166 results about "Countermeasure" patented technology

The invention relates to the technical field of low-altitude prevention and control, in particular to a low-altitude target detection identification and countering prevention and control system which comprises an operation and maintenance management platform, a multi-source data fusion unit, an intelligent noise reduction preprocessing unit, a general command platform, a dynamic threat evaluation unit and a cross-domain collaborative interface module. The detection and recognition precision and efficiency are improved through intelligent noise reduction and multi-source data fusion, intelligent collaborative countering is achieved through an intelligent decision center and a full-link countering unit, global situation awareness is enhanced through cross-domain data collaboration, operation and maintenance management and system stability are optimized by means of a prediction maintenance module and a modular architecture, and the detection and recognition efficiency is improved. The system can make up for the shortages of domestic existing systems, guarantees the airspace safety of key scenes, and reduces the long-term operation cost.

The invention discloses a low-altitude unmanned aerial vehicle countering monitoring system based on state feature decoding, relates to the technical field of unmanned aerial vehicle prevention and control, and is used for solving the problem of poor low-altitude target detection and countering. According to the invention, through closed-loop management and control of heterogeneous radar networking detection, signal level fusion processing, threat assessment and resource scheduling and intelligent countering decision, accurate identification and directional countering of the low-altitude unmanned aerial vehicle are realized; according to the method, the detection precision and the micro-Doppler feature extraction capability of a low-speed small target are improved by combining a virtual aperture synthesis technology, then unbalanced resource allocation is implemented based on a threat level, the system efficiency is optimized, and finally seamless migration of an interfered node task is realized by constructing a signal interference situation map. And continuous tracking and effect evaluation on the target are maintained in the active radio frequency countering process, so that the overall efficiency and reliability of low-altitude security and protection in a complex environment are effectively improved.

The application discloses a kind of laser anti-UAV system cooperative countermeasure decision methods, from multiple distributed deployment laser anti-UAV system according to the damage requirement decision of unmanned aerial vehicle best countermeasure combination. Main decision mechanism and process are: according to the unmanned aerial vehicle image information obtained by each laser anti-UAV system detection equipment, the unmanned aerial vehicle in the air is cooperatively positioned, and the flight trajectory data of unmanned aerial vehicle is obtained;Interception feasibility sequencing is carried out to the laser anti-UAV system satisfying accessibility;The launch energy of each accessible system is calculated in turn according to the distance and direction of target, and the energy of accessible system and the damage threshold of unmanned aerial vehicle are judged to choose, the decision method of the application can complete the countermeasure to unmanned aerial vehicle by the cooperation of multiple laser anti-UAV systems, overcome the defect that single laser anti-UAV system cannot realize countermeasure due to insufficient energy, reduce the requirement of energy, volume and the like of single laser anti-UAV system.

The invention discloses an intelligent bidding document generation and waste bidding risk confrontation optimization method and system, and relates to the technical field of natural language processing in the power industry. In order to solve the problems of low bid winning rate, high bid rejecting risk and mismatching of text styles in the existing intelligent bidding document in the power industry, the method comprises the following steps of: converting unstructured power bidding and tendering data into a knowledge graph which can be reasoned by a computer; building a bid invitation party preference feature vector model and calculating preference weight distribution based on a bid invitation party holographic image of a knowledge graph and recessive preference mining; self-adaptive generation of a bidding document first draft is carried out based on style features obtained through emotion calculation and semantic features of stealth preferences, and alignment of bidding document intonation and project attributes is realized through calculation of text similarity; carrying out waste bid risk confrontation detection and correction based on anti-fact reasoning; and carrying out confrontation detection according to the waste bid risk, and carrying out automatic correction so as to output a compliance final manuscript. The method is mainly used for generating the intelligent bidding document of the power industry and carrying out the waste bidding risk confrontation test.

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 provides unmanned aerial vehicle reconnaissance and countering equipment which comprises a software system and a hardware system. The software system comprises a multi-source information fusion system and a decision system; the hardware system comprises a processor, a radar detection device, a photoelectric identification device, a reverse takeover device and a countering device; the processor is used for operating the multi-source information fusion system and the decision-making system; the radar detection equipment and the photoelectric identification equipment are in signal connection with the processor, and the fusion investigation information of the unmanned aerial vehicle is processed by executing the multi-source information fusion system; the reverse takeover device and the countering device are in signal connection with the processor, and the reverse takeover device or the countering device is selected to be adopted for countering the unmanned aerial vehicle through the execution decision-making system. According to the invention, reconnaissance, countering and pipe connection functions can be integrated. Moreover, the recognition accuracy is improved through a multi-source information fusion system, precise detection of target signals is realized, and a better perception effect is achieved for low-slow-small unmanned aerial vehicle targets.

The invention provides a multi-mode unmanned aerial vehicle countering method and system based on ground-air cooperation, relates to the technical field of unmanned aerial vehicle countering, and solves the problems that an existing unmanned aerial vehicle countering technology is low in cooperation efficiency, weak in environmental adaptability and insufficient in real-time response capability. In the method, a ground station uses a radar to scan a target unmanned aerial vehicle in a monitoring airspace, calculates basic parameters of the target unmanned aerial vehicle, constructs a threat degree evaluation model, obtains the threat degree of the target unmanned aerial vehicle, and uses a greedy algorithm to carry out target distribution between a countering unmanned aerial vehicle and the target unmanned aerial vehicle to form a distribution scheme; the distribution scheme is uploaded to the countering unmanned aerial vehicle, and a target unmanned aerial vehicle distributed to the countering unmanned aerial vehicle in a monitoring airspace is recognized through a built-in lightweight visual recognition algorithm; a target unmanned aerial vehicle is continuously tracked through a built-in visual tracking algorithm, and a corresponding countering means is dynamically selected based on recognition and tracking states. According to the invention, the countering response speed of the unmanned aerial vehicle and the stability of target tracking in a complex environment are smoothly improved.

1. Name of the product in this design: Unmanned Aerial Vehicle Countermeasure Equipment (Space-based D100). 2. Purpose of this design: This design is used to cut off the communication and navigation links of drones, forcing them to return to their home base or make an emergency landing, thereby achieving effective control over drones. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention relates to the technical field of engineering data analysis, in particular to a safety early warning method and system based on engineering project multi-source data, and the method mainly comprises the steps: obtaining the standard reaching rate of a current project based on the total completion degree of the project and the total completion degree of a target project; and based on the first early warning index and a judgment threshold value, outputting a result of sending out early warning at present, if the early warning result is not sent out, judging whether the current project completion degree is greater than or equal to the target project completion degree, and correcting the calculation weight of the first sub-project related to the first early warning model to obtain a second early warning model. Through the above method, the data collected in each sub-project is analyzed, and comprehensive consideration is carried out in combination with the condition of the current project progress, so that a more accurate reference result is obtained, and workers can use the reference result and take more accurate countermeasures.

The present application belongs to the field of unmanned aerial vehicle electromagnetic countermeasures, high-power microwave protection and electromagnetic compatibility reinforcement, and particularly relates to a high-power microwave protection method for unmanned aerial vehicle body, which realizes lightweight global shielding by arranging three layers of gradient frequency selective composite skin on the unmanned aerial vehicle body; micro plasma units are arranged on the body gap, and the whole machine cable is replaced by optical fiber to double block the back door microwave coupling; a reconfigurable antenna, two-stage series limiting and a neural network adaptive filtering three-level radio frequency decoupling link are built on the nose; four groups of broadband sensors are arranged on the body to realize microsecond-level electromagnetic threat perception grading; a flight control closed-loop self-healing regulation system containing a bionic optimization algorithm is constructed, which can dynamically adjust the protection power consumption and automatically redundantly reconstruct the fault. The present application can realize a shielding efficiency of the whole machine of greater than or equal to 40 dB under a 1~18GHz, 20kV / m high field intensity environment, and can balance lightweight, communication signal fidelity and long endurance, effectively avoiding problems such as gap resonance, device breakdown and communication interruption, and is suitable for fixed-wing, vertical take-off and landing low-altitude unmanned aerial vehicles.

The application discloses a low-altitude aircraft cooperative countermeasure method and device based on a large model, relates to the technical field of unmanned aerial vehicle defense, and comprises the following steps: firstly, fusing real-time observation data of multiple heterogeneous radars to generate a space situation map containing target dynamic information; secondly, identifying non-self threat targets and evaluating their threat levels by using an intelligent decision model; thirdly, planning an initial countermeasure task in combination with available countermeasure resources; fourthly, simulating and deducing the task and iteratively optimizing the task by using a digital twin platform to obtain a final countermeasure execution task; and finally, parsing the task into specific instructions and distributing the specific instructions to countermeasure resources to execute cooperative strikes. Through the above method, the full-process automation and intelligentization from situation awareness, intelligent decision to task execution are realized, and the rapid response capability and cooperative countermeasure efficiency of low-altitude aircraft threats are improved.

The embodiment of the application relates to the technical field of unmanned aerial vehicle countermeasure, and discloses a power amplifier and unmanned aerial vehicle countermeasure equipment, the power amplifier comprises at least one power amplifier unit, the power amplifier unit comprises a shell, a first air vent is formed in one side of the shell along a first direction, a handle is arranged on the other side of the shell along the first direction, a second air vent is formed in at least one side wall of the shell along a second direction, the first direction is perpendicular to the second direction, a plurality of radiating fins are arranged on the shell and extend from the first air vent to the second air vent, and a radiating air duct is formed between adjacent two radiating fins, the radiating air duct is used for air flow to pass through, so that the power amplifier unit is radiated. Through the above mode, the embodiment of the application realizes the effects that the power amplifier unit is easy to replace, the radiating is reliable, and the disassembly and assembly are safe.

The invention relates to the technical field of unmanned aerial vehicle autonomous control, and discloses a random game control method for unmanned aerial vehicle attitude control. The method comprises the following steps: constructing a cooperative control system comprising an attitude sensing unit and a game decision-making unit, collecting real-time motion parameters of an unmanned aerial vehicle, and monitoring environment confrontation behaviors; dynamically evaluating the motion parameters and the confrontation behaviors to generate a situation result, and formulating a confrontation strategy according to the situation result; activating a virtual countermeasure entity according to the strategy, wherein the entity simulates a real countermeasure behavior pattern and generates a countermeasure signal; establishing a distributed communication network formed by a plurality of relay nodes, and dynamically adjusting the transmission parameters of the relay nodes according to the characteristics of the adversarial signals; finally, a control instruction is transmitted through the adjusted relay node, and closed-loop control over the attitude of the unmanned aerial vehicle is achieved. According to the invention, by introducing virtual confrontation simulation and communication network dynamic optimization, the intelligent decision-making capability of the unmanned aerial vehicle in a complex confrontation environment and the robustness of a control system are improved.

An air-based counter-countermeasure (CCM) system includes an autonomous or semi-autonomous unmanned aircraft capable of deployment to an area of a countermeasure system having (1) a laser detector to receive and identify an incident laser signal as a target designator signal and (2) one or more countermeasure subsystems operative in response to an output of the laser detector to deploy corresponding countermeasures against a laser target designator. The CCM system further includes a laser-based CCM subsystem carried by the aircraft, the CCM subsystem being configured and operative, during the deployment of the aircraft, to direct a simulated target designator laser signal to the laser detector of the countermeasure system to trigger one or more of the countermeasures and thereby reduce protective ability of the countermeasure system against subsequent laser-guided attack.

The present application provides an aircraft which is more basic in configuration and which adopts a safety countermeasure. The aircraft of the present application has a main body portion, a thrust portion provided with one or more thrust units, a connecting portion which connects the main body portion and the thrust portion in a manner such that the connecting portion can be displaced within a prescribed range, and a wing portion provided to at least either the main body portion or the thrust portion. According to the configuration, an aircraft which is more basic in configuration and which adopts a safety countermeasure can be provided.

The invention provides an unmanned aerial vehicle countering decision control method based on multi-target identification distribution, relates to the technical field of unmanned aerial vehicle countering, and solves the limitation problems of low detection precision, unstable tracking, rigid task distribution and the like in the existing unmanned aerial vehicle countering technology. The method comprises the steps that firstly, an RF-DETR model is used for detecting and recognizing all target unmanned aerial vehicles invading a preset airspace, and initial parameters of targets are obtained; predicting and tracking a target trajectory by using a DeepSORT algorithm, generating dynamic labeling information with a unique ID for each target, and maintaining a tracking state; dynamic environment parameters are obtained, the threat degree of each target is corrected according to the dynamic environment parameters, and a countering task corresponding to each target is distributed to at least one countering unmanned aerial vehicle through an adaptive firefly algorithm; and according to the distribution result, applying a differential countering strategy to each target, and monitoring a countering effect in real time. According to the invention, efficient, rapid and highly intelligent unmanned aerial vehicle countering decision can be realized, and countering tasks can be assisted in real time.

The application relates to the technical field of unmanned aerial vehicle signal processing, and discloses an unmanned aerial vehicle signal intelligent detection and countermeasure method based on deep learning, which collects real-time data of unmanned aerial vehicle signals through a multi-source sensor, extracts and fuses features by using a convolutional neural network, and then classifies the signals through a generative adversarial network. A signal countermeasure model is constructed, an improved particle swarm algorithm is used to optimize the countermeasure strategy, and the interference effect and energy consumption are balanced. A hierarchical countermeasure control model is established, the decision layer is globally planned, the execution layer is locally interfered, and the feedback layer is real-time evaluated and adjusted. The method has high detection precision and signal recognition accuracy, can efficiently optimize the countermeasure strategy, realizes global and local collaborative countermeasures and real-time dynamic adjustment, has wide applicability and strong expandability, can effectively cope with various unmanned aerial vehicle security threats, and guarantees public safety, privacy and important regional order.

The present application relates to the technical field of low-altitude safety and unmanned aerial vehicle communication interference, and particularly relates to a method and system for sensing and controllable deception countermeasure of unmanned aerial vehicle communication protocol, which first acquires communication protocol signals between an unmanned aerial vehicle and a ground station, secondly pre-processes the acquired signals to obtain protocol frame data, then adopts a CNN-LSTM fusion deep learning model to analyze the protocol frame data, next forges legal control instructions according to the analysis result, then transmits the forged instructions to the unmanned aerial vehicle, finally acquires response signals of the unmanned aerial vehicle, dynamically adjusts instruction parameters and power parameters according to the response effect, forms a closed-loop feedback control, and until the unmanned aerial vehicle completes the return, hovering or landing operation as expected, so as to realize accurate sensing and controllable deception countermeasure of the unmanned aerial vehicle communication protocol.

To provide a production floor management system capable of improving determination accuracy of whether a work instruction is correct or not.SOLUTION: A production floor management system 1 is a system for managing a state on a production floor provided with a production device for producing a product, and includes a state monitoring unit 20 for monitoring the state on the production floor, and a control unit 10 for, on the basis of the priority of each of a plurality of measures extracted corresponding to the state, there are provided the measure determination unit 30 that determines a measure corresponding to the first priority instruction to be executed from among the plurality of measures, the instruction output unit 50 that outputs the first priority instruction, and the effect determination unit 60 that determines the effect of the executed first priority instruction based on the states before and after the output first priority instruction is executed, and the production resource for which the measure corresponding to the first priority instruction is being executed is locked.SELECTED DRAWING: Figure 2

The application discloses an unmanned aerial vehicle countermeasure interception system based on flight path prediction, relates to the technical field of low-altitude safety defense, acquires flight parameters of a target unmanned aerial vehicle, constructs a prediction model and generates a predicted path in combination with environment and terrain data, identifies a path segment most likely to enter a forbidden area, and calculates an expected intrusion time; candidate interception areas are screened based on a Hamilton-Jacobian inverse reachable set, and a multi-objective evolutionary algorithm is used to select an optimal interception node; in combination with a device response radius and preparation time, a starting time is determined, and an interception device is deployed; when the target enters an interception threshold range, a physical countermeasure action is triggered; the method realizes early identification, intelligent deployment and high-precision interception of the target unmanned aerial vehicle, improves the real-time performance and effectiveness of a low-altitude safety system, and has good engineering adaptability.

The application discloses a UAV directional early warning and management and control method and device, equipment and medium, and relates to UAV management and control technology, which comprises the following steps: determining target feature dimensions based on flight data and target airspace management and control rule data; determining an initial risk score according to each target feature dimension, converting the target feature dimensions, the trajectory sequence of the UAV and the target airspace management and control rule data into structured text, inputting the structured text into a target large language model for thought chain reasoning to obtain a target risk score, a confidence, an intention classification and reasoning basis; determining a final risk score based on the confidence, the initial risk score and the target risk score, and sending directional early warning information according to the risk level determined based on the final risk score, so that the UAV actively evacuates; generating alarm information of the UAV that does not actively evacuate, so that management and control personnel perform directional management and control on the UAV based on the alarm information, the intention classification and the reasoning basis. The problem of serious waste of countermeasure resources is solved.

This invention discloses an AI-based large-scale model-based drone countermeasure system and method, including the following steps: detecting suspicious targets by monitoring the airspace with millimeter-wave radar; identifying and locating suspicious targets using a visual detection device, collecting signal information of suspicious targets using an radio frequency module, and collecting noise information of suspicious targets using an acoustic sensor; determining whether the suspicious target is a drone based on the image information identified by the visual detection device, the signal information collected by the radio frequency module, and the noise information collected by the acoustic sensor; if so, collecting the three-dimensional trajectory of the drone; obtaining the threat level of the drone based on the three-dimensional trajectory of the drone and the environmental information in which the drone is located; and taking corresponding countermeasures to counter the drone based on the threat level. By fusing four-dimensional data (radar, vision, radio frequency, and acoustic signature) and combining it with deep reasoning using an AI large-scale model, the ability to distinguish between disguised drones and jamming objects is significantly improved.

The invention relates to the technical field of remote scheduling, in particular to a remote scheduling method and system for roadbed and pavement construction equipment, and the method comprises the following steps: carrying out the division based on task units, recognizing an equipment track inflection point and an operation state conversion sudden change interval, analyzing the equipment operation direction consistency and operation state distribution, and evaluating the linkage task scheduling efficiency. And analyzing a stress distribution trend of the construction area, calibrating an abnormal level, identifying a corresponding number, and outputting an intelligent collaborative scheduling instruction set of the construction equipment. According to the method, by accurately extracting and analyzing the running track and the operation state of the equipment, the abnormal interval and the deviation area can be effectively recognized, resource allocation can be balanced, operation consistency can be improved, resource waste and low efficiency caused by improper task allocation can be avoided, risk level calibration of task units can be achieved, and the method is suitable for popularization and application. Potential problems are found in advance, effective countermeasures are taken, scheduling decision precision and flexibility are improved, and efficient and smooth execution of construction tasks is ensured.

The application discloses a kind of military airport runway tenacity analysis methods under air guidance confrontation, creates the military facilities tenacity analysis framework considering the uncertainty of "red and blue both sides attack and defense strategy-weapon confrontation result-facility physical damage-facility function loss-facility function recovery " five links.Equipment runway function is used as evaluation object, and three-stage tenacity analysis method of "evaluation-optimization-analysis" is proposed.In the "evaluation" stage, the expression form and transmission process of the uncertainty of the last four links of military facilities tenacity analysis framework are described after establishing function index evaluation model, and the first link of "optimization" stage is described;Establish attack and defense strategy optimization model to describe the first link of military facilities tenacity analysis framework;The equilibrium strategy result obtained by attack and defense strategy optimization model is input into function index evaluation model, and the tenacity analysis result that can directly, quantitatively and reliably represent the function loss and recovery of military facilities is obtained.

This invention discloses a multi-agent, multi-system cooperative detection method based on deep reinforcement learning for radar jamming countermeasures: Step 1, constructing a dynamic adversarial game model of aircraft swarms and jamming aircraft swarms in a jamming scenario; Step 2, treating the jamming aircraft swarm as the environment, and modeling the interaction process between multiple aircraft and the environment as a distributed partially observable Markov decision process; Step 3, using the HyPPO-MACAD multi-agent cooperative anti-jamming detection algorithm based on hybrid attention proximal policy optimization for training and decision-making to obtain a cooperative policy; the HyPPO-MACAD algorithm introduces a continuous-discrete hybrid branch in the policy network and an attention mechanism in the commentator network; Step 4, based on the trained cooperative policy, controlling the aircraft swarm to perform cooperative detection tasks. This invention can adapt to coupled decision-making tasks, perform intelligent anti-jamming and cooperative detection, reduce detection adhesion under irregular detection models, and improve anti-jamming capability and regional coverage efficiency.

The unmanned aerial vehicle countering gun with the foldable screen comprises a countering gun body, the screen and an elastic abutting assembly, a storage groove is formed in the side wall of the countering gun body, the head end of the screen is hinged to the head end of the storage groove, and the screen can be rotationally contained in the storage groove or rotated out of the storage groove. The elastic abutting fixing assembly is installed in the counter gun body, when the screen is rotationally contained in the storage groove, the abutting fixing assembly abuts against the first position of the screen to lock the screen in the first state, and when the screen is opened to be perpendicular to the counter gun body, the abutting fixing assembly abuts against the second position of the screen to lock the screen in the second state. According to the unmanned aerial vehicle counter gun with the foldable screen, the screen is of a foldable structure, and storage of the unmanned aerial vehicle counter gun and impact resistance of the screen are facilitated.

The present application relates to the technical field of power facility safety protection, in particular to a substation airspace safety perception countermeasure system and method based on SSD technology. The method comprises: scanning and monitoring airspace through a distributed low-altitude perception base station group; identifying target drones using an SSD target detection algorithm based on the scanning results of the monitored airspace; tracking the trajectory of the identified target drones and fusing the Kalman filter predicted drone trajectory with the radio frequency signal direction information to estimate the pilot position using a pilot positioning algorithm; threat assessment based on the pilot position and the drone trajectory; and guiding the portable countermeasure terminal to implement countermeasures according to the assessment results. The present application improves the protection accuracy of substation airspace in complex environments and enhances the automation level and response speed of protection.

The application discloses a substation low-altitude target monitoring method based on 5G-A integrated sensing technology, and relates to the technical field of integrated sensing and defense, which comprises the following steps: acquiring an electronic map of a substation and key equipment position information, and constructing a three-dimensional semantic map of the substation area; combining the kinematic characteristics of a unique low-altitude target continuous trajectory and the key equipment function semantic annotation in the three-dimensional semantic map of the substation area, performing behavior pattern recognition and intention understanding on the unique low-altitude target, and outputting a target type label, an intention label and a corresponding threat level; comparing the target type label, the intention label, the corresponding threat level and the unique low-altitude target continuous trajectory with an electronic fence, generating a graded alarm event and a countermeasure suggestion, and issuing a linkage instruction to a defense device and a linkage platform to trigger corresponding disposal actions. The application realizes accurate mapping from target behavior to threat intention by extracting kinematic characteristics and function semantic annotation, and improves the cognitive and predictive ability of hidden risks.

The invention discloses an omnibearing free controllable unmanned aerial vehicle Beidou countering terminal, and relates to the technical field of unmanned aerial vehicle countering. Comprising a fixing mechanism used for fixing the device in various environments, a first adjusting mechanism arranged on the fixing mechanism, a second adjusting mechanism arranged on the first adjusting mechanism, a signal processing carrier arranged on the second adjusting mechanism, and a radar detector and an interference transmitter which are fixedly arranged on the signal processing carrier. The device has the advantages that multi-environment stable installation is achieved through the fixing mechanism, the adaptability is high, the problem of posture deviation caused by an inclined fixing face is solved through the first adjusting mechanism, the height and angle are flexibly adjusted in combination with the second adjusting mechanism, and all the parts cooperate with one another; the radar detector and the interference transmitter are ensured to cover the detection and countering range in all directions, the countering precision and reliability are remarkably improved, and the airspace safety protection requirement in a complex scene is met.