1939 results about "Satellite positioning" patented technology

The invention relates to the technical field of geometric quantity precision measurement based on satellite positioning, in particular to a pumped storage power station dam safety monitoring method based on Beidou positioning, and the method comprises the steps: arranging a Beidou monitoring station and base station array in a dam body and a slope region, synchronously receiving multi-band satellite signals, and carrying out the edge calculation processing; and the effective frequency band data are screened and fused by using a signal-to-noise ratio threshold to generate preprocessed observation data, and the preprocessed observation data are uploaded to a cloud server in real time through a 4G network and a Beidou short message dual-channel transmission link. A cloud server constructs a local enhanced network, ionosphere and troposphere errors are corrected by adopting a multi-base-station joint error modeling method, a closed-loop mechanism dynamically optimizes monitoring point distribution density, signal processing parameters and atmospheric refraction compensation coefficients, and data integrity is guaranteed in combination with a dual-channel redundancy check and interpolation completion technology. According to the invention, full-domain millimeter-level deformation dynamic monitoring of the dam under the complex terrain is realized, and the space-time reference uniformity, the data real-time performance and the structure safety evaluation precision are improved.

The invention relates to the technical field of satellite positioning navigation enhancement, in particular to a global ionosphere inversion method based on BP neural network fusion multi-source data, and the method comprises the steps: inverting STEC through ground-based GNSS observation data, then employing a projection function to project the STEC to a vertical direction of an ionosphere puncture point, and obtaining VTEC; a BP neural network and a Kriging interpolation method are utilized to fuse foundation observation data into an IRI-2016 ionosphere model to solve the problem that GNSS tracking stations are distributed unevenly in the world, so that the inversion precision of the ionosphere is improved, a spherical harmonic function is adopted to express VTEC space distribution, and then the ocean altimetry satellite observation data is utilized to achieve the purpose of solving the problem that the GNSS tracking stations are distributed unevenly in the world. According to the method, the problem of deficiency of ground-based GNSS observation data in an ocean area is solved by using ground-based GNSS observation data, DORIS observation data and COSMIC occultation data, a global ionosphere observation equation is established, a normal equation is constructed, and finally global ionosphere grid data VTEC is generated through Helmert variance estimation precise weighting calculation, so that the global ionosphere observation precision is improved.

The invention discloses a Doppler and pseudo-range fusion positioning method and system for low-orbit satellite conduction signals, and relates to satellite positioning. The method comprises the steps that a Doppler and pseudo-range observation equation is established; performing least square residual calculation on the calculated Doppler and pseudo-range theoretical values and the observed Doppler and pseudo-range measured values, and taking a grid center point coordinate corresponding to a two-norm minimum value as a receiver position initial value; performing Taylor series expansion on the Doppler and pseudo-range observation equation, and representing a state updating matrix by using the established state transition matrix and receiver position, clock error and frequency offset correction; the inverse matrix of the observation noise covariance is used as a weight matrix to be distributed to the state transition matrix; and iterating the initial position value of the receiver, updating the state updating matrix, and stopping iteration until the two-norm of the residual solution is smaller than a set threshold value, so as to obtain the position, clock error and frequency offset results of the receiver. According to the method, the low-orbit satellite positioning algorithm model can be optimized, the convergence time is shortened, and the positioning precision is improved.

The invention discloses a lineation robot control system based on a satellite positioning and orientation technology, which relates to the technical field of robot motion control and comprises a satellite positioning and orientation module, an inertial navigation module, a fusion positioning and orientation software module, a motor control software module, a motion control software module and a pattern planning software module. The satellite positioning and orientation module is used for acquiring latitude and longitude coordinates of the current position of the robot by receiving multi-frequency satellite signals; the inertial navigation module is used for collecting posture and motion data of the robot in real time through a gyroscope and an accelerometer. According to the lineation robot control system provided by the invention, through collaborative design of the multi-frequency-point GNSS receiver and the anti-multipath interference antenna array, centimeter-level continuous positioning capability in a complex urban environment is realized, and satellite signal reflection and shielding interference in scenes such as viaducts and avenues are effectively overcome; and satellite positioning and inertial navigation data are deeply fused through a tight coupling Kalman filtering algorithm.

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

The invention discloses a Beidou satellite positioning platform remote monitoring and scheduling system and method. The method comprises the following steps: S1, dividing a scheduling task of Beidou satellite positioning data into a first layer, a second layer and a third layer; s2, the first layer generates a preliminary scheduling scheme; s3, a second layer utilizes a graph neural network to process dependency and resource conflicts among tasks, and generates an optimized scheduling scheme in combination with a near-end strategy optimization algorithm based on strategy gradient; s4, the third layer adopts a global graph neural network model to process the global dependency relationship of the tasks, and generates an execution instruction of a global scheduling scheme in combination with a soft actor commentator algorithm; s5, modeling task information into a directed graph, propagating messages layer by layer through a graph neural network, and generating an optimal scheduling scheme; s6, setting a feedback mechanism between the layers; and S7, carrying out graphical display on the finally generated optimal scheduling scheme through a visual tool. According to the invention, accurate dynamic scheduling of Beidou satellite data is realized through hierarchical scheduling and graph neural network optimization.

A communication network may comprise a plurality of devices. Reference signals may be sent to a wireless device. Timing information associated with the reference signals may be measured and sent, by the wireless device, to a computing device. These measurements may be used for positioning of the wireless device.

The invention discloses a highway engineering road and bridge measurement method based on BIM, and belongs to the technical field of highway engineering measurement. According to the method, the problems that the modeling efficiency and accuracy are difficult to consider, the modeling precision of a non-important area is redundant and the like in the existing road and bridge measurement method for the highway engineering are solved. The method comprises the following steps: acquiring satellite positioning data by using a satellite positioning system in a measurement area, acquiring point cloud data by using laser scanning equipment, and acquiring road and bridge images by using image acquisition equipment; converting satellite positioning data into unified coordinate system data information, carrying out spatial registration on the unified coordinate system data information and the point cloud data, and dividing an important region and a non-important region; constructing a precise three-dimensional point cloud model for the important area, constructing a path point cloud model for the non-important area, and integrating road and bridge images; and finally fusing the model to obtain road and bridge parameters. The method can improve the model efficiency and reduce the model resource overhead while effectively improving the measurement precision, and is suitable for the measurement work of roads and bridges of highway engineering in various environments.

The embodiment of the invention discloses an agricultural vehicle positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the posture, position and speed of an agricultural vehicle under a geographic coordinate system according to inertial navigation data obtained by an inertial navigation system; establishing an initial observation equation according to a satellite observation equation corresponding to a global satellite positioning system and a visual observation equation corresponding to a visual sensor; when it is detected that satellite data collected by a global satellite positioning system is valid, the initial observation equation serves as a target observation equation; when it is detected that the satellite data collected by the global satellite positioning system is invalid, the initial observation equation with the satellite observation equations removed serves as a target observation equation; the current error state quantity of the inertial navigation system is corrected according to the target observation equation, and the attitude, position and speed of the agricultural vehicle are corrected according to the updated error state quantity, so that the actual positioning information of the agricultural vehicle is obtained, and the robustness of the positioning result of the agricultural vehicle is improved.

The invention belongs to the technical field of ocean detection, belongs to a multi-sensor fusion intelligent anti-collision method and system, comprises a sensing layer, a processing layer and an application layer, and provides an intelligent anti-collision and evidence recording ocean monitoring floating system integrating computer vision, target ranging, satellite positioning and ship automatic recognition system multi-sensor fusion. According to the invention, YOLOv8 target detection, Transform data fusion and a Kalman filtering algorithm are adopted, so that accurate detection and anti-collision early warning of ships and floating objects on the sea are realized. The system has an AIS failure processing mechanism and an evidence encryption storage function, and ensures reliable operation and data compliance under complex sea conditions.

According to the intelligent rolling construction method and system for the concrete face rockfill dam and the computer readable storage medium, self-adaptive adjustment of the rolling speed and frequency is achieved through three-dimensional digital elevation model generation, optimal rolling path planning, rolling parameter dynamic optimization model and real-time compaction degree prediction. The system integrates satellite positioning, BIM model verification, cloud data management and an abnormal protection mechanism, can correct path deviation in real time, generates a pressure supplementing instruction and stores construction data, provides an intelligent solution for high-precision and high-reliability rock-fill dam construction, and is suitable for popularization and application. The technical problems that in traditional rolling construction, manual experience is relied on, parameters are static, monitoring lags behind, and the rework rate is high can be solved.

The invention discloses a high-precision AI positioning method and system based on spatial multi-modal data fusion, and belongs to the technical field of fusion positioning, and the method specifically comprises the steps: collecting satellite positioning signals, inertial measurement data, visual images, laser radar point clouds, high-precision maps and other spatial multi-modal data; analyzing visual image illumination distribution, laser point cloud atmospheric particle density distribution and a satellite signal multipath reflection path to generate an environment physical attribute parameter set; inputting the original data of each modal into a correction function bound with environmental parameters, and outputting a standardized feature vector subjected to error compensation; and finally, inputting the recurrent neural network with space-time memory, and outputting the six-degree-of-freedom pose of the carrier by dynamically adjusting each modal feature fusion weight coefficient. According to the invention, through deep fusion of multi-modal data and environmental physical attributes, the problems of poor environmental adaptability and insufficient dynamic adjustment in the prior art are solved, and the precision and robustness of positioning in a complex scene are improved.

The invention discloses a construction engineering site safety monitoring and early warning system, which comprises a high-precision sensor network, an intelligent video monitoring system, a data processing and analysis center, an early warning and decision support platform, an early warning and decision support platform, a mobile terminal application, a satellite positioning and geographic information system GIS integration and an internet of things gateway and edge computing device, the high-precision sensor network is composed of various sensors deployed at key parts of a building structure, construction equipment, a temporary support system and the like, and is used for monitoring the stress state and the deformation condition of a structure body and the operation parameters and the environment information of the equipment in real time; the data is transmitted to a data processing center through a low-power-consumption and long-distance wireless communication technology; according to the invention, a high-precision sensor network is constructed, real-time and accurate monitoring of information in multiple aspects such as key parts, construction equipment and environment of a building structure is realized, the condition of a construction site is comprehensively and accurately mastered, and monitoring dead angles and information omission are effectively avoided.

The invention discloses an anti-counterfeiting traceability system and method based on Beidou satellite positioning and a block chain. The method comprises the following steps: generating a current positioning data tuple; performing validity judgment on the satellite signal quality index; generating current event summary information, performing encryption calculation on the event summary information by using a private key embedded in a commodity and improving a verifiable random function, and outputting a random seed and a verification proof; constructing an event fingerprint and generating an event signature by using a private key; a challenge request is generated when the commodity request state is migrated, the commodity end device responds to the challenge request and collects new Beidou positioning information, and a challenge response data packet is constructed; and performing consistency verification on the challenge response data packet according to the virtual state resume smart contract, writing the verified data into a geographic sub-chain, recording an event abstract hash path by a main chain, and updating a commodity state transfer path. According to the invention, based on Beidou positioning and an improved verifiable random function, the credible verification of the commodity position and the traceable management of the state are realized.

The invention discloses an ambiguity determination method for satellite positioning, a terminal and a medium in the field of satellite navigation and positioning, and the method comprises the steps: obtaining observation data of a base station and a mobile station, eliminating errors through employing a double-difference technology, and carrying out the cycle slip correction, and obtaining the corrected observation data; preliminarily estimating the speed and position of the mobile station; based on the corrected observation data, extracting an optimal ambiguity subset through satellite-level and ambiguity-level screening; constructing a factor graph model by using the optimal ambiguity subset, taking the preliminarily estimated speed and position of the mobile station as initial values, minimizing an error function in a factor graph, and optimizing to obtain a floating solution of ambiguity; obtaining an integer ambiguity solution based on the floating point solution; and verifying the stability of an ambiguity resolving result through consistency, and finally obtaining an ambiguity fixed solution. According to the method provided by the invention, high precision, high efficiency and high stability of ambiguity calculation are realized, and the method is suitable for a high-precision satellite positioning system in a complex environment.

The invention provides a Beidou intelligent early warning analysis method and system applied to a drainage basin-level reservoir dam group, and the method comprises the steps: obtaining a dam body deformation time sequence record and a corresponding hydrological environment time sequence record which are collected by a monitoring system of the drainage basin-level reservoir dam group through a Beidou satellite positioning terminal; dam body deformation response mode self-encoding processing is carried out on the associated time sequence data set, a deformation response feature element set representing the dam body structure state is generated, the deformation response feature element set is input into a pre-constructed basin reservoir dam group topological relation graph, abnormal state propagation calculation is carried out through the state dependency relation between graph nodes, and the abnormal state propagation calculation is carried out. And obtaining a chain risk transmission path set, performing risk evolution trend deduction on dam nodes in each path based on the chain risk transmission path set, generating a risk evolution index matrix, and generating a threatened risk identification sequence for key dam nodes. According to the method, the structuralization and response operability of the early warning information can be improved, and the scientificity and practicability of early warning analysis of the basin-level reservoir dam group are comprehensively improved.

The invention provides a driving fatigue monitoring auxiliary system based on Beidou satellite positioning and a multi-modal data fusion technology, which relates to the field of electric digital data processing and comprises a multi-modal information sensing and acquisition module, a data preprocessing and quality assurance module, a fatigue state recognition and evaluation module and an intelligent early warning and adaptive optimization module. The multi-modal information perception and acquisition module is responsible for acquiring driver states, driving behaviors and environment information in real time, and the data preprocessing and quality assurance module is responsible for performing space-time alignment, quality evaluation and feature standardization on multi-source data. The fatigue state recognition and evaluation module is responsible for fusing multi-dimensional features and judging fatigue levels and risk trends, and the intelligent early warning and self-adaptive optimization module is responsible for implementing hierarchical intervention and continuously optimizing system performance; according to the system, the accurate space-time reference provided by Beidou satellite positioning is utilized, effective fusion of multi-source heterogeneous data is realized, and the accuracy, the real-time performance and the individuation level of fatigue monitoring are remarkably improved.

The invention discloses an operator positioning method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a target positioning scene corresponding to an operator in a plurality of preset positioning scenes according to comparison between a visible satellite number and a satellite number threshold value, comparison between a signal-to-noise ratio of a visible satellite and a signal-to-noise ratio threshold value and comparison between reference signal receiving power and a reference signal receiving power threshold value; wherein the preset positioning scene at least comprises an outdoor open scene, an indoor scene, an outdoor shielded scene and a special operation scene; determining a target positioning mode matched with the target positioning scene in a plurality of preset positioning modes; wherein the preset positioning modes at least comprise Beidou satellite positioning, 5G positioning and Beidou satellite and 5G fusion positioning, and the calculation positioning mode assists the Beidou satellite and 5G fusion positioning; and positioning the operator through the target positioning mode, and determining a target positioning result of the operator. According to the scheme, the accuracy of positioning the operator can be improved.

The invention relates to the technical field of Internet of Things, and provides an obstacle avoidance method of an unmanned sweeper based on V2X communication and related equipment thereof. Space-time alignment and map initialization are carried out on satellite positioning information and real-time V2X communication data to obtain a reference electronic map, and rasterization fusion is carried out on the reference electronic map and laser radar point cloud data to obtain a dynamic obstacle probability map. Performing dynamic path planning on the dynamic obstacle probability map according to an A * algorithm to obtain an initial obstacle avoidance global path, and performing dynamic optimization on the initial obstacle avoidance global path according to real-time V2X communication data through a vehicle motion model to obtain a local optimization track; and performing motion analysis and instruction synthesis on the local optimization track through a differential driving model to obtain a driving control instruction. According to the invention, through multi-source information fusion, efficient probability mapping, double-layer path optimization and feedforward-feedback control compensation, the obstacle avoidance precision, the response speed and the driving smoothness in a complex dynamic environment are improved.

The invention discloses a pedestrian inertia / vision / satellite integrated navigation method based on a handheld terminal PDR. The pedestrian inertia / vision / satellite integrated navigation method comprises the following steps: calculating to obtain inertial navigation pose information based on strapdown inertial navigation; when the pedestrian is static, constructing an observation constraint of zero-speed motion for correction, and updating inertial navigation position information based on step length information when a new step is carried out; obtaining visual pose information of the pedestrian based on an inertia / visual fusion odometer, obtaining satellite position information of the pedestrian based on satellite positioning, and carrying out coordinate system alignment and step length coefficient correction factor estimation; a pedestrian multi-source factor graph optimization model with a handheld terminal PDR as a core is constructed, inertial navigation pose information and step length information are used as local state constraints, visual pose information and satellite position information are used as global state constraints, and a target optimization function is constructed to obtain a final pose of a pedestrian. The method is applied to the field of pedestrian navigation, has full-scene robust and continuous positioning capability, and can effectively realize high-precision navigation positioning under long endurance.

The invention provides a rice yield prediction method and system based on multi-source time sequence remote sensing data, and relates to the field of agricultural informatization and remote sensing technology application, and the method comprises the steps: collecting multi-spectral data and laser radar data, and carrying out the precise geographic positioning of the data through a high-precision satellite positioning system, obtaining multi-source unmanned aerial vehicle remote sensing data; performing camera internal orientation, wave band registration, orthoimage splicing and embedding, radiation correction and remote sensing index calculation on the multispectral data to obtain processed multispectral data; and performing point cloud reconstruction and point cloud filtering on the laser radar data, and calculating the height of the rice plant to obtain processed laser radar data. According to the method, multi-source remote sensing data and spatio-temporal data are fused, and remote sensing characteristics of different phenological periods of rice are dynamically analyzed and filtered, so that the precision and reliability of rice field yield prediction are remarkably improved.

Methods and devices for detecting a defect in a rail of a railway track, include at least two sensors selected from among magneto-acoustic and / or piezoelectric and / or magnetostrictive transducers; each sensor being associated with a timestamping circuit of a GNSS satellite positioning system; a measuring circuit for measuring, by way of the sensors, the acousto-elastic waves propagating in the rail, the wave or signal measurements being timestamped. Some developments describe notably active and passive modes; the use of train crossings; the emission of waves; the determination of the existence and then of the position and finally the characterization of the defect, where applicable; preferred placements for installing the sensors; the use of inter-correlation, passive inverse filter or correlation of coda of correlation methods; the use of mobile robots and / or drones; the use of artificial noise sources.

The invention belongs to the technical field of satellite positioning, and discloses an unmanned aerial vehicle positioning cruise method and system based on satellite-based enhancement, and the method comprises the steps: setting an unmanned aerial vehicle cruise region range, a high-coverage cruise route and flight time; and checking software and hardware equipment of the unmanned aerial vehicle, taking off from a safe area, and starting automatic cruise. Observation data, broadcast ephemeris and Beidou B2b and Galileo HAS products are obtained through an unmanned aerial vehicle receiver. Carrying out decoding and correction number matching on the B2b and the HAS messages; correcting the satellite orbit, the clock error and the code and phase deviation according to the correction number provided by the B2b and the HAS; performing gross error elimination, clock jump repair and cycle slip detection on the data; and performing parameter estimation by using Kalman filtering to obtain high-precision position coordinates. If an emergency occurs, an operator can send a return instruction to the unmanned aerial vehicle through a Beidou short message. And after the cruise task is finished or a return instruction is received, the unmanned aerial vehicle completes safe landing at the planned return point.

The invention discloses a high-precision real-time positioning system and method for positioning personnel based on multi-mode fusion. The system comprises a multi-source data acquisition module, an intelligent data processing module, a fusion positioning model construction module and a positioning result application module, provides visual monitoring, trajectory analysis and scene customization functions, and supports flexible expansion through modular design. According to the method, satellite positioning, Bluetooth beacon and inertial navigation technologies are integrated, the weight is dynamically adjusted in combination with an adaptive weighted fusion algorithm, and a fusion positioning model supports outdoor (satellite dominant + EKF calibration, the precision being 2-5 meters) and indoor (beacon dominant + fingerprint matching, the precision being lt); according to the invention, intelligent switching between three modes (inertial navigation + ZUPT correction) and signal loss (1 meter) is realized, data noise is optimized by using Kalman filtering, and high-precision real-time positioning in indoor and outdoor complex scenes is realized. According to the invention, the problems of insufficient precision, poor environmental adaptability and weak expansibility of a single positioning technology are solved, and the comprehensive performance of the positioning system is significantly improved.

The present application relates to an Informer-based autonomous satellite positioning accuracy prediction method and apparatus. The method includes: collecting satellite observation data of a train within a given operational section, there being an area where satellite signals are blocked within the given operational section, where the satellite observation data is satellite observation data collected by the train on the given operational section via a satellite positioning receiver; according to the satellite observation data on the given operational section, obtaining a prediction data set based on an effective value range of a preset three-dimensional position accuracy factor; and based on a preset accuracy prediction model, outputting an autonomous satellite positioning accuracy predictive value by taking the prediction data set as an input.

Generate ionospheric delay correction information for satellite positioning users with high precision for one cycle. 【Solution】Based on the output result of a total electron number prediction model that is trained to output a predicted value of the total electron number at a future time (e.g., one hour later) when data such as atmospheric environmental characteristics and solar altitude angle data are input, a correction parameter (a new correction parameter replacing the ionospheric correction parameter of the existing Klobuchar model) ECP for correcting the ionospheric error is generated using an electron density distribution model expanded over a wide area by a spherical harmonic function with the total electron number at the ionospheric penetration point of the received date and time calculated using observation data obtained from ranging signals of multiple frequencies (e.g., L1 wave and L2 wave).

The invention discloses a positioning method and device based on fusion of single Beidou navigation and a high-precision RTK technology, a medium and equipment in the technical field of satellite positioning. The positioning method comprises the following steps: determining single Beidou navigation information generated by a target receiver based on a single Beidou positioning device; extracting a pseudo-range observation value and a carrier phase observation value of the B1 / B2 frequency point; extracting a satellite number, epoch time, an ionosphere delay coefficient and a troposphere delay coefficient; determining delay deviation correction data of the Beidou satellite signal; total delay deviation in the signal transmission process is measured, and whether delay deviation correction is carried out or not is judged based on the dynamic delay threshold value model and the total delay deviation in the signal transmission process; and fusing the pseudo-range observation value of the receiver and the delay deviation correction data of the Beidou satellite signal, executing double-difference carrier phase calculation, and outputting a centimeter-level positioning result. According to the method, various transmission errors can be effectively eliminated, the positioning precision is remarkably improved, and the positioning continuity and stability are ensured.

The invention relates to the technical field of positioning, in particular to a rail-mounted robot high-precision fusion positioning method and system. According to the method, the error compensation model of each track segment is constructed, dynamic correction is carried out in combination with real-time environment interference data, dynamic compensation can be carried out on pulse data generated by an incremental encoder in real time, accumulation of position errors is remarkably reduced, it is ensured that the position of the robot is more accurate, and the accuracy of the robot is improved. By fusing satellite positioning data, motion state data and pulse data after error compensation, the positioning precision of the orbital robot in each orbital segment is remarkably improved, and by monitoring the position deviation in real time and comparing the position deviation with a preset threshold value, the unqualified orbital segments can be repeatedly corrected according to needs, so that the accuracy of the orbital robot is improved. And the accuracy of the positioning result is ensured, so that the robot can adaptively optimize the positioning precision under different working scenes and environment changes, and the continuity of high-precision positioning is ensured.

The invention discloses a high-precision positioning method based on combination of a Beidou satellite and 5G-Mesh, and relates to the technical field of satellite positioning, and the method comprises the steps: receiving a navigation signal of the Beidou satellite and a communication signal of a 5G-Mesh network in real time; the topological structure change of the 5G-Mesh network is monitored in real time, and the connection relation between the nodes is dynamically adjusted in combination with network performance indexes; the receiver performs pseudo-range measurement on the signals of the visible satellites; a navigation message is demodulated from the received satellite signal, and the accurate position of each satellite at the current moment is calculated by using a satellite orbit calculation model; constructing a signal intensity fingerprint database; outputting a reference position having the highest similarity with the current signal strength characteristic to carry out error modeling on the Beidou satellite signal and the 5G-Mesh network signal; and fusing the two kinds of position information by adopting a weighted fusion algorithm. By fusing the technical advantages of the two positioning technologies, the positioning precision and reliability are improved, and the requirement for high-precision positioning in a complex scene is met.

The invention discloses a Beidou satellite intelligent positioning and communication method and system based on artificial intelligence. The method comprises the following steps: S1, receiving a satellite signal and a cooperative signal; s2, processing the received satellite signal by using a pseudo-range measurement and carrier phase difference technology, and performing preliminary positioning calculation in combination with the cooperative positioning data; s3, fusion is carried out, and a multi-modal data set is constructed; s4, dynamically adjusting weights of different data sources in the multi-modal data set according to real-time environment change by utilizing a dynamic environment perception model based on a graph neural network; s5, processing the multi-modal data set by adopting a self-adaptive Monte Carlo variational inference algorithm, and optimizing the positioning precision; s6, adjusting a filtering parameter and a signal processing strategy in real time through a self-adaptive signal processing module; and S7, dynamically optimizing the communication frequency and path by using a dominant actor-commentator algorithm. According to the invention, multi-modal data fusion and a dynamic optimization algorithm are utilized, so that the precision and stability of Beidou satellite positioning and communication are remarkably improved.