6692 results about "Positioning system" patented technology

Locator systems are disclosed for locating buried utilities such as conduits, cables, pipes. or wires. The locator system may include image-capturing and position and orientation measuring devices such as magnetic compass, accelerometers, gyros, GPS, and DGPS. The system may associate images captured during the locate process with buried utility position data and the other sensor data. These data and images may be further associated with terrain images from satellites or aerial photography to provide a highly precision map and database of buried utility locations and visual images of the burial site. Information so obtained may be transferred to a hand-held personal communication device, such as a smart phone to show the location of buried utilities in combination with photo-images and / or terrain maps.

Systems, methods, and instrumentalities are described herein for supporting low power high accuracy positioning (LPHAP). A wireless transmit / receive unit (WTRU) may receive configuration information (e.g., in a radio resource control (RRC) reconfiguration message) from a first cell. The configuration information may indicate a first sounding reference for positioning (SRSp) configuration and a second SRSp configuration. The first SRSp configuration may be associated with a first positioning area and the second SRSp configuration may be associated with a second positioning area. The first positioning area may include a first cell ID set and the second positioning area may include a second cell ID set. The first SRSp configuration may be activated and the second SRSp configuration may be deactivated.

The invention relates to the technical field of fault positioning, and is used for solving the problem that a fault event positioning system in the prior art has limitation and cannot adapt to dynamic changes. The invention provides a fault event positioning method based on topological model tracking analysis. The method comprises the following steps: S1, constructing a topological model based on system information and setting an edge weight; s2, tracking a fault propagation path by using time sequence data, and updating a path weight; s3, a fault propagation path is optimized through a shortest path algorithm, the shortest path algorithm adopts an A * algorithm, and a fault source is verified in combination with machine learning; and S4, outputting fault source nodes, related path information and confidence evaluation. The method is suitable for various complex network systems, is high in universality and expansibility, can adapt to the dynamic change of the topological structure and the running state of the system by dynamically updating the edge weight of the topological model, tracking the path and the machine learning model in real time, and always maintains high positioning accuracy and efficiency.

The invention relates to the technical field of building reconnaissance, in particular to a high-precision reconnaissance lofting intelligent positioning system and method based on multi-source data fusion, and the system comprises a data collection module, a fusion processing module, an intelligent positioning calculation module, a lofting path generation module, a wireless communication module and a visual terminal module. The data acquisition module synchronously acquires multi-source data; the data fusion processing module carries out space-time alignment and feature level fusion and detects the state of the sensor; the intelligent positioning resolving module outputs three-dimensional coordinates by adopting various algorithms; the lofting path generation module generates an optimized path according to the BIM model; the wireless communication module realizes high-speed data transmission and equipment communication; the visual terminal module provides a visual interaction interface. Multi-source data fusion is utilized, the positioning precision is improved, the reliability of the system is guaranteed through sensor failure detection, the system adapts to the complex environment, the lofting path is optimized, the overall performance of the system is enhanced, and an efficient and accurate solution is provided for building investigation lofting.

The invention discloses an electrical equipment fault monitoring and positioning system based on data analysis, and relates to the technical field of electrical equipment monitoring. The problem that in the prior art, the comprehensiveness of data processing, the intelligence of fault detection, the accuracy of fault positioning and the like are insufficient is solved. According to the method, the sensor acquisition frequency is dynamically adjusted according to the equipment operation state, the effectiveness and pertinence of data are ensured, the accuracy and reliability of fault feature extraction are improved by combining time domain and frequency domain analysis with network model training, the known fault type is quickly and accurately judged by calculating the similarity and performing partition positioning, and the fault diagnosis accuracy is improved. Meanwhile, unknown fault features are analyzed and predicted, determined unknown fault information is updated to a database, fault types, equipment topological structures and structural information are combined, fault propagation paths and influence ranges are simulated, fault position ranges are determined, evaluation optimization is carried out, accurate information is provided for fault maintenance, and the fault maintenance efficiency is improved. And the equipment maintenance cost and the downtime are reduced.

The invention relates to the technical field of power system fault diagnosis, and discloses a power distribution network fault identification and positioning system based on a wide area measurement technology, and the system comprises a key measurement point optimization configuration module which determines the arrangement position of an optimal measurement point, and identifies a high-risk weak link in a power distribution network; the virtual-real fusion measurement network construction module adopts a generative adversarial network to generate blind area virtual measurement data conforming to a physical rule, and fuses actual measurement data and the virtual measurement data; the active fault excitation implementation module is used for implementing safe and controllable tiny disturbance injection and actively detecting response characteristics of weak links; the state estimation enhanced fault positioning module is used for constructing a health state evaluation model and calculating the deviation between a transfer function and a health baseline; the toughness fault positioning execution module is used for extracting key information dimensions and ensuring the reliability of fault positioning; through a virtual-real fusion measurement technology, efficient monitoring of the whole area of the power distribution network is realized on the basis of limited actual measurement equipment.

The invention discloses an emergency communication and positioning system and method based on a Beidou satellite. The method comprises the following steps: S1, collecting data in real time; s2, analyzing the emergency state of the user by using a context awareness algorithm; s3, under the condition that the satellite communication signal is stable, transmitting the emergency information to a rescue center according to the calculated priority, if the satellite signal is unstable or interrupted, constructing a self-organizing network, and continuing to transmit the emergency information; s4, dynamically selecting an optimal path based on an adaptive path optimization algorithm inspired by an immune system, and further optimizing path selection through a space-time perception algorithm; s5, according to a priority management mechanism, the emergency information with high priority is processed preferentially, and feedback information is sent; s6, if the first emergency information transmission fails, the system starts a redundant data transmission mechanism; and S7, continuously tracking the state change of the user, and dynamically adjusting the rescue scheme. According to the invention, the situation awareness and immune system optimization algorithm is combined to realize efficient transmission and feedback of emergency information.

The invention discloses an ultra-wideband laser radar inertial navigation cooperative SLAM (Simultaneous Localization and Mapping) method and system, which are suitable for robot positioning and mapping tasks in a GPS (Global Positioning System)-free environment. According to the method, high-frequency motion priori of an IMU, relative pose constraint of LiDAR and absolute ranging information of UWB are fused, a unified factor graph optimization model is constructed, and multi-sensor cooperative positioning is realized; in the system initialization stage, IMU bias calibration, UWB base station coordinate configuration and LiDAR initial attitude estimation are completed; in the operation process, IMU pre-integration is utilized to predict the pose, LiDAR point cloud registration is utilized to obtain the relative motion between key frames, UWB ranging is combined to construct a residual item, a self-adaptive weight mechanism is introduced to suppress ranging abnormity, and the fusion robustness is improved; the system supports geometric feature loopback detection, cross-frame constraints are constructed in combination with UWB to carry out closed-loop optimization, and an optimization result is used for real-time incremental updating of a global map; the method has the advantages of high positioning precision, strong anti-interference capability, wide application scene and the like.

The invention relates to the technical field of software systems, and particularly discloses a vehicle matching and positioning system and method based on comprehensive characteristics of a vehicle and a container, and the system comprises a multi-mode perception and intelligent identification module, a dynamic task matching and scheduling optimization module, an intelligent decision and automatic execution module, and a user interaction and operation module. According to the system, the states of a container and a container truck are sensed in a fusion mode through multiple sensors, cross-modal data feature learning is carried out through a Transform-VIM self-attention mechanism, and high-precision container recognition in a complex environment is achieved; meanwhile, based on multi-dimensional feature matching and a Hungary optimization algorithm, a dynamic task matching mechanism is constructed, and it is ensured that the container trucks and the containers are in accurate butt joint; the system optimizes a scheduling strategy through reinforcement learning, dynamically adjusts an operation process, and is linked with automatic equipment, so that intelligent and efficient port container transportation management is finally realized, the risks of wrong loading, neglected loading and operation delay are effectively reduced, and the overall throughput and operation efficiency of a port are improved.

The invention discloses a traveling wave fault positioning system and method based on Beidou synchronization and intelligent filtering, and belongs to the technical field of power system fault detection. The system comprises a Beidou synchronization module used for acquiring a high-precision time service signal and realizing multi-terminal clock consistency; the traveling wave sampling module is used for synchronously collecting multi-point electric power signals and filtering the multi-point electric power signals; the wave head extraction module realizes wave head identification through a sliding window and dynamic threshold judgment; the time coding module constructs a time difference vector and maps a position relation in combination with a power grid topology; the fault positioning module estimates an initial position based on a nonlinear propagation model, and the intelligent filtering module carries out dynamic correction through state prediction and unscented Kalman filtering. The method realizes rapid and accurate positioning of fault points, has the advantages of high synchronization precision, strong anti-interference capability, small positioning error and the like, and is suitable for traveling wave fault positioning requirements in various electric power scenes.

The invention provides an unmanned aerial vehicle infrared target positioning system fusing multi-model Kalman filtering and deep learning, and relates to the technical field of unmanned aerial vehicle navigation and positioning. The main body system comprises a data acquisition module, a multi-source data fusion module, a feature extraction enhancement module, a dynamic model optimization module, a target state estimation module, a positioning calculation module and a flight decision planning module, and the data acquisition module is provided with a high-resolution infrared sensor and accurately captures target infrared radiation information; a high-definition vision camera and a high-precision laser radar are integrated at the same time, environment data are collected in an omnibearing mode, and the data collection module can collect the environment data according to the environment complexity and the real-time change of the target motion state by adopting a self-adaptive sampling strategy based on fuzzy logic, particle swarm optimization and a self-adaptive threshold value. And the sampling frequency and the resolution of the sensor are dynamically and intelligently adjusted.

The invention discloses an unmanned aerial vehicle positioning system and method based on multi-source position signal fusion, and relates to the technical field of unmanned aerial vehicle positioning, and the system comprises a plurality of positioning data collection units which are carried on an unmanned aerial vehicle, and each type is specially used for collecting positioning data of a single source; the positioning data processing unit is suitable for calculating a confidence coefficient value based on the attribute parameter of each positioning data, and determining a weight of each positioning data according to the confidence coefficient value; and the positioning data fusion unit is suitable for fusing all the positioning data by applying a fusion algorithm and combining the weights of the positioning data to generate fused positioning data. According to the system, the confidence of each source positioning data is evaluated in real time, and the fusion weight is dynamically optimized according to the confidence, so that the dynamic evaluation and optimal fusion of the multi-source positioning data are realized, and the positioning precision and reliability of the unmanned aerial vehicle in a complex environment are improved.

The invention discloses a long-distance communication optical cable fault automatic detection and positioning system and method, and the method comprises the steps: collecting optical signal data in an optical fiber link in real time through the deployment of a multi-optical fiber sensor or a distributed optical fiber sensing technology; denoising processing is carried out on the collected data, abnormal fluctuation is analyzed by applying a self-adaptive algorithm, and the type of a fault which is about to occur is identified; classifying the faults by using a machine learning classification algorithm; time domain reflection and wavelength multiplexing technologies are combined, a composite algorithm is adopted to accurately position a fault point, and path optimization and error correction are carried out through sensing node data comprehensive analysis; an environment compensation algorithm is introduced, influences of environment factors on the optical signals are analyzed in real time, and errors are eliminated; and based on a fault positioning and analysis result, an AI algorithm is adopted to evaluate a fault influence range, a repair scheme is automatically generated, and priorities are scheduled for repair.

The invention discloses a container wharf hazardous chemical transport vehicle intelligent tracking and positioning system comprising a data acquisition module used for acquiring vehicle positioning, driving behaviors and environment state data; the data fusion and time synchronization module is used for performing time alignment on the multi-source data; the behavior modeling and trajectory prediction module is used for extracting driving behavior characteristics and predicting a driving trajectory; the risk assessment and anomaly detection module is used for calculating an anomaly score and predicting a driving risk; the security strategy optimization module is used for constructing a zero-sum game security control model and optimizing speed limit, path and early warning strategies; the remote control and intelligent intervention module is used for executing remote speed regulation, emergency braking, path optimization and alarm pushing in the intelligent dispatching system; and the cloud monitoring and data analysis module is used for storing a track, an environment, a driving score and a safety strategy and predicting a long-term risk trend. According to the invention, based on intelligent game and multi-modal fusion, accurate tracking and safety management and control of the hazardous chemical substance transport vehicle are realized.

The embodiment of the invention discloses an intelligent surveying and mapping method and system based on AI and BIM fusion. The method comprises the steps that an unmanned aerial vehicle platform carrying a laser radar, an RGB camera and a positioning system is used for scanning ancient building cultural relics and surroundings in a multi-angle flight mode, point cloud data, multi-view image data and position and attitude data are synchronously collected, and the three are associated through timestamps; after the point cloud data and the multi-view image data are preprocessed, cross-modal registration is completed through feature matching and pose estimation in combination with the position and pose data, and a registration data set is obtained; semantic segmentation is carried out on the point cloud data and the image data in the registration data set, and semantic segmentation results are fused based on the incidence relation; classifying and aggregating the original point cloud components according to category labels, constructing a topological relation reasoning assembly relation, calling corresponding BIM template instantiation model components based on the assembly relation, and hooking a segmentation result to generate a semantic enhanced BIM model; and integrating the BIM model and the GIS base map to form a fusion model so as to plot the historic building cultural relics.

The present invention relates to the field of dam area deformation early warning technology, and proposes a dam area deformation early warning method and system based on a laser scanner, which includes the following steps: selecting a drone, equipping the drone with a laser scanner and a Beidou positioning system; planning the monitoring flight path of the drone, continuously emitting lasers and receiving reflected signals through the laser scanner, and using the Beidou positioning system to record the scanning position information of the laser scanner in real time to obtain original three-dimensional point cloud data; integrating the three-dimensional point cloud data obtained by multiple scans of the laser scanner into a unified coordinate system through a registration algorithm to obtain a three-dimensional model of the dam area; using a statistical method and a preset threshold to perform a data consistency check on the original deformation data set, screening out abnormal values ​​in the original deformation data set, and obtaining a deformation data set; identifying the deformation data set through a dam area deformation risk assessment model, obtaining a dam area deformation risk level, and taking corresponding early warning measures based on different dam area deformation risk levels. The present invention improves the accuracy of deformation data, realizes accurate judgment of deformation risk levels, and takes corresponding early warning measures according to different risk levels, thereby enhancing the safety of the dam area.

The invention relates to the technical field of fault positioning, in particular to a power wire fault positioning system based on the Internet of Things, which comprises a data collection module, a fault analysis module and a data visualization module, firstly, a data collection module obtains wire data collected by a sensor on a wire in real time; secondly, the fault analysis module is used for carrying out data processing on the wire data to obtain fault data; according to the conductor data and the fault data, constructing a power conductor digital twinborn model; analyzing the fault features and the environmental parameters through a power conductor digital twinborn model to obtain an output result; analyzing the output result through a topology detection algorithm and signal sensitivity adjustment to obtain an optimized output result; obtaining a space-time propagation process formula of the fault signal through signal propagation simulation and space-time analysis according to the output result; evaluating the accuracy of an output result according to a space-time propagation process formula of the fault signal; and finally, the data visualization module generates a visualization chart and an analysis report.

The invention provides a spatial heterogeneous visual positioning system of a tomato picking robot, and relates to the field of deep learning, and the spatial heterogeneous visual positioning system comprises the following steps: S1, calibrating the positioning of the tomato picking robot; s2, acquiring a tomato image in a non-closed environment through a fixed camera; step S3, obtaining fruit space coordinate information under the field of view of the fixed camera; s4, judging the reachable space of the picking mechanical arm, and moving the picking mechanical arm; s5, carrying out secondary spatial information perception on the target by adopting a palm center camera, and further obtaining spatial coordinate information in a relatively closed environment; s6, performing approximate ball fitting to obtain an optimal picking object; and S7, tomato number judgment and picking pose estimation are carried out. According to the system, the fixed camera and the palm center camera are combined, the characteristics of tomato growth can be effectively handled, the positioning precision and the real-time performance are improved, the higher picking success rate and efficiency are achieved, and damage occurring in the picking process is avoided.

The invention belongs to the technical field of circuit boards, and discloses a composite pressing process of a high multilayer rigid-flex circuit board, which comprises the following steps: performing microstructure processing on the surface of a rigid base material to form a three-dimensional reinforced interface, and performing chemical grafting modification treatment on a flexible base material to generate a multilayer pretreated substrate; identifying the positioning mark of each layer of substrate through an optical positioning system, establishing a lamination stress prediction model in combination with the thermodynamic parameters of the material, and outputting a lamination configuration scheme containing an interlayer matching relationship; placing the configured laminated structure in a multi-temperature-zone press, and executing a three-stage gradient heating and pressurizing program to realize interface fusion between adjacent layers of substrates; monitoring an interlayer deformation difference value of the substrate in real time through a sensing network, and eliminating the deformation difference to obtain a press-fit molded circuit substrate; through heterogeneous interface strengthening design, multi-physical field cooperative pressing and real-time deformation compensation, accurate interface fusion and low-warpage forming of the high-multilayer rigid-flex circuit board are realized.

The invention discloses an autonomous collision avoidance method and system for an unmanned ship in a mixed traffic mode, and the method comprises the following steps: obtaining the current position coordinate information, course information and surrounding environment information of the unmanned ship in real time through a ship positioning system and a ship recognition system on the unmanned ship; combining the target point, constructing a path plan and calculating the energy consumption of a navigation path, selecting a first navigation path, identifying and classifying static obstacles and dynamic obstacles, monitoring the static obstacles in real time, calculating and evaluating a detour difference, adjusting the path according to a collision avoidance rule, and generating a second navigation path; predicting the movement direction of the surrounding dynamic obstacles, and judging whether a collision risk exists or not; predicting a future position and adjusting the course to generate a third navigation path; and respectively evaluating the electric quantity threshold, the energy consumption threshold, the battery electric quantity and the energy consumption value, and adjusting an energy use strategy in real time. According to the invention, the accuracy of the navigation path is improved, and the safety of the unmanned ship in a complex environment is improved.

A joint simulation and operation operability evaluation method based on wind power operation and maintenance ship motion dynamic response and active compensation gangway ladder motion control comprises the steps that an operation and maintenance ship frequency domain seakeeping model is built, and a hydrodynamic coefficient library is calculated; wave exciting force is reconstructed based on a Cummins time domain motion equation, and ship motion response prediction is realized by adopting implicit generalized alpha time domain composite integral; the dynamic positioning system extracts low-frequency motion through a Kalman filter and optimizes thruster thrust distribution to stabilize the position of the ship. A gangway ladder dynamic model is established based on a Lagrange equation, real-time control over displacement, speed and acceleration of the top end of the gangway ladder is achieved through a feedforward-feedback composite control strategy, and nonlinear output of a hydraulic actuator is optimized. And realizing joint simulation of the coupling system through time domain synchronization and self-adaptive PID (Proportion Integration Differentiation) control. And checking gangway ladder movement based on a preset threshold value and a space boundary condition, and evaluating the operability of the climbing operation. According to the method, the limitation of traditional single-disciplinary analysis is broken through, and the forecasting precision of wind power operation and maintenance operation operability is effectively improved.

The invention provides a rescue robot autonomous identification and positioning system and method based on industrial vision, and relates to the technical field of robots, and the system comprises a cooperative scanning module which is used for constructing a robot coordinate map; the data fusion module is used for establishing a data fusion frame with a unified time sequence to obtain multi-modal image data; the human body recognition module is used for mapping the thermal imaging image to a visible light image and executing human body local recognition to obtain human body structure features; the target marking module is used for determining a rescue target and marking the rescue target in the robot coordinate map; and the path planning module is used for performing path planning, constructing an updated path and performing rescue through the rescue robot. According to the method and the device, the technical problem of relatively low rescue efficiency caused by difficulty in accurately positioning the rescue target due to shielding and interference in a complex environment in the prior art can be solved, and the precision of positioning the rescue target is improved by combining industrial vision, so that the rescue efficiency is improved.

The invention relates to the technical field of electric heavy trucks, and discloses an electric heavy truck self-adaptive positioning method and system based on multi-sensor fusion, and the method is characterized in that a sensor data preprocessing module and a space-time synchronization module are constructed to carry out the preprocessing of data obtained by sensors; performing basic positioning on the electric heavy truck based on an Apriltag label positioning algorithm and a laser slam positioning algorithm; carrying out real-time positioning and correction on the electric heavy truck in a moving state by an Apriltag-assisted laser slam correction algorithm based on ESKF; the stability of a GPS signal in a current environment is automatically detected and analyzed through an adaptive controller module, a fuzzy control selector is adopted to adaptively switch a positioning mode according to a real-time condition, and an Apriltag auxiliary laser slam positioning algorithm based on an ESKF is designed according to the difference of different sensors carried by the electric heavy truck. And then considering the operation requirements of the electric heavy truck in complex environments such as unstable GPS signals in a mining area, designing an adaptive positioning system of the electric heavy truck so as to improve the positioning precision and robustness.

The invention relates to a substation operation risk identification method based on a multi-view video and high-precision positioning. Acquiring video data of a working site through a plurality of cameras with fixed visual angles and mobile video acquisition equipment; a high-precision positioning system is used for obtaining three-dimensional space coordinates of operators and equipment in real time; establishing a three-dimensional digital twinborn model of the substation equipment, and performing dynamic scene reconstruction based on the multi-view video stream to generate a real-time three-dimensional scene of the operation site; fusing the positioning data and the three-dimensional scene by adopting a space-time fusion algorithm to generate a dynamic digital portrait of the operator; and carrying out real-time analysis on behaviors and positions of operators by using a risk assessment algorithm based on a preset risk rule, calculating to obtain a risk assessment value, and setting a feedback mechanism to continuously optimize positioning and scene reconstruction precision. According to the invention, efficient, accurate and real-time identification and early warning of the operation risk of the transformer substation are realized, and the safety management level of an operation site is effectively improved.

Utility locators for providing information about hidden or buried pipes or other cavities are disclosed. A locator may be configured to provide positional information associated with the buried utility based on signals received from a line trace signal and a sonde signal and present the positional information on a visual display or other output device.

The invention discloses a container coating thickness online detection system and method, and the system comprises a non-contact thickness measurement unit which is used for transmitting modulation light to the surface of a container in real time according to the infrared light thermal modulation principle to excite a coating to generate a thermal wave signal, and determining the coating thickness through detecting the thermal wave reflection delay; the multi-mode executing mechanism is used for selecting a robot or a truss to carry the thickness measuring unit according to the specification of the container, and receiving a control instruction to drive the thickness measuring unit to move to a target detection point of the container according to a preset path; the three-dimensional positioning system is used for detecting the position deviation of the container entering the measuring station and feeding back the space coordinates of the container to the control system; and the control system is used for generating a motion path instruction according to the size of the container and a preset sampling rule, and receiving the coating thickness data of the thickness gauge in real time to generate a detection report, so that the precision, intelligence and high efficiency of container coating detection are realized.

The invention discloses a power transmission line abnormity early warning and fault positioning system, which belongs to the technical field of line detection, and specifically comprises the following steps: dividing early warning equipment in a line into sub-regions according to distribution through a region delimiting module; when a fault occurs, the region positioning module quickly marks the related sub-regions and equipment as undetermined states; the data acquisition module is used for collecting data of the to-be-determined equipment in a set time window before a fault, and preprocessing the data to judge whether the fault is caused by an electrical problem or not; if yes, collecting historical power consumption data of the to-be-determined area; the fault positioning module normalizes historical data, constructs a time sequence model, extracts a current value change sequence, divides the current value change sequence into a plurality of subsequences and then performs clustering analysis; judging the fault reason according to the offset condition of the category cluster where the undetermined current value change sequence is located in the clustering result; if the offset exceeds a preset threshold value, considering that the electric equipment is abnormal; otherwise, the aging of the line insulating material is caused.

The invention relates to the technical field of image analysis, in particular to a QFP chip image pyramid positioning system which comprises a pyramid construction module, a pin initial positioning module, a pin accurate positioning module and an interference area elimination module. According to the method, an original chip image is processed through step-by-step down-sampling and Gaussian filtering, the image processing speed is effectively improved when a multi-layer image pyramid is constructed, a pin connected domain is clearly identified by applying binarization processing and a pin neighbor connection strategy, the pin area identification capability of the system is enhanced, and the identification accuracy of the system is improved. Region recalibration is carried out by using an up-sampling image of an original image data size, accurate pin positioning can be executed while high resolution is maintained, the probability of wrong positioning is remarkably reduced by accurately extracting pin contour information and effectively eliminating non-target connected domains, the chip assembling quality is improved, the chip assembling speed is increased, and the chip assembling efficiency is improved. And remarkable benefits are brought to a high-speed electronic assembly line.

The invention provides a mine hole inspection unmanned aerial vehicle based on a laser radar and UWB distance measurement and a positioning system, and relates to the technical field of mine hole unmanned aerial vehicle inspection. Through the 360 laser radar and UWB distance measurement, the system can adapt to unmanned aerial vehicle positioning in the mine hole environment, so that the unmanned aerial vehicle can safely fly in the mine hole environment in which the light is dark and flying dust spreads due to the fact that the unmanned aerial vehicle is closed all the year round, the unmanned aerial vehicle is accurately positioned and lands in the preset hangar when necessary, the key problem that the unmanned aerial vehicle autonomously inspects in the mine hole is solved, and the unmanned aerial vehicle safety is improved. And the application scene of the unmanned aerial vehicle system under the inspection task is expanded. According to the invention, the position and attitude of the unmanned aerial vehicle under the launching inertial system are obtained through the laser radar for feedback control of the position and speed control module, and the distance between the unmanned aerial vehicle and the UWB base station is obtained to obtain the approximate position of the unmanned aerial vehicle in a mine and obtain the relative position relation with the hangar, so that the unmanned aerial vehicle can preliminarily position a landing point, and the unmanned aerial vehicle can be accurately located. And the subsequent unmanned aerial vehicle can be accurately positioned and landed in the preset hangar.

An antenna apparatus includes a magnetic field sonde and a satellite location system antenna node.