484 results about "Ionosphere" patented technology

The invention discloses a PPP-RTK time delay processing method and device in conversion from SSR to OSR, and relates to the technical field of global navigation satellite system positioning, and the method comprises the steps: converting orbit, clock error, ionosphere and troposphere delay SSR parameters provided by a server into OSR virtual observation values through geometric distance calculation and projection function mapping; based on a constant velocity model and a static random process, predicting a correction amount of a future moment, and correcting an OSR virtual observation value through state transition matrix compensation time delay; combining server side parameters and user side observation data, recursively generating an error covariance matrix, dynamically adjusting a state prediction weight, and obtaining covariance information through adaptive filtering optimization positioning calculation; and realizing ambiguity rapid fixation and centimeter-level positioning by using the corrected OSR observation value and covariance information. According to the method, real-time centimeter-level positioning in a high-delay scene is realized through a dynamic correction value prediction method and a recursive covariance estimation method.

The invention provides a GNSS virtual observation value generation method and system based on real-time precise point positioning, and belongs to the technical field of GNSS positioning, and the method comprises the steps: obtaining ephemeris clock error data and observation data received by a reference station in real time, filling a UCUD PPP observation equation, and solving a non-difference floating point solution of a to-be-estimated parameter of each parameter station; through UPD estimation, non-difference floating point solution ambiguity parameters recover the whole cycle characteristic, and a fixed solution STEC and a fixed solution ZTD are obtained; the STEC is locally fitted into a function about the position, and a regional non-difference ionosphere model is established; the ZTD is locally fitted into a function about the position, and a regional non-difference troposphere model is established; and generating a double-difference atmospheric delay between the main reference station and the virtual reference station based on the non-difference ionosphere model and the regional non-difference troposphere model to obtain a virtual observation value. According to the method, the reliability of GNSS signal atmospheric delay is effectively improved, so that the quality of a virtual observation value is improved.

The invention discloses a TEC space-time prediction method based on fusion of feature analysis and a self-attention mechanism, and the method comprises the steps: screening strong effective features through analyzing the correlation between TEC historical data and each feature parameter, calculating the attention weight between data points on each time sequence through employing a self-attention coding mechanism, and carrying out the weighted summation to obtain the attention output. In an ionosphere total electron content prediction task, firstly, for sun and geomagnetic activity characteristic parameters, the correlation between each parameter and a TEC sequence in the same time period and a TEC sequence after a day interval is evaluated, strong correlation characteristics are screened, TEC sequences of adjacent grid points are used as characteristic quantities, multiple spatio-temporal characteristic matrixes of different time scales in a global range are established, and the total electron content of the ionosphere is predicted. And encoding the input feature information according to a self-attention encoding mechanism to obtain an attention output result, and decoding in a decoding layer through a linear model to obtain a TEC predicted value at a future moment. According to the method, efficient extraction of spatio-temporal information can be completed, and higher-precision prediction of the TEC is realized through a self-attention mechanism.

A user equipment (UE) may receive a set of reference signals (RSs) from a set of non-terrestrial network (NTN) nodes. The set of RSs may travel from the set of NTN nodes to the UE through a first portion of an atmosphere and a second portion of the atmosphere. The UE may measure the set of RSs. The UE may calculate, based on the measured set of RSs, a first set of atmospheric delays associated with the first portion of the atmosphere and a second set of atmospheric delays associated with the second portion of the atmosphere. The UE may calculate a location of the UE based on the measured set of RSs, the first set of atmospheric delays, and the second set of atmospheric delays. The UE may transmit the calculated location of the UE. The first portion may include an ionosphere. The second portion may include a troposphere.

The invention belongs to the technical field of time service, and relates to a Beidou time service delay processing method and device based on PPP-B2b. The method comprises the following steps: acquiring a navigation signal of a current epoch to obtain an observation value, a broadcast ephemeris and precise point positioning service information; obtaining a precision satellite position and a precision satellite clock error according to the broadcast ephemeris and the precision single-point positioning service information; forecasting to obtain a forecast value; calculating a difference value between the forecast value and the observation value, when the difference value does not exceed a preset threshold value, establishing a satellite pseudo-range and carrier phase ionosphere-free combination observation equation, establishing an antenna position constraint virtual observation equation, and performing resolving according to the combination observation equation and the virtual observation equation to obtain a receiver clock error result; and correcting the pulse per second according to a clock error result of the receiver so as to carry out delay time service. According to the invention, accurate time service can be realized, interference and environmental influence are avoided, and the convergence speed is high.

The invention relates to the technical field of satellite navigation and positioning, and discloses a Beidou precise point positioning method based on double-frequency combination, which comprises the following steps of: firstly, acquiring an original observation file and various correction files of a double-frequency signal from an IGS official website; a clean observation value is obtained through the steps of data validity checking and data preprocessing; carrying out correction and correction to obtain an error correction value; establishing a Beidou dual-frequency ionospheric elimination combination model, and performing dual-frequency DCB correction on the combination observation value to obtain a corrected dual-frequency combination observation value; constructing a double-frequency ionosphere elimination observation equation, and performing coordinate solution by using Kalman filtering to obtain a positioning result of double-frequency combination; analyzing the positioning result of the double-frequency combination, counting the error value of the positioning result, and evaluating the positioning precision and the convergence time; according to the invention, when DCB correction is considered, a dual-frequency ionosphere-eliminating PPP positioning model is established by using a BDS signal, so that the positioning precision can be remarkably improved, and the convergence time can be shortened.

The invention discloses an ionosphere total electron content-oriented multi-device system error correction method, which comprises the following steps of: acquiring a double-frequency observed quantity acquired by a GNSS (Global Navigation Satellite System) foundation observation station in a research area, solving an inclined total electron content STEC, and obtaining GNSS < VTEC >; the method comprises the following steps: reading an atmospheric density profile line acquired by a COSMIC satellite to obtain a COSMICVTEC, and carrying out integration processing on the data of the GNSS VTEC and the COSMICVTEC in a selected time period, and storing the data of the GNSS VTEC and the COSMICVTEC; through the processed COSMICVTEC, performing registration on the GNSS VTEC in a preset time range and a limited geographic position range, inputting the registered GNSS VTEC into a BP neural network for processing, and outputting a VTEC prediction difference value; and the COSMICVTEC is corrected according to the VTEC prediction difference value, so that corrected data can be obtained. According to the method, the observed quantity of the space-based COSMIC can be effectively and efficiently corrected.

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 provides a PPP-B2B-based positioning time service method, system and device and a readable storage medium, and relates to the technical field of information, and the method comprises the steps: receiving a PPP-B2b message and GNSS original observation data, extracting key features from the self-matched PPP-B2b message, and carrying out the learning and matching of the key features through a support vector machine; the satellite position and the satellite clock error are calculated by using the PPP-B2b orbit and the clock error correction data, an error model containing an error term is constructed, and the error model is optimized by using a nonlinear least square method; establishing a dual-frequency ionosphere-free combination model by using the calculated satellite position and satellite clock difference; and performing parameter estimation by adopting Kalman filtering to complete real-time positioning time service. Under the non-networking condition, single-station real-time high-precision positioning is achieved, and meanwhile synchronization of a local clock and a satellite system clock is achieved in a phase modulation mode.

The invention discloses a low ionosphere intelligent inversion method based on VLF radio wave detection, and the method comprises the steps: collecting ground-based very-low-frequency wave amplitude data, defining a gated cycle unit network objective function as an optimized performance index, and employing a mean square error as the objective function; and carrying out dynamic position updating by adopting a whale optimization algorithm, setting a double-stop criterion, and stopping iterative training to obtain an optimal model when the maximum number of iterations or a verification error convergence threshold value is reached. The calculation result of the LWPC model is used as a training set, the GRU network is used as an objective function estimator from foundation very low frequency data to low ionosphere parameters, the inversion method can accurately approach a real model, and the algorithm performance is effective and feasible and is remarkably improved compared with an existing model.

The invention relates to the technical field of meteorological monitoring and lightning protection, and discloses a radio signal-based lightning protection detection method for a meteorological station, which comprises the following steps of: receiving electromagnetic wave signals generated by lightning discharge in real time through radio receiving equipment of a plurality of meteorological stations, and acquiring characteristic data of time, frequency and intensity of the signals; an effective light velocity model is adopted to correct the influence of the propagation velocity of the lightning signal in the atmosphere, and the effective propagation velocity of the lightning signal is calculated by considering the ionospheric and atmospheric refraction effects; the position of the lightning power supply is estimated by measuring the arrival time difference and the time difference of lightning signals received by different sites and utilizing the geometric positions of the multiple sites. The positioning precision of the lightning power supply is greatly improved by adopting the cooperative work of the radio receiving equipment of a plurality of meteorological stations and combining the technologies of accurate lightning signal propagation speed correction, time synchronization error correction, geometric precision optimization and the like.

The invention discloses a functional basis ionosphere chromatography modeling method, which comprises the following steps of: acquiring longitude and latitude grid information of a research area, and calculating the electron content of a plasma layer at a preset height of a central point of each grid by utilizing an IRI-plas model. And fitting the data by adopting a third-order polynomial, and correcting the ionized layer delay observation value according to the data. Next, a non-ray penetration grid is identified based on GNSS data, a virtual ray is added, and an observation value thereof is calculated. And solving a model coefficient in combination with the corrected ionosphere delay and the virtual ray observation value, and constructing an initial ionosphere chromatography model based on the spherical harmonic function. And finally, calculating an ionosphere residual value, and performing residual correction on the initial model to obtain a corrected ionosphere chromatography model. The technical scheme of the invention has the advantages of high modeling precision and low calculation amount, and the corrected electron density value is closer to actual measurement data.

The embodiment of the invention discloses a precision positioning acceleration method and device based on a low earth orbit satellite / LSTM neural network. The method comprises the steps that a terminal obtains a wide lane phase decimal deviation product, a narrow lane phase decimal deviation product and a first GNSS combination observation value which are generated by a server based on an LSTM method and are subjected to coding processing; determining a first GNSS wide lane real number ambiguity according to the first GNSS wide lane real number Based on a precise point positioning algorithm, determining initial GNSS ionosphere elimination combination real ambiguity and other parameters; performing inter-satellite single difference on the first GNSS wide-lane real number ambiguity, and obtaining the integer ambiguity by combining wide-lane phase decimal deviation product fixation; performing inter-satellite single difference on the initial GNSS ionosphere-free combination real ambiguity, determining a first GNSS narrow-lane real ambiguity by combining the wide-lane integer ambiguity, and fixing the first GNSS narrow-lane real ambiguity by using a narrow-lane phase decimal deviation product through a partial ambiguity fixing method to obtain the integer ambiguity of the narrow-lane phase decimal deviation product; and calculating a user coordinate fixed solution in combination with related parameters.

The invention discloses a high-precision Beidou satellite navigation and positioning data acquisition method and system, particularly relates to the technical field of satellite navigation and positioning processing, and is used for solving the problem of positioning error increase caused by receiver hardware delay drift in the prior art. Inverting the first dynamic reference value by using carrier phase integral displacement, and extracting a third-order intermodulation component through coherent demodulation to generate a second dynamic reference value; adopting mutual information entropy analysis to select an effective reference value to calculate a residual error; fitting a theoretical value according to the carrier phase change rate to calculate deviation; marking a hardware drift error when the time domain correlation continuously exceeds a threshold value; finally, the ionosphere residual error is dynamically compensated to generate a corrected observation value, effective separation of the hardware drift error and the ionosphere residual error is realized, and the precision and reliability of long-time observation in a dynamic environment are improved.

The invention relates to a Beidou single-frequency double-ionosphere model weighted least square SPP positioning method. The method comprises the steps of capturing a visible satellite, calculating an ionosphere puncture point of the captured satellite, if grid point information around the puncture point meets the use requirement of ionosphere delay calculation, preferentially using a grid ionosphere model to calculate ionosphere delay, otherwise, using a broadcast ionosphere model to calculate, and calculating the weight of each satellite by using the proposed weight models respectively corresponding to the two ionosphere models, constructing a combined weight matrix, and substituting the combined weight matrix into a pseudo-range observation equation to carry out weighted least square solution. And updating the weight ratio coefficient of the double-ionosphere model by using the positioning calculation result, comparing whether the weight ratio coefficients before and after two adjacent updates meet a stop condition, and outputting a final positioning result when the stop condition is met. By adopting the method, the positioning precision can be improved.

The invention discloses a single base station PPP-RTK (point-to-point protocol-real-time kinematic) positioning method and equipment. The method comprises the following steps: firstly, according to acquired single base station observation data, single base station accurate coordinates and ephemeris data, satellite end error corrections and atmospheric delay corrections are respectively obtained based on different resolving models, and the satellite end error corrections comprise satellite clock error corrections and satellite orbit error corrections; the atmospheric delay correction number comprises an ionosphere delay correction number and a troposphere delay correction number of the first frequency; calculating an atmospheric delay difference between the single base station and the user based on an empirical model, and substituting the atmospheric delay difference into the atmospheric delay correction number to obtain an atmospheric delay correction number which can be used for the user; obtaining observation values of users to construct a PPP-RTK observation equation so as to eliminate error terms related to a single base station; and the satellite end error correction number and the atmospheric delay correction number are substituted into a user end PPP-RTK observation equation, so that single base station PPP-RTK positioning can be realized.

Method of measuring ionosphere scintillation phase index Sigma-Phi, the method including, for each of N satellites being tracked, calculating a phase prediction at an i-th sample; for each of the N satellites, calculating an individual loop discriminator signal based on the phase prediction; rejecting the i-th samples of some of the N satellites, where K non-rejected satellites remain; calculating common loop discriminator signal based on the individual loop discriminator signals of non-rejected K satellites; calculating a phase estimate and a Doppler frequency estimate at the i-th sample for each of the N satellites based on individual loop discriminator signal; calculating test statistic based on the phase estimate at the i-th sample and an observed phase for each of the N satellites; calculating index Sigma-Phi as standard deviation estimation of the test statistic for each of the N satellites; and outputting the index Sigma-Phi for each of the N satellites.

The invention provides an ionosphere TEC prediction model integrating double mechanisms of self-attention and self-correlation, and belongs to the technical field of ionosphere delay prediction, and the model comprises a trend prediction module, a correlation analysis module and a sequence fusion module. Wherein the trend prediction module predicts the overall change trends of an ionized layer TEC sequence and space environment parameters by means of an autocorrelation operation mechanism; the correlation analysis module analyzes the mutual relation among the ionized layer TEC sequence, the space environment parameters and the longitude and latitude positions by using a self-attention mechanism; and the sequence fusion module performs further integration and optimization on the overall trend of the ionized layer TEC sequence by using the correlation information obtained by the correlation analysis module, and finally obtains an ionized layer TEC prediction result fusing the space environment and the latitude and longitude position information. According to the method, the spatial environment data and the longitude and latitude position information are fully utilized, and the accuracy of model prediction is greatly improved.

The invention discloses a Beidou ground-based enhancement-oriented ionized layer weighted modeling method, which comprises the following steps of: proposing a weight function which takes an included angle between a connecting line from an interpolation point to a main reference station and each baseline as an independent variable according to the correlation of ionized layer delay of a to-be-interpolated point and a baseline and the characteristic related to the included angle between the to-be-interpolated point and the baseline; according to the correlation of ionosphere delay of a point to be interpolated and a baseline and the characteristic related to the distance ratio between the point to be interpolated and the baseline, proposing a weight function which takes the ratio of the distance from the interpolation point to a main reference station to the length of each baseline as an independent variable; the normalized ionosphere delay sample weight can be obtained by integrating the two weight functions, and the value of the point to be interpolated is obtained by using the weight according to the interpolation model of the BLUP framework. High interpolation precision can be achieved in each area in a large and medium-sized network with an active ionized layer, and the service quality of network RTK (Real-Time Kinematic) is improved.

The present invention proposes a real-time, high-concurrency, high-precision spatiotemporal service method that takes into account user behavior, and belongs to the field of navigation and positioning. Based on the dual-frequency pseudorange and carrier phase data of the domestic Beidou and low-orbit satellite ground-based reference stations, combined with the Beidou dual-frequency pseudorange and carrier phase observation data of the onboard low-orbit satellite, the present invention estimates the precise orbits, clock errors, clock speeds and clock drifts of Beidou and low-orbit satellites, as well as the spatial atmospheric delays of the regional ionosphere and troposphere, and establishes relevant models; classifies the resolved enhancement information, and establishes a high-precision spatiotemporal position enhancement information pool that integrates wide-area and regional areas; at the same time, by identifying user behavior or needs, the accuracy requirements of user applications and the types of enhancement information required are judged, and load balancing is used to achieve high-precision positioning services that match massive, multi-class users with high concurrency.

The invention belongs to the field of ionosphere satellite magnetic field seismic anomaly extraction, and particularly relates to a satellite magnetic field seismic anomaly extraction method based on complex non-negative matrix factorization, which comprises the steps of reading Swarm A satellite magnetic field data, and removing a main magnetic field of a ground core and a lithosphere magnetic field of an earth crust to obtain a residual magnetic field; performing short-time Fourier transform on the preprocessed data to obtain a complex time-frequency matrix in a rectangular coordinate representation form of a complex domain; decomposing the complex time-frequency matrix by using complex non-negative matrix decomposition to obtain R feature components; performing inverse short-time Fourier transform on each feature component to obtain a time domain feature component; a mean square root of a time domain seismic component of each orbit is calculated, a threshold value is set by using an over-limit rate method, and abnormal points are extracted from the seismic components of the orbits. The amplitude and phase information contained in the time-frequency domain of the satellite observation data is fully utilized, so that the component related to the earthquake is identified, and the earthquake anomaly extraction is more accurate and reliable.

The invention discloses a global ionosphere modeling method and device based on Beidou single-frequency ionosphere weighted PPP, and belongs to the technical field of GNSS navigation positioning and atmosphere modeling. The method comprises the following steps: acquiring real-time precise orbit and clock error information of a Beidou satellite and an initial ionospheric delay correction value; a single-frequency ionosphere weighted precision single point positioning (SF-IW-PPP) observation equation is constructed; establishing a space-time correlation constraint model of the ionized layer delay error and determining a prior variance; carrying out combined calculation by taking the previous variance as a constraint to obtain an ionosphere delay residual error, and further obtaining the total delay of the high-precision inclined ionosphere; and finally generating a global ionosphere grid model. According to the invention, high-precision and real-time global ionosphere modeling is realized by only needing a low-cost single-frequency receiver and combining Beidou real-time enhancement service, the hardware threshold and data processing delay are remarkably reduced, and the method is suitable for the fields of public navigation, intelligent transportation, space weather monitoring and the like.

The invention relates to the technical field of Beidou positioning, in particular to a Beidou virtual reference high-precision positioning method taking ionosphere delay influence into consideration. The invention provides a weighting method combined with ionosphere delay influence, which comprises the following steps of: constructing a physical check station, calculating double-difference ionosphere delay # imgabs0 # of the check station relative to a main reference station, and taking a calculation result as a double-difference ionosphere delay reference value; calculating to obtain a double-difference ionosphere delay reference value # imgabs1 # at the construction position of the check station obtained by interpolation of the virtual reference station, and taking the absolute value of the difference value of # imgabs2 # and # imgabs3 # as the ionosphere error of the satellite; compared with the prior art, on the basis of combining the precision of the elevation angle related prior observation value of the double-difference observation value and combining the ionosphere error of the satellite, gross errors caused by ionosphere anomalies can be weakened, and high-precision and reliable GNSS virtual reference calculation can be achieved when the ionosphere is active, disturbance occurs and the like.

The invention provides a correlation constraint-based positioning method, computer equipment and a storage medium, and the method comprises the steps: constructing constraint information based on electron content information and positioning observation information, and the positioning observation information is obtained through the signal collection of a target satellite by a first single observation station; according to the constraint information, a Kalman filter is constrained to obtain a resolving parameter of the Kalman filter, and the Kalman filter is used for estimating the ionosphere delay parameter based on the correlation between the receiver differential code deviation and the ionosphere delay parameter; and determining a first target ionosphere delay parameter of the first single observation station based on the resolving parameter, the first target ionosphere delay parameter being used for positioning. And the Kalman filter is constrained by using the constructed constraint information, so that high-precision ionosphere delay parameters can be obtained when parameter estimation is carried out based on resolving parameters in the constrained Kalman filter, and the accuracy of a positioning result of positioning based on the ionosphere delay parameters is improved.

The invention provides a geometric random channel modeling method for satellite-ocean communication, and the method comprises the steps: S1, building a satellite-ocean communication simulation scene, and setting scene layout parameters; s2, initializing a satellite transmitting end orbit parameter, a receiving end position and a sea wave fluctuation parameter; s3, calculating large-scale parameters with consistent space; s4, calculating path loss, shadow fading, atmospheric absorption loss, ionospheric scintillation loss and rainfall loss according to the set receiving and transmitting end position information; s5, calculating a small-scale parameter according to angle extension in the generated large-scale parameter, initializing the position of a scattering cluster on the sea surface and the surface of the ship body, generating time delay and power of the cluster, and generating a channel coefficient by combining the loss calculated in the step S4; s6, updating the large-scale parameters and the small-scale parameters according to the motion of the transmitting and receiving end and the birth and extinguishment process of the cluster, and generating a new channel coefficient; and S7, calculating channel statistical characteristics according to the obtained channel coefficients.

The invention relates to a low ionized layer electron density inversion method based on occultation data. The method comprises the following steps: obtaining a secondary data file provided by an occultation item consisting of a plurality of low-orbit satellites, then carrying out TEC data preprocessing, extracting an F-layer component of an ionized layer in a TEC profile according to two-section linear fitting within a certain height interval range based on the preprocessed data, and obtaining an F-layer TEC component of the ionized layer after interpolation; calculating the TEC component of a low ionized layer according to the occultation observation value after interpolation and the TEC component of the F layer of the ionized layer; constructing an electron density inversion linear equation set based on an Abel weighting function according to the height distribution of the TEC component of the low ionized layer, and solving by adopting non-negative least squares to obtain an inverted electron density profile; and performing smooth fitting on the inverted electron density profile by using a Gaussian function to obtain an electron density profile product. By adopting the method, the inversion precision of the electron density of the low ionosphere can be improved.

The invention provides a far-zone electromagnetic pulse waveform simulation method and system, and the method comprises the steps: introducing an international reference geomagnetic model, an international reference ionosphere model and an international reference atmosphere model when a waveguide parameter of a single-frequency signal segmented along a path is calculated through an LWPC model; the obtained geomagnetic parameters, the ionosphere electron density and the electron collision frequency contain influences of time and space, solar disturbance and geomagnetic changes, are used for simulation of the far-zone electromagnetic pulse waveform, and can improve the simulation precision of the far-zone electromagnetic pulse waveform.

The invention discloses a QPS numerical ray tracing and multi-target optimization-based high-frequency sky-ground wave radar ionosphere electron concentration inversion method, which comprises the following steps of: firstly, carrying out FFT (Fast Fourier Transform) on radar echo data, constructing a radar echo distance-Doppler matrix, and according to the obtained radar echo distance-Doppler matrix, calculating the electron concentration of a high-frequency sky-ground wave radar ionosphere according to the obtained radar echo distance-Doppler matrix; determining an antenna direct wave group distance and a transmitting station-receiving station ground distance; then determining an optimal emission elevation angle by using randomly generated ionosphere parameters; and finally, taking the emission elevation angle data corresponding to the n groups of ionosphere parameters as an initial population, and carrying out iterative optimization on the initial population by utilizing a population optimization algorithm to obtain an optimal ionosphere parameter result, thereby realizing ionosphere electron concentration inversion. According to the scheme, the radar echo data and the randomly generated ionosphere parameters are combined, the amount of data needing to be calculated is remarkably reduced, accurate inversion of the ionosphere parameters is achieved through ray tracing and multi-target optimization, the structure is simpler, the method does not depend on a complex model or a large amount of experience data, and the method is suitable for large-scale popularization and application. The optimal ionosphere parameter can be approached more quickly and effectively, and the real-time performance and accuracy of ionosphere electron concentration inversion are improved.

The invention discloses a real-time GNSS satellite clock error estimation and analysis method based on different references, and relates to the technical field of satellite navigation positioning, and the method comprises the steps: data input, which is used for collecting needed real-time data; the data provides necessary basic information for a subsequent processing flow; the data processing is used for data processing of real-time clock error estimation; in the operation process of a GNSS, the accuracy of time is directly related to the satellite-ground distance, and then the positioning precision of a user is influenced. Therefore, ensuring time accuracy becomes a core element of GNSS design and operation. According to the real-time GNSS satellite clock error estimation and analysis method based on different references, real-time satellite clock error estimation is carried out by adopting epoch difference ionosphere-free combination observation values. The method can effectively eliminate ionosphere delay and integer ambiguity, significantly reduce the number of to-be-estimated parameters, and further improve the precision and efficiency of real-time clock error estimation.

The invention discloses an unmanned aerial vehicle real-time tracking and positioning system and method based on a Beidou satellite, and relates to the technical field of high-precision navigation and unmanned aerial vehicle real-time tracking and positioning, and the system comprises a receiving module which receives signals of the Beidou satellite and a global navigation satellite system in real time through an antenna, and converts and demodulates the signal frequency to obtain a pseudo range; the processing module is used for performing multi-path effect detection and preliminary correction on the pseudo-range, and further correcting and optimizing the pseudo-range after preliminary correction according to the delay effect of the ionosphere and the troposphere; according to the method, multi-path effect correction is carried out on the pseudo-range, the influence of reflection and refraction on GNSS signals is reduced, the positioning precision is remarkably improved, the error of the pseudo-range is further reduced through correction of the ionosphere and the troposphere, and therefore the precision of position calculation is improved, and the positioning real-time performance of the unmanned aerial vehicle is remarkably improved.