55 results about "Total electron content" patented technology

The invention provides an ionosphere inversion method and system based on space-ground multi-source data fusion, and belongs to the technical field of ionosphere inversion. The problems that an existing ionosphere inversion method is poor in precision, low in timeliness and poor in adaptability to ionosphere change characteristics in different regions and under different conditions are solved. According to the method, after a proper ionized layer model is selected, sky-ground data are acquired and processed, and the critical frequency of an ionized layer, the vertical height at which the electron density reaches the maximum value and the total electron content of the ionized layer are reconstructed by using an improved Kriging interpolation method; and based on the reconstruction result, analyzing the change rule of the ionized layer characteristics along with time and space distribution and under different disturbance conditions. The method can improve the precision and reliability of ionosphere inversion, so that key parameters such as electron density distribution, critical frequency, total electron content and the like of the ionosphere are described more accurately, and more accurate data support and theoretical guidance are provided for the fields of navigation positioning, communication system optimization and space weather monitoring.

The invention provides a satellite navigation deception detection method, device and equipment based on total electron number deviation and a storage medium, and relates to the technical field of satellite navigation. The method comprises the following steps: acquiring a satellite signal of each satellite, and preprocessing the satellite signal to obtain a dual-frequency original pseudo-range observed quantity corresponding to the satellite signal; determining a total electron number measurement value of each satellite based on the double-frequency original pseudo-range observed quantity; global ionosphere map grid information is acquired, and a total electron number reference value of each satellite is determined based on the global ionosphere map grid information; determining a detection statistic of each satellite based on the total electron number measurement value and the total electron number reference value; and judging whether the satellite signal of each corresponding satellite is a deception signal or not based on the detection statistic and the deception detection threshold value of each satellite. According to the embodiment of the invention, whether the satellite signal is the deception signal can be accurately detected, and the deception jamming detection capability of the double-frequency GNSS receiver is improved.

The invention provides a total electron amount calculation and correction method for space-based detection ionosphere data. The method comprises the following steps: converting an earth-fixed coordinate system; calculating collision parameters; sorting collision parameters and phase arrays; performing phase calibration; and obscuration correction of the total electron amount. The method has the beneficial effects that according to the forward relation between the total electron content of the ionosphere and the additional time delay of radio wave propagation caused by the ionosphere, the accurate total electron content is obtained from the satellite-ground radio detection ionosphere data by using a calculation and correction method; the method is of great significance in the aspects of satellite positioning navigation radio wave correction, space environment monitoring and the like.

The invention discloses a foundation space ionosphere and troposphere integrated joint detection method and device, and belongs to the technical field of satellite navigation, and the method comprises the steps: detecting the vertical total electron content of an ionosphere: extracting the inclined total electron content of the ionosphere at an ionosphere puncture point, and converting the inclined total electron content into the vertical total electron content of the ionosphere; detecting a foundation Beidou ionosphere disturbance index; and detecting an ionosphere phase scintillation index, a troposphere zenith total delay, a troposphere precipitable amount and an ionosphere amplitude scintillation index, and outputting ground-based Beidou space ionosphere and troposphere integrated joint detection parameters. The method effectively improves the reliability, robustness and meteorological perception capability of a navigation positioning system in a complex atmospheric environment, and is especially suitable for special environmental conditions such as severe convection weather, typhoon landing, violent disturbance of an ionized layer and the like.

The invention discloses a low-cost GNSS (Global Navigation Satellite System) ionosphere disturbance monitoring and early warning method based on Transform, which is characterized in that a low-cost GNSS receiver is used for extracting total electron content (TEC) and processing data of a plurality of monitoring stations in a region in real time in combination with an ROTI index, and ionosphere disturbance is quickly predicted and early warning delay is remarkably reduced through a dynamic attention mechanism and multi-scale feature extraction of the Transform. Compared with a traditional method, more comprehensive ionosphere state information is provided by integrating observation sequences of all receivers in an area, meanwhile, the dependence on expensive high-frequency equipment is greatly reduced, and the monitoring cost is reduced. According to the invention, the architecture based on deep learning has high expandability, can be seamlessly integrated to the existing GNSS network, and provides an economical, efficient and high-timeliness solution for global ionosphere monitoring.

The embodiment of the invention discloses a training method, a using method and a related device of an electron content prediction model, and the method comprises the steps: carrying out the feature extraction of the total electron content data, geomagnetic activity index data and solar activity index data of an ionized layer collected by a Beidou satellite navigation system through a random forest algorithm; obtaining key feature data corresponding to the total electron content data; adopting a sliding window mechanism, taking the key feature data under a preset time window length as input time sequence data, taking the total electron content data at the last moment of the time window length as target output, and constructing a training sample pair; and performing prediction training of total electron content data according to the training sample pair and a preset deep learning model to obtain a trained electron content prediction model. In this way, the nonlinear dynamic characteristics of the ionosphere delay are effectively captured by the deep learning model, the prediction precision of the total electron content is improved, and the correction precision of the ionosphere delay is improved.

Described herein are solutions for real-time precise ionosphere corrections. An integrate and dump (I&D) server can receive a Networked Transport of Radio Technical Commission For Maritime Services (RTCM) via Internet Protocol (NTRIP) bit stream of a spherical harmonic model for precise point positioning (PPP). The model can be a vertical total electron content (VTEC) spherical harmonic expansion model and / or can include a set of ionosphere coefficients for correcting errors in satellite signals due to ionospheric conditions. The I&D server can generate a file of ionosphere coefficients, according to a refresh timer, and can send the file to a content delivery network (CDN) for distribution to user equipment (UEs) upon request. These and many other features and examples are described herein.

The invention discloses a GNSS (Global Navigation Satellite System) single-frequency precise single-point positioning method, a GNSS single-frequency precise single-point positioning device and electronic equipment. The method comprises the following steps: for each satellite in a satellite group, when an occultation event occurs, obtaining the total electron quantity of a first area and a second area of the satellite, and calculating the ionospheric delay at the position of a single-frequency receiver according to the total electron quantity; constructing a virtual observation equation according to the ionized layer delay; the method comprises the following steps: acquiring original observation data of a satellite and error terms of a satellite end, a propagation path and a receiver end, performing error correction on the original observation data according to each error term to obtain corrected observation data, and preprocessing the corrected observation data to obtain target observation data; constructing a positioning observation equation and a state equation according to the target observation data; adding the virtual observation equation as a constraint into a positioning observation equation to obtain a target positioning observation equation; determining a previous variance of the virtual observation equation; and resolving the target positioning observation equation and the state equation by using a Kalman filtering algorithm according to the prior variance to obtain the position of the single-frequency receiver.

The invention discloses an ocean sky ionized layer data enhancement method, device and equipment and a medium, and belongs to the technical field of ionized layer modeling. The method comprises the following steps: acquiring vertical total electron content data of a plurality of positions of an ionized layer over the ocean through observation of a low-orbit satellite; combining the vertical total electron content data of a plurality of positions of the ionosphere over the ocean and the longitude and latitude, observation time and space weather state data of the corresponding ionosphere puncture point as input feature data; inputting the input feature data into a first learning device to obtain enhanced feature data; and inputting the input feature data and the enhanced feature data into a second learning device to obtain vertical total electron content data of the ionized layer above the ocean. According to the invention, data enhancement is carried out on the ionosphere over the ocean through the integrated machine learning model, virtual observation data of the ionosphere in an unobserved area over the ocean can be obtained, and the observation coverage condition of the ionosphere over the ocean is effectively improved.

The invention relates to a global ionosphere TEC inversion method based on a Galileo HAS service, and the method comprises the steps: obtaining correction information through the HAS service, carrying out the preprocessing of observation data of a reference station according to the correction information, and obtaining a preprocessed carrier phase observation value; calculating carrier phase ambiguity and a purified carrier phase observation value according to the preprocessed carrier phase observation value; calculating the total electron content STEC of an inclined path according to the carrier phase ambiguity and the purified carrier phase observation value; constructing a double-layer ionosphere network model according to the geographic coordinates of the ionosphere puncture point and STEC; and carrying out inversion on the vertical total electron content of the ionized layer by using Kalman filtering to obtain the vertical total electron content of the ionized layer and carrying out compression. The method breaks through the network dependence of traditional foundation enhancement, and can still provide continuous and reliable ionized layer delay correction under the scenes of ocean, desert and the like.

The application discloses an ionosphere total electron content prediction method, a model training method and a system, relates to the field of satellite geodesy and space weather prediction, and the model training method comprises: an ionosphere total electron content prediction model comprising an encoder part of a stacked autoencoder, an Informer network and a decoder part of the stacked autoencoder connected in sequence; wherein the model training comprises stacked autoencoder training and Informer network training. The ionosphere total electron content prediction model is constructed based on the Informer network and the stacked autoencoder, the ionosphere total electron content prediction model is used for ionosphere total electron content prediction, the time complexity is reduced, the memory occupation is reduced, and the ionosphere total electron content prediction efficiency is improved.

The application discloses a method, system, device, medium and product for ionospheric modeling based on detection data, relates to the field of electromagnetic wave transmission and ionospheric modeling, and comprises the following steps: acquiring GNOS-II detection data of different dates according to a space environment, and screening effective rays based on the correction degree of electron density of the detection data; acquiring grid points through by the effective rays based on a space-based ionospheric inversion method according to corresponding data of the effective rays; determining total electron content of the space-based ionospheric inversion by using a dual-frequency calculation method according to the corresponding data of the effective rays; performing horizontal constraint and vertical constraint on global ionospheric electron density distribution by using a ground-based ionospheric inversion method according to the grid points through by the effective rays and the total electron content of the space-based ionospheric inversion; outputting the constrained global ionospheric electron density distribution to obtain a global ionospheric model. The application realizes real-time high-precision ionospheric construction in a global range.

The application discloses a method and system for ionospheric irregularity identification based on machine learning. The method comprises the following steps: receiving a GNSS observation file and an ephemeris file, and preprocessing the GNSS observation file and the ephemeris file; extracting an electron total content rate index feature, a time integral and total electron content index feature, and a Doppler coefficient feature according to the preprocessed GNSS observation file and ephemeris file; identifying ionospheric irregularities according to the extracted electron total content rate index feature, time integral and total electron content index feature, and Doppler coefficient feature, and outputting an identification result. The method can avoid setting a single threshold to determine whether an ionospheric irregularity event occurs during the process of identifying ionospheric irregularities, and effectively avoids data loss caused by cycle slip detection, thereby effectively identifying EPB events and TID events.

The invention provides a GNSS-R wide swath ionosphere vertical total electron content measurement method, device and equipment and a medium. The method comprises the following steps: measuring the propagation delay inequality of a direct signal and a reflection signal from the same navigation satellite through a satellite-borne GNSS-R dual-frequency receiver; calculating a first VTEC value below the satellite orbit at the specular reflection point according to the propagation delay inequality; according to the two-dimensional ionosphere model and the first VTEC value, calculating a second VTEC value and a third VTEC value below the satellite orbit at the incident puncture point and the reflection puncture point; for each target point in the specular reflection point, the incident puncture point and the reflection puncture point, calculating the total VTEC value of the vertical path based on the three-dimensional ionosphere model and the VTEC value below the satellite orbit at the target point, and taking the total VTEC value as the VTEC observation result of the single navigation satellite; and fusing VTEC observation results of a plurality of navigation satellites to generate wide-swath ionized layer VTEC observation data.

The application provides a kind of heat wave influence on global navigation satellite system positioning accuracy evaluation method and system, determine the research area and research year of target heat wave event, according to the corresponding climate state of research year;Obtain the temperature data of each meteorological station in the research area, interpolate and supplement the missing data among them;According to the data after interpolation and supplement, determine the research period of heat wave;Analyze the abnormal value spatial distribution of two-meter temperature above ground and daily average soil moisture in the research period of research area;Analyze the change of abnormal value of air temperature and atmospheric precipitable water per hour, and explain the reason of atmospheric precipitable water anomaly through the corresponding relationship of factors;Analyze the abnormal value change of ionospheric total electron content and air temperature per hour;Compare the difference of global navigation satellite system positioning accuracy in heat wave period and non-heat wave period in research period.The application provides a reference for users to carry out high-precision GNSS positioning during heat wave.

The application discloses a method and device for ionospheric delay correction based on regional ground-based GNSS and occultation data, and the method comprises the following steps: acquiring double-frequency observation data of ground-based GNSS in a target region and calculating VTEC; constructing a regional ionospheric TEC model by using a spherical cap harmonic function, calculating VTEC on each grid point in the target region according to a preset resolution, and screening effective grid points according to the number of piercing points of the grid points to form a regional grid constraint data set; taking the regional grid constraint data as virtual observation values, fusing the virtual observation values with global occultation vertical total electron content observation values, constructing a joint observation equation, and solving real-time broadcast ionospheric model coefficients; and calculating ionospheric delay correction values according to the real-time broadcast ionospheric model coefficients. According to the application, the regional VTEC grid constraint is constructed and is cooperatively inverted with global occultation data, so that the numerical ill-conditioned problem caused by direct fusion of multi-source heterogeneous data is effectively relieved, and on the premise of not depending on an empirical background field, the global precision, stability and dynamic adaptability of the model are significantly improved.

The application discloses a global ionospheric model precision factor generation method and device, and belongs to the technical field of satellite navigation and ionospheric modeling. The method comprises the following steps: inversing ionospheric vertical total electron content based on carrier phase smoothing pseudo-range; extracting ionospheric unmodeled error by using a global ionospheric grid map; analyzing the skewness and kurtosis distribution characteristics of the error; combining experience error optimization and measured error driving to reconstruct the ionospheric model precision factor, and improving the reliability and stability of the precision factor by introducing monitoring point classification, scale adjustment factor, inflation factor time smoothing and other mechanisms; further proposing an ionospheric error precision consistency map and an RMS envelope probability index to verify the consistency of the precision factor and the measured error. The application can generate a precision factor that truly reflects the statistical characteristics of ionospheric error, provides effective support for the construction of an ionospheric random model in high-precision GNSS positioning, and significantly improves the positioning precision and convergence performance.

Described are methods, systems, and devices for correcting ionospheric error. In some aspects, a mobile device equipped with a Global Navigation Satellite System (GNSS) receiver is configured to determine a positioning measurement of a GNSS signal. The mobile device is further configured to receive augmentation data from an augmentation system. When the mobile device is unable to obtain newer augmentation data, the mobile device can instead obtain augmentation data associated with historical Total Electron Content (TEC) values. In such instances, the augmentation data will have been generated to represent ionospheric delay during a time period that ended before the augmentation data is obtained. Based on the augmentation data associated with historical TEC values and a pierce point of the received GNSS signal, an ionospheric error in the positioning measurement of the GNSS signal can be determined and corrected.

The invention discloses a volcanic eruption monitoring method fusing wind cloud satellite and COSMIC ionosphere occultation data, which comprises the following steps: firstly, collecting and preprocessing data, fitting the preprocessed data through a spherical harmonic function, and inverting to obtain the vertical total electron content of each grid point; defining an abnormal state and a normal state according to the solar radiation flux index under the grid, and obtaining an abnormal state dynamic threshold value and a normal state dynamic threshold value; collecting real-time data, and obtaining a vertical total electron content real-time value of a global grid through inversion, wherein the vertical total electron content real-time value is used for judging a suspected abnormal disturbance signal and recording related spatio-temporal information; and extracting vertical total electron content data of a preset area in a time window corresponding to the suspected abnormal disturbance signal, calculating a grid proportion through conditions, judging that the interference is solar or geomagnetic activity interference according to the proportion, and otherwise, judging that the interference is local volcanic eruption. According to the method, efficient, rapid, global-coverage and high-precision volcanic eruption monitoring can be realized, and timely and reliable decision support is provided for disaster prevention and reduction departments.

The present disclosure presents systems method for remote sensing of the ionosphere. One such method comprises providing a single-board computer communicatively connected to a global navigation satellite systems (GNSS) receiver which is preconfigured to determine global positioning system coordinates by communicating with a set of GNSS satellites, reconfiguring the function of the single-board computer and GNSS receiver to acquire a set of GNSS signal parameters; and determining the set of physical properties of an ionosphere from the set of GNSS signal parameters. Other methods and systems are also provided.

An ionosphere monitoring method, device and equipment and medium using crowd-sourced GNSS data, the method comprising: obtaining inter-station single-difference ionosphere slant delay at crowd-sourced GNSS users and static reference stations, and calculating absolute ionosphere slant delay of the crowd-sourced GNSS users; obtaining line-of-sight direction total electron content of the crowd-sourced GNSS users through the absolute ionosphere slant delay of the crowd-sourced GNSS users; taking absolute ionosphere slant delay at the static reference stations as a reference, calculating absolute ionosphere slant delay of the crowd-sourced GNSS user group, and generating line-of-sight direction total electron content distribution map of the crowd-sourced GNSS user group to monitor the ionosphere. The application enhances the spatial coverage of the static reference station through the dynamic GNSS user group, improves the spatial resolution of the ionosphere discrete sampling information, and uses the static reference station to provide high-precision reference for ionosphere modeling of the dynamic GNSS user group, thereby forming a complementary enhancement mechanism of GNSS dynamic and static observation data, and finally cooperatively improving the spatial resolution and accuracy of ionosphere monitoring.

The invention provides an ionosphere modeling simulation method and device and related equipment, and the method comprises the steps: fusing first electron density fields of at least two simulation models of an ionosphere on a satellite signal propagation link, and obtaining a second electron density field of the ionosphere; superposing the second electron density field with disturbance terms of M scales to obtain a third electron density field of the ionized layer, M being an integer greater than 1; based on the orbit height corresponding to the satellite signal and the third electron density field, correcting a simulation environment about the ionosphere on the satellite signal propagation link to obtain a total electron content TEC correction result, matched with the orbit height, of the ionosphere; and based on the TEC observation data and the TEC correction result of the satellite signal about the ionized layer, performing data assimilation processing on the simulation environment about the ionized layer on the satellite signal propagation link to obtain a fourth electron density field of the ionized layer.

The application discloses a method, device, medium and product for predicting the total electron content of the ionosphere, which comprises the following steps: acquiring geomagnetic disturbance data of a region where a single-station global navigation satellite system is located, wherein the geomagnetic disturbance data comprises a magnetic north component and a magnetic east component; calculating the horizontal geomagnetic disturbance intensity based on the magnetic north component and the magnetic east component; inputting the horizontal geomagnetic disturbance intensity, the geomagnetic disturbance data, the acquired solar activity index and the historical observation sequence of the total electron content into a preset prediction model, so as to obtain a plurality of subspace attention features through a multi-head attention mechanism, and to obtain an encoding feature matrix through linear change processing; decoding the encoding feature matrix through a decoder of the prediction model to obtain a context vector, and performing autoregressive processing on the context vector until a target total electron content prediction sequence is obtained. The application can improve the prediction accuracy of the total electron content in the ionosphere above the single-station global navigation satellite system.

This invention belongs to the field of satellite navigation and space environment monitoring technology, and relates to a dual-frequency TEC inversion optimization method based on real-time altimetry data. Based on GNSS ground-based dual-frequency observations, it integrates ionospheric altimetry data and absolute signal deviation products to achieve high-precision conversion of STEC (Slant Total Electron Content) to VTEC (Vertical Total Electron Content). The method includes data preprocessing, TEC inversion, cycle slip detection, deviation correction, and mapping correction, and generates ROTI (Rate of TEC Index, i.e., ionospheric scintillation characterization parameter) products. By introducing a single-layer model for correcting the effective ionospheric height, the ability to characterize ionospheric disturbances is improved.

The invention discloses an ionosphere modeling method, system and device based on detection data, a medium and a product, and relates to the field of electromagnetic wave transmission and ionosphere modeling, and the method comprises the steps: obtaining GNOS-II detection data of different dates according to a space environment, and screening effective rays based on the correction degree of the detection data on electron density; according to the corresponding data of the effective ray, based on a space-based ionosphere inversion method, obtaining grid points through which the effective ray passes; according to the corresponding data of the effective rays, determining the total electron content of space-based ionosphere inversion by using a dual-frequency calculation method; and according to the grid points through which the effective rays penetrate and the total electron content of space-based ionosphere inversion, carrying out horizontal constraint and vertical constraint on the global ionosphere electron density distribution by utilizing a ground-based ionosphere inversion method, and outputting the constrained global ionosphere electron density distribution to obtain a global ionosphere model. According to the invention, real-time high-precision ionosphere building in a global range is realized.

The application discloses a method and system for identifying ionospheric irregularities, and the method comprises the following steps: pre-processing the night disk observation data by using a data integrity check and invalid value removal method, obtaining an effective radiation data set, and extracting a fixed-wavelength radiation data set in the southern and northern hemispheres from the effective radiation data set respectively; merging the fixed-wavelength radiation data sets in the southern and northern hemispheres, and drawing a radiation distribution map by combining a two-dimensional grid interpolation method; identifying ionospheric irregularities by using a radiation difference threshold identification method on the radiation distribution map to obtain a preliminary ionospheric irregularity identification result; and matching the preliminary identification result with total electron content data, calculating and determining a final ionospheric irregularity identification result. The method does not depend on densely distributed ground-based GNSS receiving stations, can significantly reduce the calculation complexity, and improves the processing efficiency.

The application provides a GNSS-R wide-swath ionospheric vertical total electron content measurement method, device, equipment and medium, and the method comprises the following steps: measuring the propagation time delay difference of direct signal and reflected signal from the same navigation satellite through a space-borne GNSS-R dual-frequency receiver; calculating a first VTEC value below the satellite orbit at the mirror reflection point according to the propagation time delay difference; calculating a second VTEC value and a third VTEC value below the satellite orbit at the incident piercing point and the reflection piercing point according to a two-dimensional ionospheric model and the first VTEC value; for each target point in the mirror reflection point, the incident piercing point and the reflection piercing point, calculating the total VTEC value of the vertical path based on a three-dimensional ionospheric model and the VTEC value below the satellite orbit at the target point, as the VTEC observation result of a single navigation satellite; and fusing the VTEC observation results of multiple navigation satellites to generate wide-swath ionospheric VTEC observation data.

The application provides a non-spherical assumption ionosphere occultation inversion method and device, comprising the following steps: solving occultation observation collision parameters and absolute total electron content through a data processing module; and constructing a non-spherical assumption inversion function model through a model establishing module. The application has the beneficial effect that the application solves the problem that mainstream ionosphere occultation inversion algorithms are limited by the spherical assumption, thereby making it difficult to improve inversion accuracy, and provides an ionosphere occultation inversion method based on a non-spherical assumption, thereby improving the accuracy of ionosphere occultation inversion, and the product can be applied to the fields of ionosphere weather monitoring and forecasting, navigation and positioning enhancement and the like.

The present application belongs to the technical field of satellite navigation, and specifically discloses an ionospheric delay correction method of a space-based data driven broadcast ionospheric model. The present application aims to use the occultation observation data of a low earth orbit (LEO) constellation to directly obtain global total electron content (TEC) which is independent of ground stations by integrating from the occultation electron density profile; and to introduce a neural network model to quickly calibrate and optimize the quality of the space-based TEC data; finally, to directly drive the NTCM-G broadcast ionospheric model using the calibrated TEC product which is high-precision and globally uniformly covered, to generate its global broadcast correction coefficients and broadcast them to users. The present application method establishes a new method of realizing a broadcast ionospheric model with space-based data as the core driving source, avoids the limitations of the ground-based observation network from the data source, and improves the autonomy, complete coverage and overall precision of the ionospheric correction service of the global navigation system.

The invention relates to the technical field of satellite navigation atmosphere modeling, and particularly discloses a GNSS ionized layer modeling method and system based on a multilayer mapping function, and the method comprises the steps: extracting the oblique total electron content of an ionized layer according to a multi-frequency non-difference non-combination precise point positioning ambiguity fixing method; constructing an ionized layer multi-layer mapping function model, and converting the oblique total electron content in each line-of-sight direction of the ionized layer into the vertical total electron content of the ionized layer through an ionized layer mapping function; and constructing a local ionosphere model, a regional ionosphere model or a global ionosphere model through corresponding mathematical models based on different regional characteristics of the ionosphere according to the oblique total electron content and the ionosphere multilayer mapping function model.