853results about "Communication jamming" patented technology

The invention belongs to the technical field of electromagnetic confrontation and intelligent decision making, and particularly relates to an electromagnetic situation intelligent confrontation decision making method and system based on deep learning. Threat level evaluation and resource adaptation degree analysis are carried out based on a multi-head self-attention mechanism, and a dynamic electromagnetic confrontation strategy knowledge graph is generated; a game confrontation engine driven by deep reinforcement learning is used for deducing an enemy countering path and a situation evolution result under different interference strategies of our party, interference parameters are optimized through a multi-agent collaborative learning model, weight parameters of a strategy network are updated in real time through online confrontation element learning, and historical confrontation efficiency data and current task constraints are combined to obtain a confrontation result. And dynamically generating a target interference decision sequence and an electromagnetic confrontation efficiency prediction report, and synchronously updating the electromagnetic confrontation strategy library. Therefore, the problems of serious disjunction of deduction results, low real-time antagonism and the like in the prior art are solved.

The invention discloses an unmanned aerial vehicle intrusion real-time alarm and countering guidance system based on RID information. The system comprises a multi-source information acquisition and fusion module, an intrusion detection and threat evaluation module, a real-time alarm and countering strategy generation module, a feedback evaluation and strategy iteration module, a signal loss prediction and compensation module, a comprehensive processing terminal module and the like. The system establishes a three-dimensional geofence model by analyzing remote identification information of the unmanned aerial vehicle and fusing radar, photoelectric, electromagnetic and other multi-source data, and performs dynamic judgment and multi-factor threat grading on a target intrusion state. Multi-mode alarm is automatically triggered according to the threat level, and a hierarchical countering scheme from broadcast alarm and electromagnetic interference to physical capture is generated; and when the RID signal is lost, the system realizes continuous tracking and state recovery of the target by using a motion prediction and probability association algorithm.

The invention relates to the technical field of unmanned aerial vehicle communication anti-interference, in particular to an unmanned aerial vehicle anti-interference system based on spectrum sensing. According to the invention, a spectrum sensing data acquisition module acquires multi-band frequency spectrum signal data and generates a spectrum interference characteristic spectrum; the interference source positioning module calculates an azimuth angle and a distance of an interference source and generates a spatial distribution data set; the three-dimensional interference field construction module constructs a three-dimensional interference field model containing an interference intensity gradient and a propagation direction in combination with the real-time height and geographic coordinates of the unmanned aerial vehicle; the anti-interference strategy generation module analyzes the vulnerability of a communication link, and dynamically adjusts the frequency band switching priority and the transmitting power allocation weight; the beam forming control module calculates antenna array phase offset and a beam pointing angle, and generates an adaptive beam forming parameter set. The system can improve the anti-interference capability and communication stability of the unmanned aerial vehicle in a complex electromagnetic environment.

The invention discloses an unmanned aerial vehicle detection countering method, system and equipment and a medium, and the method comprises the steps: obtaining a task instruction and sensing signals of a plurality of sensing devices in a monitoring region in real time, carrying out the preprocessing of the task instruction and the sensing signals, and obtaining the standardized modal data; performing feature extraction and high-level semantic extraction on the task instruction and the standardized modal data corresponding to each sensing signal in parallel to obtain a task context parameter and a high-dimensional feature vector of each sensing signal; fusing the high-dimensional feature vectors based on the task context parameters by using a space-time alignment multi-modal fusion algorithm to obtain multi-modal fusion features; using a neural network model to predict and generate a flight trajectory of the unmanned aerial vehicle in a future time period according to the historical trajectory data and the multi-modal fusion features; and performing threat level judgment and behavior anomaly detection based on the task context parameters and the flight trajectory, generating alarm information, and executing a security countering strategy generated based on the alarm information.

The invention relates to the technical field of unmanned aerial vehicle countering, in particular to a vehicle-mounted unmanned aerial vehicle detection and countering integrated system and a working method thereof. The method comprises the following steps: continuously scanning a preset airspace and acquiring radio frequency fingerprint characteristics of an unmanned aerial vehicle in real time through a radio detection unit carried by a vehicle-mounted platform; generating a target recognition result based on the radio frequency fingerprint features; when the target identification result determines that illegal unmanned aerial vehicle intrusion exists, generating a corresponding adaptive countering instruction based on the threat level; driving a directional interference unit to transmit a blocking signal to the target unmanned aerial vehicle according to the self-adaptive countering instruction; and synchronously monitoring the state response of the target unmanned aerial vehicle in the countering process, and feeding back the state response to the control unit in real time to dynamically adjust the countering strategy until the threat is relieved. According to the invention, full-process intelligent disposal of the illegal unmanned aerial vehicle is realized, and target detection, accurate identification and dynamic countering can be completed in real time in a vehicle moving state.

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.

The invention discloses a secure communication method for eavesdropping a D2D relay NOMA network. The communication process has two time slots; in the first time slot, the information source equipment sends an NOMA signal, and the multi-antenna relay equipment selects one antenna to send an interference signal to resist eavesdropping attack; in the second time slot, the relay equipment adopts the digital network coding technology to mix the interference signal of the first time slot and the decoded information source message, then adopts the NOMA technology to construct a novel NOMA signal, and re-selects one antenna to send the NOMA signal, and meanwhile, the information source sends another interference signal to weaken the eavesdropper; the NOMA user equipment and the eavesdropper calculate a required signal-to-noise ratio and a required signal-to-interference-and-noise ratio, and calculate a system outage probability and an eavesdropping probability; according to the invention, the two NOMA users can realize physical layer security communication in the D2D network, and the security of the physical layer is far better than that of a security communication scheme based on non-cooperative interference and a traditional security communication scheme based on cooperative interference.

The invention discloses an unmanned aerial vehicle countering method and countering device for radio detection, and relates to the field of signal processing, and the method comprises the steps: scanning and capturing a transient radio frequency pulse signal through a radio frequency receiving array, carrying out the time-frequency domain conjoint analysis, constructing a signal intensity space distribution matrix, and extracting a parameter set; matching with a protocol feature library, identifying an unmanned aerial vehicle remote control link protocol type, and calculating an unmanned aerial vehicle position and a threat level in combination with a signal time difference of arrival and a frequency difference; generating adaptive interference signal parameters according to the protocol type and the threat level; the method comprises the following steps: generating a directional beam through a two-dimensional phased-array antenna, focusing the position of an unmanned aerial vehicle to transmit an interference signal, monitoring signal intensity change and protocol response delay in real time, calculating a communication suppression ratio, and iteratively optimizing an interference strategy until a suppression threshold is reached. The method has the advantages that efficient and accurate signal capture and interference are realized through multi-channel radio frequency detection, accurate positioning and adaptive interference technologies, and the countering efficiency and adaptability are remarkably improved.

The invention belongs to the field of unmanned surface vessels, and discloses an unmanned cluster defense control platform and method based on a mooring aerial vehicle, and the platform comprises an aerial vehicle and unmanned vessel flexible cooperative control module, and an intelligent decision and tactical optimization module. The aerial carrier and unmanned ship flexible cooperative control module is used for constructing a closed command and control system independent of a wireless network on the basis of a mooring type coupling control technology, and the unmanned ship-unmanned aerial vehicle rigid connection requirement in a marine high dynamic environment is met; and the intelligent decision and tactical optimization module is used for constructing a virtual-real mapping marine combat experiment field based on a digital twin confrontation deduction technology, restoring a complex marine environment and a confrontation scene through digital modeling, and forming a closed-loop capability improvement mode.

The invention discloses a communication base station spectrum signal anti-interference method and device, equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring radio frequency spectrum signals in a coverage range of a base station, extracting interference signal features to generate a multi-dimensional feature vector group, constructing an interference propagation prediction matrix, calculating an interference diffusion probability, and generating a prediction data set. And according to the prediction data set, calculating anti-interference parameters under different interference combinations and constructing a strategy preset library. And when a target interference signal is detected, feature parameters are extracted to be matched with the prediction data set, and a corresponding anti-interference parameter combination is selected for processing. In the processing process, the monitored signal-to-noise ratio and the bit error rate are compared with a reference threshold value, feedback evaluation data are obtained, and preset library parameter configuration is updated. By implementing the technical scheme provided by the invention, the communication accuracy of the communication base station can be improved.

The invention discloses an anti-unmanned aerial vehicle monitoring and scheduling method with adaptive frequency band identification, relates to the technical field of anti-unmanned aerial vehicle monitoring and scheduling, and is used for solving the problem of poor frequency band identification and interference optimization. According to the method, a closed-loop mechanism with linkage of radar echo analysis, frequency band efficiency evaluation and monitoring scheduling is constructed, frequency band efficiency characteristics of an unmanned aerial vehicle target are extracted through multi-frequency-band monitoring data, a recommended tracking frequency band and a candidate countering frequency band are dynamically identified, and a scheduling reference scheme is generated in combination with frequency spectrum occupation and protected frequency band information. A quantitative basis is provided for frequency band selection and power configuration of the interference equipment; meanwhile, the frequency band weight and the recognition rule are continuously optimized based on monitoring operation feedback, fine judgment of the unmanned aerial vehicle signal and the external electromagnetic interference source is achieved, and the unmanned aerial vehicle wave band recognition accuracy, the scheduling reference reliability and the operation stability of the system in the complex electromagnetic environment are improved.

The invention discloses a wireless communication anti-interference strategy optimization method and system based on reinforcement learning, and relates to the technical field of wireless communication, and the method comprises the steps: obtaining the communication environment state information of a target scene in real time; inputting the communication environment state information into a pre-trained anti-interference decision model, and obtaining an anti-interference action at the current moment; and executing an anti-interference action through an anti-interference action actuator, synchronously collecting anti-interference action response information, and carrying out collaborative updating on the anti-interference decision model according to the anti-interference action response information. The technical problems that an existing wireless communication anti-interference technology lacks self-adaptability and intelligent decision-making capacity to a dynamic complex interference environment, an anti-interference strategy is difficult to adjust in real time, and the anti-interference effect is limited are solved.

The invention discloses a multi-mode unmanned aerial vehicle cooperative interference control method and device and a medium, and relates to the technical field of unmanned aerial vehicle interference, and the method comprises the steps: dynamically selecting an interference waveform parameter through employing an interference efficiency value of an unmanned aerial vehicle, obtaining a multi-mode interference instruction set, the method comprises the following steps: dynamically adjusting a waveform emission time sequence of an unmanned aerial vehicle by adopting a clock calibration protocol based on a consistency algorithm to form a composite interference signal, electing a coordination node according to a real-time interference efficiency value of the unmanned aerial vehicle, fusing radio frequency signal data and a multi-mode interference instruction set into the elected coordination node, and obtaining an interference scheme. And optimizing the transmitting power and frequency band selection of each unmanned aerial vehicle by adopting a game algorithm, generating an optimal interference parameter of each unmanned aerial vehicle, and controlling the array antennas of all unmanned aerial vehicles to radiate radio frequency interference signals to the interference target according to the composite interference signal, the optimal interference parameter and the interference scheme of each unmanned aerial vehicle. According to the unmanned aerial vehicle cooperative interference method, the cooperative interference capability, the intelligent level and the stability of multiple unmanned aerial vehicles are improved.

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 an anti-eavesdropping system and an anti-eavesdropping method for eavesdropping according to a substance vibration principle. The system comprises an anti-eavesdropping intelligent host which is arranged indoors and comprises a pickup module and a signal processing module; the pickup module is used for picking up a sound signal of an indoor target sound source; the signal processing module is connected with the pickup module and is used for processing the sound signal to generate an interference signal; and the at least one interference generator is arranged on a solid isolator for isolating the indoor space from the outdoor space, is connected with the anti-eavesdropping intelligent host, and is used for converting the interference signal into a mechanical vibration signal so as to interfere an eavesdropping device through the mechanical vibration signal. According to the environment medium vibration principle, anti-eavesdropping is effectively achieved through reverse interference of the mechanical vibration signals on the eavesdropping device, and the anti-eavesdropping device has the advantages of being independent of sites, rapid in deployment and low in cost.

The invention discloses an unmanned aerial vehicle spectrum anomaly detection and trajectory generation method based on unsupervised learning, and the method comprises the steps: continuously collecting broadband radio frequency signals through an SDR, and obtaining an IQ data stream; performing short-time Fourier transform to obtain a time-frequency spectrogram; performing robust normalization processing on the time-frequency spectrogram to obtain a standardized spectrogram after slow-varying drift suppression; performing constant false alarm rate detection, and generating a primary abnormal candidate binary mask; identifying spectrogram sub-blocks corresponding to the primary abnormal candidate binary masks from the standardized spectrogram, and inputting the spectrogram sub-blocks into a pre-trained unsupervised deep learning model to obtain an abnormal scoring graph; fusing with the primary abnormal candidate binary mask to generate an abnormal heat map; and clustering the abnormal heat map in a time-frequency dimension, carrying out cross-time window trajectory association and filtering on a cluster, and outputting a time-frequency trajectory of the unmanned aerial vehicle signal. According to the invention, the reliability of anomaly detection is enhanced, the risk of false detection and missing detection is reduced, and the continuity and accuracy of track generation are guaranteed.

The invention relates to the technical field of radio navigation and countering, and particularly discloses an unmanned aerial vehicle interference system and device based on phased array radar direction finding. The system comprises a phased array radar direction finding module, an environment electromagnetic propagation characteristic modeling module, an interference beam dynamic planning module and a digital beam forming interference module. Through constructing a three-dimensional electromagnetic propagation model and based on propagation loss and a multipath effect predicted by the model, a beamforming weight used for pre-compensating environmental influence is optimized and calculated, and finally an interference antenna array is driven to radiate an intelligent beam subjected to environmental pre-compensation, so that high-intensity interference is formed at an actual physical position of a target unmanned aerial vehicle, and the target unmanned aerial vehicle is subjected to environmental pre-compensation. Direction finding errors are overcome, and interference efficiency and electromagnetic compatibility are improved.

The invention discloses an unmanned aerial vehicle detection and directional interference system based on an artificial intelligence technology, which belongs to the technical field of unmanned aerial vehicle detection interference and comprises a data acquisition module, an unmanned aerial vehicle identification module, a geographic information correction module, a trajectory prediction module and a directional interference module. The data acquisition module is used for acquiring geographic information data of a target area based on a geographic information system, comprises a radar, an acoustic sensor and a radio frequency spectrum detection sensor, and is used for acquiring feature data of a moving object in the target area; and the unmanned aerial vehicle identification module obtains feature data of a moving object in the target area based on the data acquisition module. According to the unmanned aerial vehicle detection and directional interference system based on the artificial intelligence technology, the obstacle in the target area is identified, the personalized behavior of the unmanned aerial vehicle is analyzed, the trajectory prediction and interference strategy of the unmanned aerial vehicle is optimized in combination with topographic features, and the trajectory prediction precision and the directional interference effect are improved.

The invention provides an active suppression type multi-band electromagnetic interference filtering system and method for an unmanned aerial vehicle, and the system comprises a signal input unit which is used for receiving input signals from a plurality of to-be-protected modules in an unmanned aerial vehicle system; the interference identification unit is used for monitoring frequency spectrum information of the input signals in real time and identifying interference characteristics of the input signals; the control processing unit is used for generating a corresponding filtering control instruction according to the identification result; the active filtering unit is used for dynamically adjusting filtering parameters according to the control instruction and completing suppression of multi-band electromagnetic interference; and the signal output unit is used for outputting the filtered signal to the corresponding unmanned aerial vehicle module. The active suppression type multi-band electromagnetic interference filtering system is specially designed for an unmanned aerial vehicle system, has the characteristics of intelligence, light weight and high efficiency, can effectively improve the anti-interference capability of an unmanned aerial vehicle in a complex electromagnetic environment, and has a wide engineering application prospect.

The invention relates to the technical field of radio frequency signal monitoring, and particularly discloses a self-adaptive radio frequency interference resisting method and an interference system, which are used for constructing a full-process closed-loop system from interference detection, feature extraction, strategy generation to control execution. According to the method, characteristics of radio frequency interference signals are collected and analyzed in real time, an anti-interference strategy is intelligently generated based on a multi-dimensional parameter set, and then collaborative dynamic configuration of filter coefficients, impedance matching and compensation signals is carried out on a radio frequency front-end circuit of terminal equipment. The system can continuously monitor the quality index of the communication link, and when the index is lower than a preset threshold value, the optimization process can be automatically repeated, so that the continuity and the self-adaptability of the suppression effect are ensured. Besides, the even number method does not need to depend on physical shielding, efficient cooperative suppression can be carried out on multi-band, high-strength and broadband complex radio frequency interference, the bit error rate and the packet loss rate of a communication link are remarkably reduced, and stability and reliability of communication are guaranteed in a high-interference environment.

The invention relates to the technical field of unmanned aerial vehicle detection, in particular to a civil small unmanned aerial vehicle cat eye detection and countering system which comprises the steps that a cat eye detection module collects cat eye reflection characteristic signals, environment sensing data and unmanned aerial vehicle flight state associated information in an airspace; the threat level evaluation center identifies the type of the unmanned aerial vehicle and the intrusion risk level through an improved random forest model, and measures the real-time airspace position; the dynamic trajectory modeling module constructs a digital twin flight model of the civil small unmanned aerial vehicle, and simulates a flight trajectory and a potential intrusion path by using an intention pre-judgment algorithm; the grading countering unit generates a non-destructive countering strategy according to the intrusion risk grade, the flight path and the potential intrusion path; the man-machine interaction unit constructs a visual airspace monitoring scene, renders a detection result, an intrusion risk level and a countering effect in real time, and carries out man-machine interaction operation. Therefore, the problems of insufficient perception, poor decision collaboration and the like in the prior art are solved.

The invention relates to a black-box signal anti-attack method and device based on spectrum characteristics, and the method comprises the steps: S1, carrying out the preprocessing of an input IQ signal, converting a time domain signal into a frequency domain characteristic through Fourier transform, calculating an optimal frequency band according to the length of the input signal, and uniformly dividing the signal into a plurality of frequency bands; s2, performing nonlinear transformation on the spectrum features by using an adaptive spectrum disturbance generator, extracting key feature representation in the spectrum, and constructing frequency domain disturbance through the extracted amplitude and phase parameters; s3, performing time domain reconstruction on the frequency domain disturbance by using inverse Fourier transform, and superposing original signals to generate a target confrontation sample; s4, designing a loss function according to the attack effect, gradient guidance and disturbance constraint to optimize a spectrum disturbance generator; and S5, selecting a sensitive frequency band based on a dynamic mask mechanism, and iteratively optimizing countermeasure disturbance based on the selected frequency band. And when the query resources are consumed up, returning a final confrontation sample. The method only depends on input and output of a model, a self-adaptive spectrum disturbance generator and a dynamic mask mechanism are used for dynamically updating frequency domain confrontation disturbance, the frequency domain confrontation disturbance is converted into a time domain through inverse Fourier transform, and finally a confrontation sample with higher concealment is generated.

The invention discloses a portable multi-band unmanned aerial vehicle interference method and system based on a directional antenna array, and belongs to the field of unmanned aerial vehicle countering. The invention discloses a portable multi-band unmanned aerial vehicle interference method and system based on a directional antenna array. The method comprises the following steps: detecting and tracking a multi-sensor fused target; generating a multi-band interference signal; multi-band signal interference based on a directional antenna array; the system comprises a detection and tracking module, a signal generation and processing module, a directional interference array module, a main control and interaction module and an integrated platform and support module. The problems that in the prior art, a high-speed maneuvering unmanned aerial vehicle is difficult to track, and a modern unmanned aerial vehicle using multiple communication frequency bands at the same time cannot be effectively handled are solved. The method is high in interference efficiency and long in acting distance, wide effectiveness of unmanned aerial vehicles of different models and different communication configurations is guaranteed, multi-band coverage is achieved, the beam switching speed reaches the millisecond level through electronic beam forming, and the capacity of coping with complex targets is high.

The invention relates to a low-altitude protection management method and system, and the method comprises the steps: collecting the real-time flight information and identity information of a low-altitude unmanned plane through a multi-source detection device, and carrying out the identity verification based on the identity information, and obtaining an identity verification result; if the identity verification result is not passed, determining an abnormal target, and countering the abnormal target; if the identity verification result is passed, preprocessing the real-time flight information to generate preprocessed data; performing threat analysis based on the preprocessed data and historical flight data through a machine learning framework to generate a threat level; and determining a new abnormal target according to the threat level, and countering the new abnormal target. The problems of inaccurate identity recognition, lagging threat assessment and extensive countering measures in the prior art are solved, and the low-altitude unmanned aerial vehicle management and control accuracy and real-time performance are improved.

An unmanned aerial vehicle interference method and apparatus, and a device, a storage medium and a program product. The method comprises: acquiring configuration information corresponding to a communication signal of an unmanned aerial vehicle; and acquiring an interference signal corresponding to the configuration information, and transmitting the interference signal. By using the method, it is possible to efficiently, accurately and comprehensively interfere with an unmanned aerial vehicle.

The invention relates to the technical field of wireless communication, in particular to a secure communication perception integrated system optimization method based on rate segmentation multiple access and a reconfigurable holographic surface, which comprises the following steps: constructing a secure communication perception integrated system model; constructing a multi-objective joint optimization problem; a multi-objective joint optimization problem is decomposed into three sub-problems, and solving algorithms are designed respectively; and sequentially updating the solutions of the three sub-problems in an alternate iteration mode until a convergence condition is met, outputting an optimal parameter, and carrying out multi-dimensional verification on the system performance. According to the invention, through a rate segmentation multiple access public stream-private stream layered coding mechanism, the system can intelligently convert part of signal energy into man-made interference to potential eavesdroppers, and at the same time, a high-dimensional beam forming degree of freedom provided by a reconfigurable holographic surface is utilized; accurate orientation of legal user signals and accurate control of null depth of an eavesdropping direction are realized.

The invention provides a collaborative array position planning method for remote support interference of an electronic warfare aircraft, and belongs to the technical field of shipboard aircraft combat operation. The method comprises the following steps: firstly, in a long-distance support interference scene, determining an interference coverage range of an electronic jammer from two aspects of pitching and orientation; and secondly, calculating the interference effect of the electronic jammer based on the interference unified equation. Thirdly, based on the interference coverage range, designing constraint conditions and a target function, and establishing an electronic jammer collaborative array planning problem model; and finally, based on the electronic jammer collaborative array planning problem model, a genetic algorithm is utilized to solve an electronic jammer optimal array planning scheme of long-distance support interference. The method is suitable for a collaborative array planning problem of electronic warfare aircraft remote support interference, interferes the enemy radar when the jammer formation executes a remote support interference task, reduces the detection threat of the enemy radar to the strike formation, and guarantees the smooth execution of our strike task.

Disclosed herein is a method and system for detecting, monitoring and / or controlling one or more of mobile services for a mobile communication device (also referred to herein as a Controllable Mobile Device or CMD), and in particular, when the device is being used and the vehicle, operated by the user of the device, is moving. In addition, one aspect of the invention generally relates to a method and system for modifying a user's driving behaviors, in particular to a system and method for modifying a user's unsafe driving behaviors, e.g., using one or more services of a controllable mobile device while driving.

The invention discloses a sweep frequency interference modeling and interference optimization method for a remote control data link of an unmanned aerial vehicle. The invention provides: 1) a transmitter-receiver adaptive modeling system based on unmanned aerial vehicle signal priori parameters; 2) an interference source generation system which comprises four modulation types of single-tone interference, random binary code modulation interference, PN code MSK interference and pulse interference and integrates two modes of stepping frequency sweeping and frequency hopping frequency sweeping; and 3) an interference strategy intelligent optimization system based on a particle swarm optimization algorithm. Performing similarity verification through DTW, and establishing a high-fidelity communication link model; connecting an interference source to a communication system by adopting a front door coupling mechanism, and constructing a bit error rate-oriented black box optimization model; and finally, carrying out mechanism analysis on an optimization result through a multi-dimensional interference effectiveness evaluation system. According to the method, an efficient interference parameter optimization scheme is provided for the unmanned aerial vehicle countering defense system, the optimization convergence speed is remarkably improved while the interference efficiency is guaranteed, and the method has important application value in the field of low-altitude security and protection.

The invention relates to the technical field of unmanned aerial vehicle anti-interference, in particular to a cloud collaborative unmanned aerial vehicle anti-interference system, which comprises a sensing and pre-processing module, an edge calculation and collaboration module and a cloud decision and management module, and is characterized in that the sensing and pre-processing module comprises a multi-mode sensing unit, an identification analysis unit and a control unit; wherein the multi-mode sensing unit acquires environmental electromagnetic interference intensity, spatial topological data and multi-source sensing data in real time, and realizes interference source positioning through a data fusion technology; the identification analysis unit adopts a lightweight AI model to carry out real-time processing on the multi-modal data; according to the invention, rapid and accurate interference sensing and autonomous response are realized, rapid identification, positioning and classification of interference signals are realized through multi-modal sensing and a lightweight AI model, and the speed and accuracy of anti-interference response of the unmanned aerial vehicle in a complex electromagnetic environment are significantly improved by combining an adaptive antenna, high-speed frequency hopping and an intelligent control algorithm.