63 results about "Combat unit" patented technology

The invention provides a real-time command and control strategy optimization method and device based on multi-agent reinforcement learning, equipment and a storage medium, and the method comprises the steps: deploying a pre-trained cooperative intention network on edge equipment of each combat unit, and coding local observation data and a historical sequence thereof into a low-dimensional local cooperative intention vector; replacing original high-dimensional data as inter-unit communication content; whether broadcasting is carried out or not is dynamically determined according to observation uncertainty and a channel state by combining a self-adaptive intention broadcasting mechanism, and communication resources are distributed according to needs; after each unit receives an adjacent collaborative intention vector, a lightweight space-time attention module in a pre-trained local strategy execution network carries out space weighting on adjacent intentions and fuses time features of own historical intentions, and a collaborative and consistent real-time command and control instruction is generated under the condition that global information convergence is not needed.

The invention discloses a multi-target killing chain optimization method and device based on combinatorial optimization, and the method comprises the steps: constructing a combat network according to the interaction relation between combat units, and determining an edge attribute as a combat index according to a network node parameter; according to the number of targets attacked in the current combat scene and the number of combat indexes required for optimization, whether a static killing chain or a dynamic killing chain is generated is judged; if the number of the attacking targets in the current combat scene is single, carrying out monocular single-index killing chain optimization, or carrying out monocular multi-index killing chain optimization to generate a static killing chain; and if the number of the combat targets in the current combat scene is multiple and the number of the combat indexes is multiple, performing multi-view and multi-index killing chain optimization by combining and optimizing different killing chain paths, and generating a dynamic killing chain. According to the invention, a commanding mechanism can be assisted to select a static killing chain or a dynamic killing chain which most meets requirements from a plurality of killing chains based on the four combat indexes.

The invention relates to the field of combat command and dispatch, in particular to a multistage linkage combat unit command and dispatch system. According to the invention, a basic-level minimum emergency unit element information base is constructed through a data acquisition module; generating an electronic map supporting 2D and 3D switching; an intelligent analysis early warning module identifies abnormal conditions and generates early warning information; a plurality of multi-level linkage combat unit topology networks are generated through the multi-level linkage command architecture module; generating a command data large screen for dynamically aggregating public security indexes and a global situation visualization electronic map through a global situation visualization module; an early warning area is circled and selected through the intelligent scheduling module; and associating the corresponding multi-stage linkage combat unit to generate a deployment instruction. According to the multi-level linkage combat unit command and dispatch system provided by the invention, the multi-level linkage combat unit is effectively combined with a dynamic visual geographical environment from data acquisition, analysis and early warning to command and dispatch through cooperation of multiple modules, so that the command and dispatch efficiency is remarkably improved.

The present application relates to the technical field of simulation system, specifically to a virtual battlefield scene simulation system and method thereof, the system comprises: terrain node identification module, combat unit control radius extraction module, terrain advantage area preliminary demarcation module, control force gradient evolution analysis module, advantage area boundary dynamic adjustment module.In the present application, through the joint screening based on elevation, visible penetration rate and surface roughness, the key nodes with cover and accessibility are accurately identified, the terrain selection accuracy is improved, the spatial distance between the advantage nodes and the combat units is calculated to realize the accurate association between the control range and the deployment, the isolated points are excluded by node clustering division, the complete control domain contour is constructed, the Laplace operator is introduced to calculate the control force change rate, the boundary is dynamically adjusted in response to the situation evolution, the spatial continuity and change logic of the control force expression are strengthened, and the scene adaptability and deduction accuracy in the simulation process are enhanced.

The invention discloses a tactical simulation confrontation training system based on digital twinning and VR. The tactical simulation confrontation training system comprises a digital twinning construction and synchronization module, a virtual reality interaction and presentation module, a tactical confrontation simulation and deduction module, a training process monitoring and data acquisition module and a training effect evaluation and intelligent redisk module. According to the invention, the digital twinborn body synchronously mapped with the real combat unit and the environment is constructed, and is deeply integrated with the immersive VR interaction environment, so that a highly vivid and panoramic immersive tactical training scene is provided for trainees, the system supports red and blue parties or multiple parties to carry out intelligent confrontation in a virtual-real combined dynamic environment, and the training efficiency is improved. The multi-dimensional training data is acquired in real time, and based on the data, the system can perform refined and quantitative objective evaluation and intelligent redisk on the tactical actions, decision-making processes and collaborative effects of individuals and teams, so that the authenticity of training, the intelligence of confrontation and the scientificity of evaluation are remarkably improved.

The invention relates to the technical field of combat evaluation, in particular to an AI-based unmanned combat evaluation method, which comprises the following steps of: based on an unmanned combat unit, analyzing a relationship between control signal triggering and attitude change, judging action lag characteristics, analyzing action errors under the influence of wind speed, electromagnetism and illumination, identifying a pairing relationship, and distinguishing abnormal actions. And determining a tactical behavior key path and a grading result. According to the method, layered structure judgment of the target task is realized through the proportion of the time interval to the action amplitude, the sensitivity of the unit action response and the dynamic corresponding relation between the target sorting and the response process, environment disturbance data and action error attribution are integrated, the recognition capability of the non-interference abnormal action is enhanced, and the recognition accuracy of the non-interference abnormal action is improved. Based on full-process distribution and path structure expression, high-value tactical nodes can be distinguished and graded, a quantitative basis is provided for credibility and structural hierarchy of unmanned combat behaviors in a complex scene, and finer and systematic evaluation and judgment are realized.

The invention relates to the technical field of simulation systems, in particular to a virtual battlefield scene simulation system and method, and the system comprises a terrain node recognition module, a combat unit control radius extraction module, a terrain dominant zone preliminary delimiting module, a control force gradient evolution analysis module, and a dominant zone boundary dynamic adjustment module. According to the method, through combined screening based on the elevation, the visual penetration rate and the surface roughness, key nodes with shielding and accessibility are accurately recognized, the terrain selection precision is improved, accurate association between the control range and deployment is achieved by calculating the spatial distance between the dominant nodes and the combat units, isolated points are excluded by means of node clustering division, and the control range and the deployment range are optimized. A control domain contour with a complete structure is constructed, a Laplacian operator is introduced to calculate a control force change rate, dynamic response situation evolution is performed to adjust a boundary, spatial continuity and change logic of control force expression are enhanced, and scene adaptability and deduction accuracy in a simulation process are enhanced.

A simulation system for dynamically constructing combat resources based on a multi-agent system includes a combat center server and a multi-agent system. The combat center server includes a command unit, a support unit, an analysis unit, and multiple combat units. The command unit issues simulated combat missions; the support unit generates combat support information, which is referred to as simulated combat information. The analysis unit generates simulated combat formation information based on the available combat resources of each combat unit. The simulated combat formation information includes combat agents and a combat command map. The multi-agent system includes agents corresponding to each combat unit. The multi-agent system accesses the corresponding agents based on the simulated combat formation information and establishes command relationships. This invention achieves efficient resource scheduling and management, enhancing the flexibility and reliability of the system.

The present invention provides a method for constructing a kill chain based on a simulation deduction based on the combination of virtual and real, which relates to the field of simulation technology, and comprises: S1: obtaining a combat mission, identifying and defining a target according to the requirements of the combat mission, and determining the type of the kill chain based on the combat mission; S2: collecting corresponding scene data for different combat domains, and constructing a three-dimensional digital virtual environment based on the scene data; S3: establishing a multi-dimensional physical model for various types of combat platforms, and rendering the multi-dimensional physical model in real time into a virtual environment to form a virtual combat unit, wherein the combat platform comprises a plurality of sensors; S4: collecting sensor data of each combat platform, fusing the sensor data, and generating a unified target situation map; S5: making a plan decision by using a decision algorithm according to the target situation map and a combat knowledge base, and generating a combat plan; S6: deducing and verifying the combat plan in a virtual environment, and evaluating and optimizing the combat plan by using an evaluation method, and obtaining an optimized combat plan; S7: converting the optimized combat plan into an executable instruction parameter set, and transmitting the instruction parameter set to each combat platform through a heterogeneous network to coordinate and dispatch combat; S8: forming a kill chain according to the process of steps S1-S7. The present invention provides a reliable kill chain construction method for different combat domains, which not only improves the flexibility and efficiency of operations, but also lays a solid foundation for the development of future combat fields.

The invention discloses an SD-MANET coverage optimization method based on an improved dung beetle optimization algorithm, and the method comprises the steps: taking combat soldiers, unmanned aerial vehicles and unmanned vehicles in a cooperative combat unit in a task area as combat nodes, taking the number of the combat nodes and a sensing radius as input, and taking the optimal deployment position of the cooperative combat unit as output; constructing an SD-MANET topology model based on a Boolean perception model in the task area; and improving a dung beetle optimization algorithm by combining Chebyshev chaotic mapping, an eagle optimization algorithm and adaptive t distribution variation, and optimizing the SD-MANET topology model by using the improved dung beetle optimization algorithm to obtain an optimal deployment position of the cooperative combat unit in the task area. According to the method, the convergence and the performance are improved while the algorithm complexity is not increased, and the efficient deployment of the active / unmanned cooperative combat unit in a complex battlefield environment and the initial deployment network coverage rate of the cooperative combat unit are ensured.

The invention discloses an end-to-end unmanned aerial vehicle target behavior detection system and method based on large kernel convolution. The system comprises a visual acquisition module, an embedded edge calculation module, a flight platform, an end-to-end decision link and a time sequence feature fusion module. According to the invention, the behavior detection task can be executed accurately and efficiently. Aiming at hidden dynamic behaviors (including reconnaissance, attack and escape) of an enemy combat unit in a complex battlefield environment, visible light-infrared multi-source data collaborative acquisition, multi-stage expansion convolution feature extraction, time sequence attention feature fusion and end-to-end decision link construction are carried out, so that the hidden dynamic behaviors of the enemy combat unit in the complex battlefield environment are obtained. Millisecond-level real-time detection, high-precision behavior recognition and threat evaluation of military targets are realized.

The invention provides a virtual collusion tactical intention analysis method and device, equipment and a storage medium, and the method comprises the steps: obtaining multi-modal battlefield intelligence, carrying out the feature alignment and fusion of information data of different modals through employing a cross-modal attention mechanism, mapping heterogeneous data to a unified semantic space, obtaining a unified feature vector of each combat entity, and carrying out the analysis of the virtual collusion tactical intention. Therefore, the problem of multi-source heterogeneous data splitting is solved. A dynamic battlefield map is constructed based on unified feature vectors, combat units and key facilities serve as nodes, tactical interaction relations serve as edges, the weights of the edges are dynamically calculated by a map attention mechanism according to node features, and self-adaptive modeling of the tactical cooperation relations between combat entities is achieved. And finally, inputting the dynamic battlefield map into a multilayer map attention network for message passing and feature aggregation to obtain node high-order representation fused with global associated information, performing classification prediction on enemy tactical intentions based on the high-order representation, generating tactical intention probability distribution, and realizing adaptive intention reasoning.

The invention discloses a C # architecture-based four-level data automatic identification and adaptation method, and relates to the technical field of wargame combat deduction, and the method comprises the following steps: during combat deduction, monitoring and recording the combat damage data access condition of each thread to a combat unit in real time, and constructing a thread access competition data analysis set; for the established analysis set, key indexes related to access competition loads are extracted, and the extracted thread access competition key indexes are deeply analyzed; according to the method, the thread competition risk is intelligently recognized through the machine learning model, competition hotspots can be accurately detected in a high-concurrency environment, and resource allocation is dynamically optimized. Particularly, self-adaptive adjustment is performed on the priority of the read-write lock based on a competition load prediction result, so that the query efficiency is improved in a low-competition environment, the update of war damage data is preferentially guaranteed in a high-competition environment, the problem of data lag is reduced, and the occurrence of unenemy unit or war damage superposition abnormity is prevented.

The utility model relates to an unmanned aerial vehicle double-launch throwing device which comprises a main body, the top of the main body is fixedly connected with a fixing ribbon, the fixing ribbon is used for fixing the throwing device and an unmanned aerial vehicle body, and two mounting mechanisms are symmetrically arranged at the bottom of the main body; a power module, a light sensation receiver and a mechanical lock catch are arranged in the main body, the light sensation receiver is used for receiving a light source signal sent by the unmanned aerial vehicle, and the light sensation receiver is electrically connected with the mechanical lock catch; one end of the mounting mechanism is movably connected with the side wall of the main body, the other end of the mounting mechanism is fixedly connected with a bolt, the bolt is inserted into the main body, and the bolt is detachably fixed with the mechanical lock catch. According to the invention, two grenades or self-made warheads can be continuously put in the air.

The present application relates to a kind of unfragmented fire extinguishing bomb, comprising: warhead, fire extinguishing combat unit, propelling device, window breaking device and control unit;Warhead and propelling device are located at the opposite ends of fire extinguishing combat unit, and propelling device is set apart from fire extinguishing combat unit;Window breaking device is installed at the end of warhead away from fire extinguishing combat unit;Control unit is arranged in warhead;Fire extinguishing combat unit includes: outer shell, inner shell arranged in outer shell, fire extinguishing agent release device arranged in inner shell;Outer shell is hollow regular cylinder, including: two symmetrically arranged outer shell parts, hinged structure and switch structure;Two outer shell parts are respectively connected with hinged structure, so that two outer shell parts are rotated with hinged structure;Two outer shell parts are respectively connected with switch structure, for controlling the opening and closing of two outer shell parts;Inner shell is hollow cylinder, and a plurality of through holes are arranged on the side wall of inner shell;Fire extinguishing agent release device uses compressed gas explosion type fire extinguishing device.

The invention discloses a formalized description method of a wireless communication scene and a related device. The method comprises the following steps: acquiring a wireless communication equipment configuration table; based on the combat scenario instruction, obtaining a target combat scenario from a preset combat scenario template library; distributing the wireless communication equipment in the wireless communication equipment configuration table to a basic combat unit of the target combat scenario, and establishing a communication sub-network to obtain a combat scenario communication model; configuring parameters for the communication subnet based on the network configuration instruction; configuring service parameters for the wireless communication equipment based on the service configuration instruction; configuring a channel model for each link in the communication subnet; and performing formalized description on parameters of the combat scenario communication model to obtain a scenario file. According to the application, the construction of the combat scene oriented to wireless communication can be completed, and the data are stored in a standardized manner according to a standard format, so that the reusability of the scene is realized, and the universality of the scene is improved.

The application discloses a protection device for inhibiting explosion incidental damage of an active interception combat unit, which comprises a barrier layer for bearing a detonation wave of the active interception combat unit, an H-shaped arc muscle structure arranged at the rear end of the barrier layer, a plurality of ceramic round-taip-shaped protection blocks connected between the barrier layer and a honeycomb plate and having a front end area greater than a rear end area, the height of the ceramic round-taip-shaped protection blocks being greater than the height of the H-shaped arc muscle structure, and the height and density of the ceramic round-taip-shaped protection blocks at the central position being greater than those at the peripheral position, so that ceramic cones can be formed under the action of pressure, the honeycomb plate for dispersing and absorbing impact force, a back plate for supporting the honeycomb plate and connecting an eight-shaped reinforced front end, a plurality of eight-shaped reinforced structures arranged in a central symmetry, the rear end of the eight-shaped reinforced structures being used for being connected with a vehicle body and being inclined outward, so that the front ends of the plurality of eight-shaped reinforced structures are broken laterally under the action of pressure. The application can reduce the tactical index of incidental damage to the loaded vehicle body.

The invention relates to a cooperative firepower attack intelligent decision-making system based on a CPS. The cooperative firepower attack intelligent decision-making system comprises an intelligent decision-making center, a fire control system, a weapon system, a situation awareness system, a combat command and control center, a combat data center, reconnaissance equipment and a real-time communication network. The situation awareness system is used for acquiring weapon and target information of a battlefield and transmitting the information to the intelligent decision center; the intelligent decision-making center fuses and processes information from all the systems to obtain a cooperative firepower strike decision-making scheme; the combat command control center is used for receiving the preliminary task decision and sending the final task decision to the intelligent decision center; the fire control system is used for receiving the attack decision task and controlling the weapon system to attack the target; the combat data center is used for providing data support; and the real-time communication network is used for realizing real-time information transmission. According to the method, the advantages of information-physical fusion of the decision making system are fully exerted, the cooperative firepower strike decision is optimized, and the overall firepower strike capability of the combat unit is improved.

The application provides a multi-target switching device, which comprises a target frame, a target plate, a driving mechanism and a base, the target frame comprises two power edges and two fixed edges; the target plate comprises an upper target plate and a lower target plate; one end of the first fixed edge is hinged to the base, and the other end is hinged to one end of the first power edge; the first fixed edge is arranged in a vertical state, can be tilted backward and fixed back; the second power edge is located in front of the first fixed edge, one end of the second power edge is connected to the driving mechanism and can rotate around the driving mechanism; the two ends of the second fixed edge are respectively hinged to the other ends of the two power edges; the upper target plate is fixedly connected to the second fixed edge, and the lower target plate is fixedly connected to the second power edge; when the two power edges are in a vertical state, the upper target plate and the lower target plate are located in the same plane; a shifting block is arranged on the second power edge. The application can independently realize random switching of the tactical posture of a combat unit and more realistically simulate the tactical action of the combat unit in actual combat.

The invention relates to the technical field of command and control information processing, in particular to a land battlefield combat power entity model building and using method and a medium, and the method mainly comprises the steps that model units are built according to composition, attributes and capacity of a combat power entity in the physical world, and the model units are built according to the attributes and capacity of the combat power entity in the physical world; comprising a single-platform combat power model, and the single-platform combat power model is established and matched with the model of a weapon system in the physical world; comprising the steps of grouping combat power models, and grouping a plurality of single-platform combat power models into a group to form a grouping relationship. According to the method, the combat platform and the weapon equipment are separated in the design, and flexible combination and matching between the combat platform and the weapon equipment are supported; the universal combat power entity modeling design supports combat entity modeling of combat unit and team levels.

The application provides a simplified particle swarm weapon target distribution method with priority, and belongs to the field of resource distribution. First, weapon and target information of a combat unit is acquired, and priority of the combat unit to a strike target is calculated. Then, a distribution method is selected according to the priority, if the priority is less than a threshold value, a simplified particle swarm method is adopted, if the priority is greater than the threshold value, weapon distribution is directly performed according to threat degrees of the strike targets in sequence. The application determines the priority of the strike target, so that the strike target with higher threat is preferentially distributed with the weapon, and the threat degree of the combat unit is reduced. The application adopts the simplified particle swarm algorithm, and the convergence time of the algorithm can be shortened, which is of great significance for efficient strike of targets in cooperative air combat.

The present invention relates to the technical field of target damage assessment, and in particular to a target damage assessment analysis and compilation system based on a large model. The system includes a combat target data cleaning module, a combat target feature fusion module, a target damage assessment model establishment module, and a target damage visualization compilation module. The system can obtain corresponding combat target geographic situation images through satellite reconnaissance and integrate the combat intelligence reports and combat instructions corresponding to the target combat units to obtain combat target text data; perform data standardization cleaning on the combat target geographic situation images and combat target text data to obtain combat target situation standard images and combat target standard text data; construct a corresponding target feature analysis large model and perform combat target drive analysis, and simultaneously perform target damage assessment analysis and target damage visualization compilation to generate combat target damage visualization compilation results. The present invention can improve the accuracy of joint combat target damage assessment.

The invention discloses a multi-anti-ship missile cooperative route planning method based on a particle swarm optimization algorithm, and the method comprises the steps: summarizing a multi-anti-ship missile cooperative route planning problem into a series of 1: 1 combat units, and carrying out the initialization definition of environment parameters; four-point constraints are provided for a series of 1: 1 combat units; aiming at the route planning of the multi-anti-ship missile, constructing a problem model of multi-anti-ship missile collaborative route planning by utilizing four-point constraint in combination with geometric knowledge and rules of the route planning of the anti-ship missile; based on the problem model and in combination with a particle swarm optimization algorithm, the multi-antiship missile collaborative route planning problem with a 1: 1 combat unit as a combat mode is solved; and outputting the collaborative route planning results of all the anti-ship missile 1: 1 combat units to a single standard coordinate system to obtain a complex multi-anti-ship missile collaborative route planning scheme. According to the technical scheme, the problem of complex multi-antiship missile collaborative route planning can be solved.

1. Name of the Design Product: Virtual Reality Ideological and Political Education Interactive Device (Combat Unit 20252). 2. Use of the Design Product: Used for ideological and political education interaction in a virtual reality environment. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photo that Best Illustrates the Design Key Points: Perspective view.

The present application belongs to the technical field of ammunition research, and particularly relates to a throwing type four-rotor range-extended grenade and a flight control method thereof. The grenade structure comprises a flight unit, a control unit and a combat unit. The flight unit is responsible for providing an additional driving force in the air after the grenade is thrown, so as to extend the throwing distance of the grenade. The control unit is used for triggering the flight unit after the grenade is thrown, controlling the flight process of the grenade and detonating the combat unit of the grenade. The combat unit is used for exerting the fighting force of the grenade. The range-extended grenade provided by the present application can obtain a certain initial speed or height directly after being thrown, without the need of a mother machine or a launching cylinder tool. The ground preparation time is not needed, the arrival time is significantly shortened, and the battlefield survival rate is greatly improved.

The invention discloses a method for determining a war game deduction strategy and a related product. In the scheme, a tactical target corresponding to current battlefield situation information is obtained; based on the tactical target, performing action space design on a plurality of combat units to obtain an action set corresponding to each combat unit, and based on the action set corresponding to each combat unit, determining a target action of each combat unit; the target action of each combat unit indicates an action corresponding to the current battlefield situation information in an action set corresponding to each combat unit; and obtaining a war game deduction strategy based on the target action of each combat unit. Compared with the problem of low precision of a war game deduction strategy generated by an intelligent decision-making method in the prior art, the method has obvious advantages.

The present invention relates to the field of digital twin technology, and specifically, to a digital twin-based electronic sand table command system. It includes: a combat unit for obtaining the physical status, real-time location of combat personnel, and real-time images of the enemy; a sand table unit for converting a DIS map into a three-dimensional map, and at the same time displaying and real-time updating the real-time location of the received combat unit and the real-time images of the enemy in the three-dimensional map, thereby generating the movement trajectory of the enemy; a command unit, according to the movement trajectory of the enemy, inputs task instructions in the three-dimensional map of the sand table unit and selects the combat personnel to execute the task, and transmits it to the combat unit. This system not only considers the detection accuracy of different cameras, but also improves the robustness of the model, thereby providing more accurate positioning results in complex environments, and can achieve efficient battlefield management and command, improving the combat efficiency and success rate.

A multi-agent reinforcement learning method for collaborative decision-making of multiple combat units includes the following steps: for the red-blue game confrontation scenario, a multi-agent reinforcement learning model is established to realize intelligent collaborative decision-making modeling for multiple combat units; the post-goal conversion method is used to increase the number of effective training samples to achieve the optimization convergence of the multi-agent reinforcement learning model; the reward function is constructed based on the team's global task reward and the specific action reward of each combat unit as feedback information; a variety of opponent strategies are generated according to different combat plans, and the multi-agent reinforcement learning model is trained through massive simulated game confrontation using the reward function. The present invention solves the problems existing in the prior art of low coordination of decision-making of multiple combat units in the red-blue game confrontation and difficulty in obtaining valuable training samples.

The invention discloses a tactical simulation deduction method based on heterogeneous computing power collaboration, and relates to the technical field of tactical simulation deduction, and the method comprises the following steps: constructing a simulation index structure used for distinguishing an initialized unit from a non-initialized unit, recognizing a newly-added combat unit in a simulation operation process, and carrying out the calculation of the newly-added combat unit; marking the newly added combat unit as a temporarily added combat unit based on the identification result; the method comprises the following steps: acquiring state change data and behavior instruction sequences in a plurality of continuous simulation frames on the basis of a marked temporarily-added combat unit, constructing a behavior event sequence matrix, calculating a behavior change quantity between frames by adopting a sliding window weighted summation algorithm, and establishing a short-time behavior change speed index on the behavior event sequence matrix. According to the method, the problem that the calculation power adaptation is not accurate when a combat unit is temporarily added is solved, the heterogeneous calculation power resource dynamic adjustment based on the behavior change speed is realized, and the simulation response efficiency and the time sequence precision are improved.

This application provides a knowledge graph-based method and system for battlefield situation semantic understanding. The method acquires multi-dimensional visual and electromagnetic wave data from the battlefield, extracts enemy equipment outlines and environmental occlusion features through distributed processing; optimizes the capture range of thermal radiation features using vegetation density, and identifies equipment types using an equipment database; integrates terrain, thermal radiation features, and equipment location to establish an entity relationship model and combat unit network; and finally, dynamically adjusts spatial weights based on equipment type feedback to establish an equipment-terrain adaptation relationship to optimize network semantic expression and output the understanding results. The technical solution provided in this application significantly improves the accuracy and semantic level of battlefield situation understanding through multi-source data fusion, environmentally adaptive optimization of feature extraction and equipment identification, and dynamic construction and optimization of the equipment-terrain association model, providing precise support for decision-making.