whether the signal is a complex signal is judged, the waveform of the signal is stored and generated by adopting a DDWS technology aiming at the unknown complex signal, the waveform of the signal is directly generated by adopting a modulation module of a signal processing unit aiming at a conventional signal, and the waveform of the signal is directly generated by adopting a modulation module of a signal processing unit aiming at a known complex signal. The waveform of a fixed part in a signal is synthesized by adopting a DDWS technology, a modulation module of the signal processing unit is used for generating a non-fixed part, and the fixed part and the non-fixed part are combined according to a signal message format time sequence, so that the simulation of a complex signal is realized, and the requirement of current electronic countermeasure training on radar communication integrated radiation source simulation is met.

The present invention relates to a method, device, electronic device, and readable storage medium for generating a baseband signal, belonging to the technical field of electronic countermeasure simulation training signal generation technology, and solving the problem of low baseband signal generation efficiency in the prior art. The method comprises: generating multiple alternative baseband sampling rates based on a final sampling rate; among the alternative baseband sampling rates, determining the corresponding baseband sampling rate according to the characteristics of each signal, and forming a baseband sampling group with signals having the same baseband sampling rate; and each baseband sampling group independently generates a signal. The technical solution of the present invention improves the efficiency of baseband signal generation and saves storage and communication resources.

The invention discloses a multi-band high-stability ferrite magnetic material composite formula and a preparation process, and relates to the technical field of magnetic materials. The ferrite magnetic material composite formula comprises 38-42 parts of ferric oxide powder, 37-41 parts of ferroferric oxide powder, 6-12 parts of graphene nanosheets, 5-7 parts of hydroxypropyl methyl cellulose, 6-9 parts of lanthanum oxide, 4-6 parts of scandium oxide, 1-3 parts of nano titanium dioxide, 4-6 parts of bismuth magnesium boron, 9-13 parts of ferric sulfate, 3-5 parts of manganese sulfate, 4-6 parts of zinc sulfate, 2-4 parts of copper sulfate and 2-3 parts of samarium sulfate. By utilizing a physical vapor deposition gradient doping process, the problems that an existing ferrite magnetic material is single in electromagnetic performance, cannot stably and efficiently work in a multi-frequency-band complex electromagnetic environment and cannot meet the requirements of the fields of communication, radar, electronic countermeasure and the like for wide-frequency-band and high-performance magnetic materials can be solved.

The invention belongs to the field of electronic countermeasures, and particularly relates to a sidelobe cancellation method for extracting auxiliary channel array elements in electronic countermeasures. The method comprises the following steps: step 1, determining the number of main channel array elements, array element spacing, the number of auxiliary channels and the position of each auxiliary channel array element in a main channel; step 2, according to the antenna parameters, calculating antenna directional diagrams of the main channel and the auxiliary channel; and step 3, comparing amplitude values under the same azimuth angle and pitch angle, and the like. According to the invention, the problem that the target signal is attenuated is effectively improved.

The present invention discloses an intermittent sampling interference method and system based on pseudo-random sequence frequency shift modulation, which relates to the technical field of radar electronic countermeasures, including intermittent sampling of enemy radar signals to obtain intermittent sampling signals; setting a pseudo-random sequence and a frequency shift amount, constructing a frequency shift amount function and a frequency shift modulation function; using the frequency shift modulation function to modulate and forward the intermittent sampling signal to obtain a frequency shift modulation interference signal; then performing matched filtering processing, parsing the filtered interference signal to obtain an optimal frequency shift amount matrix; substituting the optimal frequency shift amount matrix into the filtered interference signal to obtain an optimal interference signal, and implementing interference on the enemy radar. The present invention causes false targets to randomly superimpose around the real target, forming strong false targets with random distributions of leading, nearby, and lagging; not only adjusting the amplitude and position distribution of the strong false targets, but also destroying the time-frequency distribution and spatial distribution characteristics of the intermittent sampling interference, having both suppression and deception interference effects.

This invention provides a communication countermeasure simulation method based on random simulation, belonging to the field of electronic countermeasure simulation technology. The method first establishes a probability distribution model of reconnaissance information deviation for key parameters of the communication target; then, based on the probability distribution model of each parameter deviation, independent random sampling is performed to generate instantaneous values ​​of frequency deviation, positioning deviation, and modulation pattern recognition results at each moment, and the guidance parameters of the jammer are determined; next, the instantaneous interference-to-signal ratio (ISR) at the target receiver at the current moment is calculated; finally, the ISR calculated at the communication receiver is compared with a preset communication performance degradation ISR threshold to determine whether the jamming is successful. The model of this invention has clear physical meaning and can accurately quantify the impact of reconnaissance information deviation and propagation loss on the jamming effect, significantly improving the credibility and practicality of the simulation evaluation.

The invention provides a multifunctional radio frequency comprehensive integrated universal transceiver and a configuration method thereof, and belongs to the technical field of radio frequency transceiver systems, and the equipment comprises a multi-channel radio frequency transceiver assembly, a variable frequency multi-channel local oscillator module, a radio frequency switch matrix, a baseband signal processing module, a plurality of digital-to-analog converters and a plurality of analog-to-digital converters; the variable-frequency multi-channel local oscillator module is used for generating local oscillator signals corresponding to a plurality of function modes and dynamically distributing the local oscillator signals to a plurality of pairs of transceiving channels through the radio frequency switch matrix; and the baseband signal processing module is used for dynamically configuring the multi-channel radio frequency transceiving component, the variable-frequency multi-channel local oscillation module and the radio frequency switch matrix, so that the universal transceiving equipment performs time division multiplexing or performs at least two function modes of radar, communication and electronic countermeasure in parallel. According to the invention, the integrated transceiver which performs radar, communication and electronic countermeasure functions in a time-sharing or parallel manner is realized.

The invention relates to the technical field of radar electronic countermeasures, in particular to an equipment intelligent decision-making method based on threat level classification. Comprising the following steps: constructing an electronic warfare decision state space containing own defense equipment, enemy attack equipment and an environment state; selecting threat assessment factors, determining the weight of each factor through a preset weight calculation method, quantifying the total threat value of single enemy equipment and a battlefield, and dividing at least two threat levels according to a threshold value; a collaborative decision-making framework comprising a high-level threat evaluation network, a plurality of low-level strategy networks and a time sequence state control module is constructed, the high-level network outputs threat levels and activates corresponding low-level networks, the low-level networks output decision-making actions, and the time sequence module calculates a state change score and judges whether a new decision is triggered or not; and network training optimization is carried out, the network is updated through initialization parameters, partition management track data and a preset algorithm, and the exploration rate is dynamically adjusted. The method has the advantages that decision pertinence and real-time performance are improved; and the decision-making stability of complex electronic warfare scenes is enhanced.

The application provides a signal semantic segmentation and parameter extraction method based on RepViT, which is suitable for communication signal monitoring, radar target identification, spectrum sensing and electronic countermeasure scenes in complex electromagnetic environments, and comprises: multi-signal-to-noise ratio signal data set construction and preprocessing, design of a signal semantic segmentation model based on RepViT, model training and optimization, signal semantic segmentation reasoning, and extraction of key signal parameters; the application realizes end-to-end, automatic and high-precision extraction from deep learning semantic segmentation masks to signal start time, duration, center frequency and bandwidth parameters, and effectively improves the intelligent level and processing efficiency of signal parameter analysis.

This invention discloses a dual-station three-dimensional cross-location method based on grid search, belonging to the field of electronic countermeasures reconnaissance technology. Based on the azimuth-elevation angle vectors measured by reconnaissance equipment at two stations (air or ground), the direction-finding vectors of the corresponding radiation sources at each station are transformed into a northeast-sky coordinate system with their respective stations as the origin. Then, the dual-station direction-finding vectors are transformed into the same coordinate system using a coordinate system transformation method. The coordinates of the radiation sources are searched using a grid search method that minimizes the straight-line distance between opposite planes. Finally, the coordinates of the radiation sources searched multiple times are clustered to obtain the optimal positioning coordinates.

The invention belongs to the technical field of electronic countermeasures, and particularly relates to a distributed jammer closed-loop coherent control method based on synthesis effect feedback, which comprises the following steps of: modeling signal coherent synthesis efficiency, acquiring coherent synthesis efficiency of a jammer A and a jammer B under different phase differences under an error-free condition, and calculating the coherent synthesis efficiency of the jammer A and the jammer B; establishing a phase difference-coherent combination efficiency mapping relation reference database; a-B jammer phase correction is carried out; and jammer A-C correction is carried out. According to the method, the robustness and the engineering practicability are remarkably improved; the cost, the power consumption and the complexity are effectively reduced; according to the invention, by taking a synthesis effect as a guide, the harsh requirement on the absolute space-time precision of a single node is relaxed, common commercial devices with lower cost and lower precision are allowed to be used for construction, and meanwhile, the complexity of initial calibration and setting is simplified, so that the hardware cost, power consumption and deployment and maintenance difficulty of the whole distributed mode are greatly reduced; and the dynamic self-correction and long-term stability capabilities are endowed.

The invention belongs to the technical field of electronic countermeasure, and discloses unmanned aerial vehicle interference equipment with low power consumption and controllable interference distance and a control method thereof, and the equipment comprises a target detection module, a main control module, a frequency source module, a high-precision numerical control attenuator module, a power amplifier module, a grid voltage control module, a signal emission module and a feedback adjustment module. All the modules are electrically connected to form a complete closed-loop link of interference signal generation, power regulation and control, signal emission and feedback regulation and control. The method is suitable for performing accurate and efficient prevention and control tasks on the unmanned aerial vehicle, realizes accurate control of interference output power and on-demand matching of interference distance, reduces equipment power consumption, and improves endurance performance.

The invention provides a PPO-based unmanned aerial vehicle interference power adaptive distribution method and system, and belongs to the technical field of unmanned aerial vehicle electronic countermeasures. According to the method, real confrontation elements such as radar target threat dynamic change, unmanned aerial vehicle power consumption and unmanned aerial vehicle shot-down are simulated by constructing an unmanned aerial vehicle electronic confrontation environment model, and a simulation environment close to reality is provided for training of a power distribution decision model. On the basis, a PPO algorithm is utilized to train an actor-commentator network, so that the power distribution decision model can adaptively output an optimal power distribution scheme according to a real-time confrontation environment state. Compared with a traditional method based on rules and an optimization algorithm, the method has strong environment adaptive ability, can adjust the decision strategy in real time in dynamic scenes such as radar threat change and unmanned aerial vehicle state change, and significantly improves the flexibility and effectiveness of electronic countermeasure.

This invention discloses a radar clutter signal simulation method based on dynamic scene simulation, mainly addressing the problems of low computational efficiency and insufficient flexibility of traditional clutter simulation methods under conditions of large scenes, long time series, and multiple dynamic factors. The implementation scheme includes: constructing a digital simulation scene based on radar signal parameters and dynamic scene information to determine the clutter region to be simulated; discretizing the clutter region into a uniform basic grid in the range-azimuth plane, and then aggregating it into multiple independently processable clutter channels; calculating the amplitude, Doppler frequency, and phase parameters of the center point of each channel in parallel, constructing a two-dimensional convolution kernel reflecting spatial correlation, and using this convolution kernel to efficiently expand the center point parameters to the entire channel, generating a continuously distributed parameter field; and transmitting the parameter fields of each channel to a hardware logic unit to complete signal modulation and synthesis, outputting a high-fidelity radar clutter signal. This invention can achieve rapid, high-fidelity parameter generation from point to field, and significantly improves computational efficiency while strictly maintaining physical accuracy. It can be used for radar system simulation, electronic countermeasures testing, and radar performance evaluation.

The invention relates to a common-caliber three-frequency-band miniaturized radio frequency decoy system, which belongs to the electronic countermeasure technology and comprises a common-caliber forward antenna, a common-caliber backward antenna, a front line TR module, a backward TR module, a common local oscillator intermediate frequency module and a signal processing module. The common local oscillator intermediate frequency module is respectively connected with the signal processing module, the front TR module and the back TR module; the front line TR module is connected with a common-caliber forward antenna; and the backward TR module is connected with a common-caliber backward antenna. Under the condition of a certain size, integration of the three-frequency-band radio frequency bait is completed by utilizing technologies of common caliber, common local oscillator, common intermediate frequency branch and the like, so that a single bait can resist single-frequency-band seekers, double-frequency-band seekers and three-frequency-band seekers, and the survival rate of airplanes facing air-to-air missiles is greatly increased.