25 results about "Satellite altitude" patented technology

The invention discloses a multi-GNSS satellite signal power abnormity real-time monitoring method. The method comprises the following steps: acquiring real-time observation data of an observation station network which is uniformly distributed globally; when the linear relation between the carrier-to-noise ratios of different frequency signals of each satellite in each observation station and the dynamic monitoring threshold value related to the elevation angle of each satellite are determined, one signal is used for predicting another signal by using the linear coefficient, and the deviation between an actual value and a predicted value is calculated; calculating a satellite elevation angle of the real-time observation data, and determining a monitoring threshold value of the current satellite at the current moment according to the satellite elevation angle; and counting an average value of the deviations of all satellites monitored by all observation stations at the current moment, and marking that the power of the current satellite at the current moment is abnormal when the absolute deviation of the current satellite is greater than a monitoring threshold value. According to the invention, on the basis of the carrier-to-noise ratio linear relation of different frequency signals and the dynamic monitoring threshold, real-time monitoring of various power abnormal scenes including natural interference, man-made interference, satellite active power adjustment and the like is realized.

The invention relates to the technical field of satellite communication, in particular to a dynamic beam adjustment system for medium and low orbit satellite communication. Comprising a beam demand sensing unit; the dynamic beam calculation unit counteracts the influence of a complex environment on beam coverage through a multi-factor cooperative compensation mechanism; the beam execution adjustment unit is used for realizing beam accurate pointing and interference suppression through an adaptive phase optimization algorithm; and a satellite-ground cooperation unit. Through a multi-factor cooperative compensation mechanism, a beam theory pointing angle is calculated based on a spherical geometrical relationship, compensation amounts are determined by combining satellite motion, user movement and atmospheric refraction, and a communication scene is determined according to a satellite elevation angle, a user terminal motion speed and a communication link signal-to-noise ratio. The weight of each compensation amount is dynamically adjusted and synthesized into the total compensation amount, and finally the actual beam pointing angle is obtained, so that the coupling influence of multiple factors on beam coverage in a complex environment is effectively counteracted, and the beam pointing precision is improved.

Disclosed in the present invention are a method and apparatus for constructing an ionospheric mapping function model, a device, and a storage medium. The method comprises: acquiring historical slant total electron content data of an ionosphere; in the historical slant total electron content data, taking, as a corresponding historical vertical total electron content value, a historical slant total electron content value corresponding to a satellite elevation angle greater than a preset angle, and calculating a corresponding historical mapping function value; acquiring a corresponding Modified Julian Day, local time, satellite elevation angle and azimuth angle of an ionospheric pierce point; and on the basis of the historical mapping function value, the Modified Julian Day, the local time, the satellite elevation angle, and the azimuth angle of the ionospheric pierce point, training a preset LSTM model by taking the Modified Julian Day, the local time, the satellite elevation angle and the azimuth angle of the ionospheric pierce point as inputs and taking the historical mapping function value as an output, so as to obtain an ionospheric mapping function model. The present invention can improve the accuracy of ionospheric mapping functions.

The invention discloses a method for constructing a regional polynomial ionosphere oblique delay model, which belongs to the field of ionosphere delay error correction of a global satellite navigation system, and comprises the following steps of: calculating a signal puncture point coordinate through a reference station latitude and longitude coordinate, and calculating a signal puncture point coordinate by taking the signal puncture point coordinate, observation time and a satellite elevation angle as joint independent variables; sTEC constructs a polynomial function model for dependent variables; the spatial-temporal dynamic characteristics and the geometric characteristics of the sight line of the satellite are synchronously incorporated into modeling, and the spatial-temporal change rule of the ionosphere region is accurately captured; by utilizing polynomial analysis characteristics, model parameters can be quickly output, a user can directly calculate the required STEC only by inputting own coordinates, time, a satellite elevation angle and a satellite azimuth angle, the process is remarkably simplified, and the real-time performance is improved. According to the invention, the defects of precision and efficiency in a complex regional scene in the prior art are overcome, and a more reliable ionosphere error correction scheme is provided for regional GNSS high-precision positioning.

The invention provides a ground GNSS differential data correction method and device, and the method comprises the steps: obtaining a pseudo range and a carrier phase, calculating a whole cycle jump value of the carrier phase through employing an M-W combination function and an ionosphere delay change rate, and correcting a carrier phase value through employing the calculated whole cycle jump value of the carrier phase. The influence of station-satellite geometric distance is eliminated, the influence of ionosphere change is considered, and the method is suitable for cycle slip detection in a dynamic environment; according to the method, a self-adaptive threshold model is constructed on the basis of Turbo Edit cycle slip detection in a flight dynamic observation environment, cycle slip misjudgment at a low satellite elevation angle is reduced, and the influence of too low sampling rate on GF combined cycle slip detection performance is weakened to a certain extent; and a technical guarantee is provided for applying the GNSS differential data to the flight test.

The invention provides a troposphere anisotropy-considered real-time PPP positioning method, and relates to the technical field of satellite navigation and positioning, and the method comprises the following steps: S01, receiving real-time GNSS observation data, broadcast ephemeris data and precision correction data, carrying out detection and restoration of clock slip and cycle slip, data quality control and preprocessing of antenna phase correlation errors on the data to obtain a preprocessed data set; s02, calculating the solar altitude after atmospheric refraction correction according to each preprocessed data set and the geographic position and observation time of the observation station corresponding to each data set; and S03, based on the solar altitude and the satellite altitude. According to the method, solar altitude parameters are introduced, the troposphere anisotropy effect caused by solar radiation is effectively modeled, and the precision and convergence speed of real-time precise single-point positioning are remarkably improved.

The invention discloses a troposphere delay multi-layer grid modeling method fusing GNSS and ray tracing, which comprises the following steps of: performing ambiguity fixing processing on non-difference and non-combination PPP positioning data from GNSS reference stations, and estimating per-epoch parameters of each reference station, including troposphere delay, a satellite elevation angle and an azimuth angle; the longitude, the latitude and the altitude of the receiver are measured; the estimation parameters except for the troposphere delay are combined with meteorological data to serve as input of ray tracing calculation, so that the troposphere delay profile of the position of each receiver is determined to serve as ray tracing troposphere delay; and according to the troposphere delay estimated by the GNSS at the height of the reference station and the ray tracing troposphere delay, combining the ray tracing troposphere delays calculated at different height layers to obtain GNSS troposphere delays at different height layers, and forming a multi-layer GNSS troposphere delay product.

The invention discloses a broadcast ionosphere model adaptive selection method for a GNSS (Global Navigation Satellite System) terminal, which comprises the following steps: receiving navigation message information broadcasted by each GNSS system in real time, and obtaining various broadcast ionosphere model parameters; calculating the geographic latitude corresponding to the ionospheric puncture point according to the current position coordinate of the user, the satellite elevation angle and the azimuth angle; according to the geographic latitude and the time period of the current calculation time, selecting an optimal broadcast ionosphere model under the current space-time condition; and according to the optimal broadcast ionosphere model and the broadcast ionosphere model parameters, calculating to obtain a correction value of the ionosphere delay amount. According to the invention, by selecting the optimal broadcast ionosphere model in the current environment, the positioning precision is improved, the error of a certain model is prevented from being amplified, the advantages of each broadcast ionosphere model are exerted, and the stability and consistency of system positioning are improved; dynamic environment change is supported, and good space-time adaptive capacity is achieved; and model selection is realized only at a user side without modifying the broadcasting format of the existing satellite message.

The invention relates to an ionosphere pseudo observation random model construction method considering time-varying characteristics and baseline trend, which comprises the following steps: extracting a single-difference ionosphere delay estimated value as a sample, counting the random characteristics of the sample through a sub-window, and converting the absolute value expectation of the sample in the sub-window into an estimated value of a single-difference ionosphere delay standard deviation; the method comprises the following steps: selecting a satellite elevation angle, a baseline length, local time and a baseline azimuth angle as influence factors, expressing the standard deviation of single-difference ionosphere pseudo observation as a product form of each influence factor, and introducing logarithmic transformation into the standard deviation of single-difference ionosphere pseudo observation; and converting the product form into a linear regression form taking a satellite elevation angle, a baseline length, local time and a baseline azimuth angle as independent variables, and performing exponentiation on the linear regression form to obtain a single-difference ionosphere pseudo observation random model. The interpretation capability of the random model constructed by the method on the uncertainty of the ionosphere is remarkably enhanced, and the RTK resolving performance is remarkably improved under the condition of a low-latitude complex ionosphere.

The invention provides a GNSS diffraction error elimination method based on a regular hexagon grid, and the method comprises the steps: obtaining observation data and broadcast ephemeris of a GNSS reference station and a monitoring station, carrying out the calculation, obtaining an observation residual sequence of each satellite, and obtaining the corresponding elevation angle and azimuth angle of the satellite; a regular hexagon grid model covering the observation hemispherical surface is constructed, the regular hexagon grid model comprises a plurality of regular hexagon units which are equal in area and have isotropy, the observation residual error sequence is mapped into the corresponding regular hexagon units according to the elevation angle and the azimuth angle of the satellite, and a grid residual error set is formed; performing statistical distribution analysis on the grid residual error set in each regular hexagon unit, and calculating statistical characteristic parameters of residual errors; when the statistical characteristic parameters exceed a preset threshold value, it is judged that the corresponding regular hexagon units are polluted by diffraction errors, a data quality control grid mask is generated, and observation values in the regular hexagon units which are judged to be polluted by the diffraction errors are removed in subsequent positioning calculation.

The application discloses a kind of construction methods of regional polynomial ionospheric oblique delay model, belong to the ionospheric delay error correction field of global satellite navigation system, comprising: the signal piercing point coordinates are calculated by the longitude and latitude coordinates of reference station, then signal piercing point coordinates, observation time and satellite elevation angle are jointed as independent variable, and STEC is as dependent variable to construct polynomial function model;By synchronously including the space-time dynamic characteristics and satellite line-of-sight geometric characteristics into modeling, the space-time variation law of ionosphere is accurately captured;Using the analytical properties of polynomial, the model parameters can be quickly output, users only need to input their own coordinates, time, satellite elevation angle and satellite azimuth angle to directly calculate the required STEC, significantly simplify the process and improve real-time performance.The present application fills the accuracy and efficiency gap of the prior art in the complex scene, and provides a more reliable ionospheric error correction scheme for regional GNSS high-precision positioning.

This invention relates to the field of navigation satellite application technology, and particularly to a method and apparatus for inverting the multipath reflection coefficient of a water surface in a global navigation satellite system. Specifically, it includes the following steps: S1, releasing wave-damping material: releasing a linear damping medium onto the sea surface; S2, acquiring observation parameters: during the effective time of wave suppression, using a GNSS geodesic receiver to acquire observation data files and calculate the signal incident angle information; receiving a standard format RENIX file from the satellite using the GNSS geodesic receiver; calculating the satellite elevation angle information, obtaining the specific navigation satellite signal incident angle value P, and calculating the phase difference of the reflected signal; S3, inverting the water surface reflection coefficient α: inverting the water surface reflection coefficient α using a machine learning method. This invention achieves suppression of multipath errors in a water surface environment, improves the stability of monitoring point coordinates, and solves the problem of high false alarm frequency in large water areas.

The application relates to the technical field of satellite communication, in particular to a dynamic beam adjustment system for medium and low orbit satellite communication. The system comprises a beam demand perception unit, a dynamic beam calculation unit, a beam execution adjustment unit and a satellite-ground coordination unit. The dynamic beam calculation unit offsets the influence of complex environment on beam coverage through a multi-factor collaborative compensation mechanism. The beam execution adjustment unit realizes accurate beam pointing and interference suppression through an adaptive phase optimization algorithm. The application calculates the theoretical pointing angle of the beam based on spherical geometry, determines the compensation amount in combination with satellite movement, user movement and atmospheric refraction, dynamically adjusts the weight of each compensation amount and combines the compensation amounts into a total compensation amount according to the satellite elevation angle, user terminal movement speed and communication link signal-to-noise ratio, and finally obtains the actual beam pointing angle, so that the coupling influence of multi-factors on beam coverage in complex environment is effectively offset, and the beam pointing precision is improved.

The invention discloses an RTK random model refining method based on pseudo-range error distribution prediction. The method comprises the following steps: extracting a pseudo-range double-difference observation value residual error, and independently segmenting a residual error sequence of each satellite based on a variance point change detection method; performing layered parameterized model fitting and parameter estimation on the segmented residual error sequence; extracting a satellite elevation angle, an azimuth angle, a signal-to-noise ratio, a signal lock loss identifier and pseudo-range information from GNSS original observation data as features; a composite loss function combining a Huber function and priori knowledge constraints is constructed to suppress the influence of extreme abnormal values, and an intra-batch sample weight reduction strategy is introduced to improve the training stability; predicting a mean value and a standard deviation parameter of pseudo-range error distribution in real time by adopting a space-time diagram neural network architecture fusing LSTM and a diagram attention network; the predicted distribution parameters are used for refining the RTK random model in Kalman filtering; and finally, ambiguity fixation is carried out through an LAMBDA method, and a fixed solution or a floating solution is output.

This invention discloses a dual-antenna GNSS-IR water level monitoring method, apparatus, device, and storage medium, relating to the field of water level measurement technology. The method involves placing a first antenna below a second antenna and using a dual-antenna receiver to receive the signal-to-noise ratio (SNR) sequences of both the first and second antennas. Based on the antenna spacing, the antenna interference phase difference is calculated. Based on the antenna interference phase difference, the interference phase of the target antenna is calculated. Based on the oscillation frequency and wavelength of the SNR sequences, the interference phase, the GNSS satellite elevation angle, and the absolute antenna altitude, the absolute altitude of the target water surface is calculated. Compared to existing technologies, this invention solves the problem of low sampling rate in traditional single-antenna GNSS-IR altimeter measurement. Furthermore, compared to dual-antenna GNSS-IR, this invention offers more stable signal tracking and lower hardware costs.

The application provides a GNSS diffraction error elimination method based on a regular hexagon grid, comprising: acquiring observation data and broadcast ephemeris of GNSS reference stations and monitoring stations, calculating observation residual sequences of each satellite, and acquiring corresponding satellite elevation angles and azimuth angles; constructing a regular hexagon grid model covering an observation hemisphere, the regular hexagon grid model comprising a plurality of regular hexagon units with equal areas and isotropy, mapping the observation residual sequences into corresponding regular hexagon units according to the satellite elevation angles and azimuth angles, and forming a grid residual set; statistically analyzing the grid residual set in each regular hexagon unit, and calculating statistical characteristic parameters of the residuals; when the statistical characteristic parameters exceed a preset threshold, determining that the corresponding regular hexagon unit is contaminated by diffraction errors, generating a data quality control grid mask, and eliminating the observation values in the regular hexagon unit determined to be contaminated by diffraction errors in subsequent positioning calculation.

This invention discloses a method and system for determining ionospheric activity. Specifically, in the implementation process, firstly, the ambiguity integer solution of double-difference observation data is obtained through baseline resolution. Then, the ionospheric delay of all double-difference satellites for the current baseline is calculated using the ambiguity integer solution. Based on the double-difference ionospheric delay of all satellites, a first activity coefficient of the ionospheric delay is calculated using an elevation angle weighted method. Next, for each satellite, the ionospheric activity coefficient is obtained by subtracting the multi-epoch mean from the ionospheric delay of the current epoch. A second activity coefficient of the ionospheric delay is calculated using an elevation angle weighted method for all satellites. A first threshold and a second threshold are set respectively. When the first activity coefficient is greater than the first threshold or the second activity coefficient is greater than the second threshold, the current baseline is determined to be in an ionospherically active state, and an appropriate method is selected to fix the baseline ambiguity. As illustrated by the example, this disclosure can accurately determine the current ionospheric activity level, providing prior conditions for fixing baseline ambiguity and improving the reliability of NRTK services.

The invention discloses a multi-modal model mixing-based satellite-borne GNSS-R sea ice discrimination inversion method. The method comprises the following steps of obtaining DDM original data, a satellite elevation angle, a sea surface temperature and a bistatic radar cross section value; the real-time DDM data is preprocessed, and preprocessed four-channel DDM data is obtained; according to the preprocessed DDM data, extracting an observed quantity having correlation with the significant wave height; forming a data set by the extracted DDM data, a satellite elevation angle, a sea surface temperature and a bistatic radar section value; based on M% of data in the data set, constructing a sea ice discrimination inversion model mixed with a multi-modal model; and extracting an observation value sequence based on 1-M% data in the data set, inputting the observation value sequence into the sea ice discrimination inversion model to obtain a sea ice discrimination inversion value, obtaining a corrected observation value sequence at the same time, and establishing a parameter correction model for the corrected value to realize sea ice discrimination inversion.

The application discloses an optimal strategy and system for GNSS-IR snow depth inversion of a Beidou station. Existing snow depth inversion is mostly based on a fixed single model, and the optimal model cannot be selected for specific conditions to perform snow depth inversion. The application comprises obtaining standard format data received by a ground observation station from a satellite; obtaining observation values of a Beidou satellite from the standard format data, and combining coordinate information of a mirror reflection point of the Beidou satellite and satellite elevation angle and azimuth angle information to form a Beidou observation quantity file; screening the Beidou observation quantity file to select observation values meeting preset conditions; determining corresponding snow depth inversion models based on the number of observation values of each type in the observation values meeting the preset conditions; and performing snow depth inversion according to the determined snow depth inversion models and the corresponding observation values. The most suitable snow depth inversion model is determined through the type and number of observation values, and snow depth inversion is efficiently performed.

The invention provides a laser atmosphere data system, which belongs to the field of atmosphere parameter measurement and comprises a photoelectric component, an optical component connected with the photoelectric component through an optical cable and an external system crosslinked with the photoelectric component. The optical assembly is used for emitting laser to the outside of the aircraft and receiving a backscattering signal generated after the laser interacts with the atmosphere, and the photoelectric assembly dynamically adjusts the laser emitting power of the optical assembly according to the signal-to-noise ratio of the backscattering signal in combination with the laser air pressure height, the pressure air pressure height, the radio height, the satellite height and the wheel load signal; the device automatically maintains minimum power output on the ground and at a low-altitude stage, optimizes power configuration according to height change and working conditions at a flight stage, realizes self-adaptive adjustment of laser emission power of an optical assembly, guarantees the accuracy of atmospheric parameter measurement, prolongs the service life, and solves the problems that in the prior art, the emission laser power is not adjustable, and the laser emission power is not adjustable. The laser damage to ground personnel is caused; and the service life is short.

The present application relates to the field of sea ice detection, in particular to a sea ice thickness estimation method based on GNSS reflected signal phase. According to the oscillation frequency of the reflected signal phase with the satellite elevation angle, the thickness of the sea ice is estimated. The present application takes the navigation satellite as the signal source, receives and processes the GNSS direct signal and the signal reflected by the sea surface, extracts the frequency of the reflected signal phase oscillation with the satellite elevation angle, and estimates the thickness of the sea ice through the linear correspondence between the phase oscillation frequency and the sea ice thickness. The algorithm has low complexity, high detection accuracy, rich signal resources, global all-day, all-weather coverage, wide detection range, low cost, is not affected by the antenna pattern, is not limited by the receiver mode, does not need to select a specific satellite, has low algorithm complexity, high detection accuracy, and can effectively estimate the thickness of the sea ice.

The present disclosure relates to the technical field of satellite communications, and in particular to an end-to-end network system, and a serving cell handover method and apparatus. The serving cell handover method comprises: the system comprises a gNB-control plane (CP), at least one gNB-user plane DP, a first satellite, and a second satellite, wherein: the gNB-CP is arranged on the first satellite, the at least one gNB-user plane DP is arranged on the second satellite, the gNB-CP and the at least one gNB-user plane DP are connected by means of an inter-satellite link radio resource interface, the satellite altitude of the first satellite is greater than that of the second satellite, a base station RRC layer protocol stack function is deployed on the gNB-CP, and base station PHY and L2 protocol stack functions are deployed on any gNB-user plane DP among the at least one gNB-user plane DP. The present disclosure can improve the handover efficiency and the continuity of network services, and can expand the application range of the system and increase the transmission rate of user plane data.

This disclosure relates to the field of sea ice monitoring technology, specifically to a sea ice thickness estimation method, apparatus, storage medium, and electronic device. The sea ice thickness estimation method includes: acquiring image data, GNSS signals, pile foundation data, and environmental parameters; segmenting the pile foundation area and ice layer area based on the image data to obtain the pile foundation area and ice layer area, and shielding the pile foundation area to extract image features of the ice layer area; calculating the satellite elevation angle based on the direct signal in the GNSS signal, and calculating the observations based on the reflected signal in the GNSS signal, to calculate signal features based on the satellite elevation angle and the observations; inputting the image features, signal features, pile foundation data, and environmental parameters into a pre-trained sea ice thickness estimation model to obtain the sea ice thickness value output by the sea ice thickness estimation model. The sea ice thickness estimation method provided by this disclosure can improve the accuracy of sea ice thickness estimation under marine photovoltaic background.

The invention discloses an inland water level monitoring method and system based on altimetry satellite altitude difference data, and the method comprises the steps: obtaining a target water remote sensing image and an altimetry satellite data set, and carrying out the superposition selection of altimetry data points completely falling into the surface of a water body; the height measurement data points are preprocessed, height difference data are obtained, and after preset conditions are supplemented, a water level change time sequence is obtained through least square adjustment calculation; the system correspondingly implements the method. The height difference data are obtained through the intersection point method or the overlapped trajectory method, the geoid model residual error is offset, the problem of height errors caused by the spatial position in a traditional method is solved, and the water level monitoring accuracy is improved.

The invention discloses a multi-index combined high-credibility ionospheric scintillation monitoring system, which belongs to the field of ionospheric scintillation monitoring, and comprises the following steps: calculating an ionospheric scintillation intensity index based on historical observation data of a base station; calculating a flicker intensity threshold value in each satellite elevation angle interval according to the relative distribution condition of the ionospheric flicker intensity index and the satellite elevation angle and in combination with the phase flicker intensity index and the amplitude flicker intensity index of all satellites; respectively training ROTI, DI and AATR in the ionospheric scintillation intensity index to obtain respective random forest classifiers, and finally obtaining ionospheric scintillation intensity and scintillation intensity probability; and based on historical observation data of the base station, the observation value residual error change rate of all satellites is calculated, and the ionospheric scintillation intensity and probability are subjected to credibility evaluation. According to the method, the current ionospheric scintillation intensity is judged by using a random forest method, the intensity probability is given according to the judgment result, and credibility information is provided for a user.