4751 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.

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 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 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 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.

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

The invention relates to the technical field of pulsed ion beam processing, and discloses a positioning system for a pulsed ion beam processing optical element, which can accurately predict nonlinear structure deformation in a complex thermal environment and eliminate compensation deviation caused by a traditional linear model. A multi-sensor data fusion mechanism effectively suppresses the interference of local measurement noise on a control decision, and improves the reliability of a compensation strategy. And a closed-loop control system realizes real-time verification and dynamic optimization of the compensation effect, and machining precision reduction caused by error accumulation is avoided. The submicron executing mechanism ensures that the thermal drift compensation amount is accurately converted into platform pose adjustment, the high-precision optical element machining requirement is met, and the problem that a traditional positioning system is incomplete in model input due to the single temperature field information collection dimension is solved. Meanwhile, the dynamic characteristics of the temperature-displacement coupling relation are verified through high-precision displacement data.

The invention relates to the technical field of electrical equipment defect monitoring, in particular to a high-voltage equipment defect positioning system and method based on multi-modal image fusion, and the system comprises an ultraviolet triggering module, a modal synchronization module, a space positioning module, a structure recognition module and a fusion diagnosis module. According to the method, automatic calibration of a suspected defect area can be realized by performing quantitative threshold judgment on a corona discharge signal in an ultraviolet image, the consistency of three-mode data in space and time dimensions is ensured, and the accuracy of the defect area is improved by comparing three types of coordinates of a lead hot spot, boundary geometry and a spot center in the image and performing registration offset correction. The image feature alignment precision is improved, the insulator chain light spot distribution path is extracted, the continuous distribution length is calculated and corresponds to the pollution level standard, automatic identification of the pollution level is achieved, a multi-modal image fusion feature block is constructed, and a risk sorting label is given. And the defect positioning accuracy and the comprehensive evaluation capability on the defect property and the influence degree are effectively improved.

The invention discloses an unmanned aerial vehicle intelligent precise positioning system and method based on multi-source information fusion, and belongs to the technical field of unmanned aerial vehicle navigation positioning, and the system comprises a multi-sensor data collection module which is used for obtaining an original physical signal required by positioning; the data preprocessing and synchronizing module is used for processing original physical signals and ensuring the consistency of multi-source data; the feature extraction and semantic recognition module is used for extracting environment features and industrial equipment semantic information from original data and providing geometric and semantic constraints for positioning; the multi-source information fusion positioning module is used for fusing multi-source data and constructing a factor graph containing sensor error terms and semantic constraint factors; the positioning calculation and state estimation module is used for calculating the positioning pose of the unmanned aerial vehicle based on the fused data; according to the unmanned aerial vehicle intelligent accurate positioning system and method based on multi-source information fusion provided by the invention, by fusing multi-source information, the positioning problem in a complex industrial environment is solved, and accurate identification and positioning of target equipment are realized.

The invention provides a spatial heterogeneous vision positioning system and positioning method of a pineapple picking robot, relates to the technical field of picking robot positioning, and realizes high-precision spatial positioning and attitude estimation of the robot in a complex terrain environment by comprehensively utilizing multi-source information such as vision, inertial measurement, multispectrum and structured light. The positioning stability and the real-time performance are obviously improved; by embedding a multi-modal deep learning model, efficient non-destructive detection and intelligent classification of internal defects of pineapple fruits are realized, a mechanical arm is supported to dynamically adjust a picking strategy, fruits with better quality are preferentially selected for picking, and the picking quality and efficiency are improved; and meanwhile, the preset three-dimensional terrain model and the heuristic search algorithm are combined, the motion path of the robot is effectively planned, it is guaranteed that the robot safely and stably moves in the complex environment, and the mechanical damage risk is reduced.

The invention discloses a high-voltage cable operation state on-line monitoring, intelligent early warning and fault positioning system, particularly relates to the technical field of power equipment insulation monitoring, and is used for solving the problems that transient discharge signals generated in the cable insulation degradation process are difficult to effectively capture and accurate fault positioning cannot be realized in the prior art. The method comprises the following steps: collecting transient leakage current signals and traveling wave propagation characteristic parameters, performing phase correlation analysis on leakage current pulses and power frequency voltage to identify discharge types, and performing variational mode decomposition and Hilbert-Huang transform on the signals to respectively extract complexity characteristics and energy distribution characteristics; signal logic conflicts are judged by analyzing similarity and statistical distance among characteristics of a plurality of monitoring points, and collaborative diagnosis is started or traveling wave distance measurement is directly utilized to carry out insulation state evaluation and fault location. And finally, differential early warning levels are generated according to the diagnosis result, and fault line selection and positioning information is output to realize real-time monitoring, intelligent early warning and accurate positioning of the operation state of the high-voltage cable.

The invention discloses an intelligent identification and grading early warning method based on mine production abnormity, and a system and equipment thereof. The method comprises the following steps: obtaining space-time evolution data, earth surface deformation data and environment monitoring data of rock mass stress in a target area; performing abnormal mode detection on the data by using a space-time convolutional network to obtain accident risk probability distribution data; using an ultra wide band positioning system to track the movement track of the person entering the target area in real time to obtain the movement track data of the person; and constructing a three-dimensional early warning index system in combination with the accident risk probability distribution data in the target area and a dynamic early warning mechanism, performing dynamic early warning grading on different positions in the target area by using the three-dimensional early warning index system, and generating a grading response strategy matched with the personnel activity trajectory data. According to the invention, the problems of incapability of tracking a personnel movement track in real time and low timeliness of mine production abnormity early warning are solved.

The invention discloses a digital steel structure embedded part accurate positioning system, and belongs to the technical field of computer aided design and digital twinning, and the system comprises a data acquisition module which is used for obtaining a correction vector of a digital twinning model, the currently measured local positioning precision and the current global attitude consistency deviation; the model entropy calculation module is used for calculating a model authority entropy representing the accumulated deviation degree of the digital twin model based on the correction vector and a preset reference correction scale; the model authority calculation module is used for determining the model authority of the digital twin model according to the model authority entropy and a preset attenuation sensitivity coefficient; and the correction decision module is used for generating a correction acceptance probability in combination with the model authority and the local positioning precision, and performing probabilistic screening on the execution of the correction vector based on the correction acceptance probability, thereby providing a solid quantitative basis for subsequent judgment of the health condition of the model.

The invention provides an unmanned aerial vehicle inspection accurate positioning method and device integrating vision and satellite navigation, and relates to the technical field of aerospace information. According to the method, satellite signal quality features reflecting aerospace information reliability and multi-dimensional features such as visual geometric textures reflecting ground environment features are jointly extracted, and the environment state is deeply perceived; based on real-time dynamic generation of a fusion strategy adaptive to the current environment, a data weight and an algorithm model are intelligently adjusted, and the limitation of a traditional fixed parameter fusion mode is broken through; a specific inspection stage and a target object where the unmanned aerial vehicle is located are understood through visual identification, and a corresponding priori task constraint model is loaded, so that the positioning process closely meets the precision and safety requirements of actual operation. And finally, fusion calculation is carried out under the common guidance of a dynamic strategy and task constraints, so that the problem of inaccurate positioning of the unmanned aerial vehicle in a complex environment is solved, and the environmental adaptability, robustness and task guidance accuracy of a positioning system are improved.

The invention relates to the technical field of partial discharge of power equipment, and particularly discloses a multi-modal sensing-based partial discharge monitoring and positioning system for power equipment, and the system comprises a multi-modal sensing unit which is configured to be arranged around to-be-monitored power equipment and is used for synchronously collecting various physical signals generated by partial discharge, the multi-mode sensing unit at least comprises an ultrahigh frequency sensing array used for receiving ultrahigh frequency electromagnetic wave signals generated by partial discharge; the ultrasonic sensing array is used for receiving ultrasonic signals generated by partial discharge; and the data acquisition and synchronization unit is connected with the multi-mode sensing unit. According to the power equipment partial discharge monitoring and positioning system based on multi-modal sensing, an integrated framework of multi-modal sensing cooperation and high-precision time synchronization is constructed, so that the problems of insufficient multi-modal cooperation, low time synchronization precision and no closed-loop optimization mechanism in existing partial discharge monitoring are effectively solved.

Example implementations are directed to recapturing or realigning a room or scene in an artificial reality (XR) environment as a three dimensional (3D) space. To initially capture a room, a user manually annotates, using an XR system, one or more walls around the XR system. The XR system then aligns or localizes itself relative to the room. Once a room is captured and stored, and the user in the future enters the room again, the XR system may not be able to align itself in the room due to, for example, lighting conditions. Rather than require the user to manually recapture every wall captured during the initial room capture, the XR system can select one wall for recapture and, after receiving an annotation or marking of the one wall from the user, use the selection to realign the XR system relative to the room.

The invention discloses a rotating wheel nondestructive testing robot and a testing method thereof, and belongs to the technical field of specialized robots and nondestructive testing. The rotating wheel nondestructive testing robot comprises a permanent magnet adsorption walking mechanism, a multi-degree-of-freedom mechanical arm, a module flaw detection unit, a multi-sensor positioning system and a central controller; the adsorption walking mechanism is used for realizing all-attitude stable crawling on the curved surface of the rotating wheel; the multi-degree-of-freedom mechanical arm is arranged above the middle part of the permanent magnet adsorption walking mechanism and is used for moving the module flaw detection unit to a specified position; the module flaw detection unit is used for performing high-resolution detection on the damage of the composite material on the rotating wheel; the multi-sensor positioning system is used for real-time pose feedback of the robot; the central controller is used for controlling all the components to work cooperatively. According to the nondestructive detection robot for the runner and the detection method thereof, the problems that in the prior art, detection of internal cracks of turbine runner blades depends on a manual frame erecting mode, the high-altitude operation risk is large, the number of detection blind areas is large, and efficiency is low can be effectively solved.

The invention discloses a multi-base-station AOA cooperative low-altitude target rapid positioning system. The system comprises an AOA measurement base station network, an AOA data preprocessing module, an adaptive weighted intersection positioning module, an extended Kalman filtering state estimation module and a data fusion and system integration module. The system synchronously measures the arrival angle of a target signal through multiple base stations, removes noise in combination with smoothing filtering and an anomaly rejection algorithm, and then solves the initial position of a target by using a self-adaptive weighted intersection algorithm based on measurement quality and geometric distribution. And then, fusing the target motion model and the measurement model by adopting an extended Kalman filtering algorithm to realize dynamic estimation and prediction of the position, the speed and the course. The system can realize high-precision and real-time positioning and continuous tracking of targets such as low-altitude unmanned aerial vehicles, small aircrafts and the like in a complex electromagnetic environment and a sight distance limited scene, and has visual display and regional alarm functions.

The invention provides a photovoltaic power station assembly hot spot identification and positioning method and system, and relates to the technical field of photovoltaic power station detection.The method comprises the steps of image preprocessing, photovoltaic panel identification, hot spot identification, photovoltaic panel and hot spot assembly numbering and the like. According to the method, accurate detection of the photovoltaic panel is realized by combining temperature characteristics and shape characteristics, hot spots are judged and identified by using a brightness threshold value and a brightness difference value and near roundness screening, then positioning is completed through a row and column numbering rule, image quality is improved through multi-step preprocessing, and photovoltaic panel detection accuracy is improved by combining temperature and shape characteristics; multiple hot spot judgment modes and reflective screening are adopted, so that the hot spot recognition precision is enhanced; the hot spots are accurately positioned through scientific numbering rules, all modules of the system work cooperatively, hot spot recognition and positioning can be efficiently completed, a reliable basis is provided for photovoltaic power station maintenance, and high practical value is achieved.

The invention discloses a mining equipment positioning system and method based on radar, ultra wide band and inertial navigation, and the system is characterized in that a multi-source sensor unit, a data synchronization and collection module and a preprocessing module are connected in sequence, and a state fusion module is connected with the preprocessing module, a UWB ranging error compensation module, a radar motion estimation module and a pose output module; the upper computer is connected with the pose output module; the method comprises the steps of collecting multi-source data; timestamp alignment and format conversion processing are carried out, and feature and speed constraint information extraction is carried out on the point cloud data; fitting correction is carried out on the ranging data by adopting a weighted least square method, and position information is obtained through an error weighted average algorithm; feature matching is carried out, and in combination with a KISS-ICP point cloud registration method, a speed estimation result is obtained; carrying out data fusion, and obtaining a pose estimation result by adopting an extended Kalman filtering algorithm; and outputting equipment position and attitude information. According to the invention, high-precision real-time estimation of the attitude and position information of the mining equipment can be realized.

The invention discloses a big-data-oriented real-time analysis and fault positioning system, and the system comprises a data collection module which is used for collecting a multi-source data stream, and constructing a high-dimensional feature data set; the confrontation feature compression module is used for compressing high-dimensional features through multi-layer nested mapping and generating initial potential feature representation; the sparrow population module is used for constructing a sparrow individual population containing a plurality of hyper-parameter combinations; the feature evolution analysis module is used for deploying the optimized analysis confrontation model to a big data platform; the abnormal event detection module is used for carrying out sliding window analysis based on the change amplitude and the deviation trend of the potential characteristic track in the time sequence and judging whether a real-time abnormal event is formed or not; the historical alignment matching module is used for marking a specific time index and a source channel of fault occurrence; and the label identification module is used for completing fault type identification and fault type label output based on the fault occurrence time index and the source channel. According to the invention, an accurate big data real-time analysis and fault positioning scheme is provided for the user.

The invention relates to the technical field of underwater robots and high-precision positioning, and particularly discloses a high-precision positioning system for collaborative operation of an underwater robot cluster. The system comprises a multi-source fusion positioning base station network module, a cross-medium cooperative positioning engine module, a cluster relative positioning subsystem module, a dynamic environment perception compensation module, an elastic positioning fault-tolerant system module and a cooperative positioning decision center module. An absolute positioning reference is constructed through a multi-source fusion positioning reference station network, a cross-medium cooperative positioning engine is combined to realize accurate pose calculation, a cluster relative positioning subsystem is utilized to establish a dynamic topological relation between robots, an environment perception compensation and elastic fault-tolerant mechanism is introduced, and finally resource configuration is optimized through a cooperative decision center. The method solves the problem of high-precision positioning of robot cluster collaborative operation in a complex underwater environment, and can be widely applied to the fields of ocean exploration, underwater engineering and the like.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention discloses a combined navigation method and system of an unmanned surface vehicle. The method comprises the following steps: forming a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation System) integrated navigation system by using a GNSS (Global Navigation Satellite System) and a strapdown inertial navigation system (INS), and establishing a mathematical model of a GNSS / INS integrated navigation system filter; the mathematical model comprises a state equation and a measurement equation; establishing a mathematical model of the influence of the GNSS auxiliary information on the GNSS positioning precision so as to preliminarily adjust the measurement noise in the measurement equation; through an improved Sage-Husa adaptive filtering algorithm, adaptive estimation is carried out on the preliminarily adjusted measurement noise, and a measurement noise estimation final value is obtained; and according to the motion characteristics of the unmanned surface vehicle, adding motion constraint conditions to the measurement equation. The GNSS auxiliary information mathematical model based on multivariate function fitting is established, the influence of the external environment on the positioning precision is objectively reflected, the measurement noise in the filter is dynamically adjusted, and the positioning precision of the integrated navigation system under the interference condition is remarkably improved.

The invention relates to the technical field of image processing, in particular to an intelligent recognition and positioning system for battery support welding defects. Obtaining defect degrees and edge pixel points of the pixel points according to gradient features and neighborhood gray features of the pixel points in the welding image; obtaining change complexity according to the change characteristics of the local edges of the edge pixel points; edge sharpness is obtained according to the local gradient features and the gray level change features of the edge pixel points; obtaining local uniformity according to the local gray level distribution characteristics of the edge pixel points; obtaining a confidence coefficient according to the change complexity, the edge sharpness and the local uniformity; and obtaining an adjustment factor of the edge pixel point according to the confidence coefficient and the defect degree. The method comprises the following steps: adjusting a weighting coefficient in a high-lift filtering algorithm according to an adjustment factor to obtain a self-adaptive weighting coefficient; performing image enhancement and defect identification according to the adaptive weighting coefficient; and the accuracy of image enhancement and defect identification is improved.

The invention discloses an automatic hoisting and positioning system and method for prefabricated parts, and relates to the technical field of building construction. The system comprises a tower crane, a frequency conversion trolley, a three-axis pan-tilt stabilizer, a receiver positioning device and an infrared emitter which are coaxial, an intelligent terminal control system with a pre-stored BIM model, and an integrated inertial sensing unit and a dome camera monitoring system. The intelligent terminal generates target coordinates through the BIM positioning reference module, the real-time deviation calculation module quantifies three-dimensional positioning and axis perpendicularity deviation, and the compensation instruction generation module drives targeted adjustment; through combination of infrared dual-mode switching, frame line deviation correction and inertia swing dynamic suppression, precise positioning and obstacle avoidance cooperation is realized. According to the method, through the closed-loop process of benchmark setting, obstacle avoidance lifting, fine compensation and standard confirmation, it is guaranteed that the positioning deviation is not larger than 0.8 mm, the axis perpendicularity is not larger than 0.3 degree, and the inertia swing is not larger than 10 cm, the problems that traditional hoisting is poor in precision and large in inertia interference are solved, and the installation quality and the operation efficiency are improved.

The present disclosure is directed to a load positioning system, a partially-assembled bridge, and a process of assembling a bridge. The load positioning system includes a gantry extending over a structure of a partially-assembled bridge, the partially-assembled bridge at least partially extending over a physical feature, a load descent mechanism arranged and disposed to lower a load having a mass of at least 10 kg onto the structure, and a load location mechanism arranged and disposed to move the load from being laterally-proximal to a first location of the structure and laterally-distal to a second location of the structure to being laterally-distal from the first location of the structure and laterally-proximal to the second location of the structure. The load descent mechanism and the load location mechanism are physically supported by the gantry. The process of assembling a bridge includes using the load descent mechanism.

A navigation system and method are disclosed for operation in GPS-denied environments using quantum-inspired sensor fusion, dynamic virtual anchor points (VAPs), and predictive environmental modeling. The system represents multiple position hypothesis using wavefunction-like expansions and integrates VAP-based triangulation for drift correction. A predictive modeling module ingests solar, geomagnetic, and environmental data to proactively adjust sensor weighting. A cybersecurity module employs quantum-algebraic key generation and location-derived ephemeral keys to secure inter-device communication. The system includes an augmented reality (AR) interface to visualize and edit anchor references, and a neurofeedback module that adapts the AR interface based on real-time physiological signals from the user. The method further enables anchor optimization via AI-driven repositioning and supports low-power edge execution using approximate amplitude filtering. Additional modules may include fractal antennas, neuromorphic processors, and adaptive forecasting layers to maintain positional accuracy and user experience in subterranean, multi-floor, or magnetically complex environments.