18 results about "Low latitude" patented technology

The invention discloses a medium-low latitude ionosphere space-time prediction method and system during a strong magnetic storm, and the method comprises the steps: fusing ground-based GNSS and air-based COSMIC occultation ionosphere observation data, employing a multi-mode space-time sequence ionosphere model, integrating the advantages of a time convolution neural network and a Transform model through a cross attention mechanism, constructing a dual-space-time-flow TransTCN-XA prediction model, and carrying out the prediction of the medium-low latitude ionosphere through a time convolution neural network. And the spatial-temporal change of the medium-low latitude ionosphere during the strong magnetic storm period can be effectively captured. By adopting the technical scheme of the invention, higher resolution and more accurate ionosphere forecasting can be provided for the fields of space weather forecasting and navigation positioning, so that the accuracy and reliability of forecasting are remarkably improved.

The application provides an ionospheric delay estimation method considering non-absolute zero constraint in high latitude areas. The application introduces ionospheric piercing point data of multiple historical moments and multiple geographical positions; a linear ionospheric delay calculation model is constructed; the multiple historical moments and the multiple geographical positions are compared with a latitude threshold in sequence to obtain multiple high-latitude geographical positions of multiple historical moments and multiple low-latitude geographical positions of multiple historical moments; a low-latitude observation equation and a high-latitude observation equation are constructed; the low-latitude observation equation and the high-latitude observation equation are combined to obtain an optimized parameter vector of an ionospheric model considering non-absolute zero constraint in high latitude areas; each ionospheric piercing point data of each geographical position in real time is taken to calculate and output the optimized ionospheric delay of the real-time geographical position. The application has the advantages of obviously relieving the high-latitude anomaly of the Beidou Klobuchar model and significantly improving the correction performance of the Beidou Klobuchar model in the southern hemisphere.

The invention provides a converged communication gateway suitable for polar navigation. The converged communication gateway comprises a core control module, a 5G communication module, a multi-interface adaptation module, a network detection module, a data forwarding module, a position positioning module, a polar region signal enhancement module and a power supply module. The core control module pre-stores a maritime satellite coverage map, and automatically selects an active link according to the priority hierarchy of 5G priority, VSAT second priority and iridium bottom according to the real-time position and network state; and the differentiated cache duration is selected according to the switching type during switching, so that the data integrity is guaranteed. According to the invention, communication seamless switching in near-shore, medium-low-latitude ocean and high-latitude areas is realized, and communication continuity, adaptability and cost economy are guaranteed.

The application discloses a prediction method for radiation refrigeration capacity by using aerosol optical thickness and precipitable water amount, comprising the following steps: S10, obtaining corresponding hourly weather data according to weather data; S20, judging whether the local latitude is greater than 33°, if yes, entering step S30, S30, calculating the local precipitable water amount (PWV H ) by using a high-latitude calculation method; if no, entering S40, S40, calculating the local precipitable water amount (PWV L ) by using a low-latitude calculation method; S50, calculating atmospheric radiation according to the calculated precipitable water amount (PWV H or PWV L ); S60, correcting the atmospheric radiation calculated in S50 according to the aerosol optical thickness in the weather data; and S70, calculating the radiation refrigeration capacity according to the atmospheric radiation corrected in S60.

The application provides a geometry checking method for mesh generation, a PCB simulation method, a computer device and a storage medium, and comprises the following steps: reading a plurality of input geometry models, obtaining the geometry and the corresponding boundary element of each geometry model; recording the collision box of each geometry, and judging the geometry whose collision boxes do not intersect as compatible, and recording other geometries as target geometries; the compatibility refers to the intersection region of two geometries being the common boundary element of the two geometries, otherwise being incompatible; sorting all target geometries according to the dimension, and checking whether the target geometry of the current dimension is incompatible with the target geometry of the same dimension or low latitude; if it is judged that there is an incompatible target geometry, the process is stopped and error information is returned. The scheme can quickly check the geometry model before mesh generation, and quickly and accurately feed back specific error information and position when incompatible geometry models are found, thereby improving the overall efficiency and effect of simulation.

The invention discloses a Beidou-based high-precision differential positioning adjustment system and method, and relates to the technical field of satellite navigation and high-precision localization. Time-frequency analysis is carried out on a multi-frequency carrier phase observation sequence, signal-to-noise ratio monitoring is combined, and a flicker identifier and a noise weight are constructed; the system can identify frequency points and observation sections which are seriously polluted by flicker at an epoch level, and the weight of the system is actively reduced at a combination stage; secondly, under the constraint of maintaining ambiguity integer characteristics, the coefficient combination takes equivalent noise variance and residual ionosphere high-order term error sensitivity as optimization targets, and considers the observation noise level and the suppression capability for high-order ionosphere residual errors, so that on one hand, the reliability of carrier phase integer ambiguity calculation is maintained, and on the other hand, the reliability of carrier phase integer ambiguity calculation is improved; and on the other hand, the sensitivity degree of combined observation to high-order ionosphere residual errors is reduced, so that high-precision differential positioning of a low-latitude region has higher robustness.

The invention belongs to the technical field of ionosphere physics, and particularly relates to a Chinese low-latitude region ionosphere TEC empirical model based on multi-source data fusion, and the modeling process comprises the steps: selecting multi-source TEC data of a solar activity cycle in a Chinese low-latitude region as a multi-source data set; determining the weight of each type of data through a Hall model variance component estimation method, and determining the weight of each type of data; carrying out data fusion on various data in the multi-source data set by utilizing the determined weight through a form of a 15-order 15-order spherical harmonic function to obtain a modeling data set; setting components of the TEC empirical model, and establishing a nonlinear mathematical expression to represent all the components; and calculating to-be-estimated parameters in the nonlinear mathematical expression of each component through nonlinear least square fitting, forming a TEC empirical model, and finishing final modeling. According to the method, the modeling precision of the Chinese low-latitude region is effectively improved, and the temporal and spatial change rule of the TEC can be described more accurately.

The invention discloses a low-latitude ionized layer total electron content prediction method based on equator ionization anomaly feature coding. The method comprises the following steps: acquiring and preprocessing historical observation data of the low-latitude ionized layer total electron content; identifying and quantitatively extracting key characteristic parameters representing the spatio-temporal evolution morphology of the equatorial ionization anomaly; constructing a feature coding network, and coding the key feature parameters into low-dimensional feature vectors to learn dynamic feature representation of the key feature parameters; and constructing and training a sequence prediction model capable of fusing the feature representation, and realizing high-precision prediction of the total electron content at the future moment by using the encoded feature vector and historical total electron content data. According to the method, quantitative physical characteristics of equatorial ionization abnormity are introduced, and a deep fusion mechanism of double-branch coding and hierarchical attention weighting is further designed, so that the prediction precision of the total electron content of the low-latitude ionized layer and the interpretability of the model are effectively improved.

Provided is a method for detecting a low-latitude air vehicle. The method includes following steps: S1: setting up a fixed column and a movable column, and disposing a detection antenna; S2: determining whether two detection antennas on the fixed column simultaneously detect a target; and if the two detection antennas on the fixed column simultaneously detect the target, performing step S3; or if the two detection antennas on the fixed column do not simultaneously detect the target, performing no operation; S3: determining in real time whether at least one of the two detection antennas loses the detected target; and if the at least one of the two detection antennas loses the detected target, performing step S4; otherwise, adopting the two detection antennas for detection; and S4: driving a rotating shaft to make the movable column rotate; and adopting four detection antennas for detection.

The invention discloses a satellite observation-based medium-low-latitude ultralow-frequency electromagnetic disturbance classification and analysis method, which comprises the following steps of: performing feature processing to obtain an electric field component disturbance value and an electron density relative variation, constructing a classification feature set, inputting in-situ observation data into a disturbance existence judgment model to obtain significant disturbance data, the method comprises the following steps of: calculating a cross covariance and multivariable mutual information among significant disturbance data, performing multi-stage disturbance classification to obtain a disturbance result and calculating a disturbance index, constructing a disturbance factor gradient lifting regression model, and inputting in-situ observation data to be processed into the disturbance factor gradient lifting regression model to obtain a disturbance prediction index and a disturbance influence factor. The method can efficiently and accurately extract and classify the ultralow frequency electromagnetic disturbance in the medium and low latitude region, can also predict the disturbance and quantitatively attribut all influence factors, and has important significance for deepening the research on the dynamics mechanism in the magnetic layer-ionized layer coupling process and improving the space environment monitoring capability.

The application discloses a method for reducing low-latitude magnetic anomaly, comprising the following steps: S1, constructing a model space of a sample data set, wherein the model space is composed of an underground half space and a plurality of cuboid units, and the plurality of cuboid units are arranged in a combined form in a non-edge area of the underground half space; S2, performing traversal sampling and data amplification to obtain a sample data equivalent magnetic anomaly body; S3, acquiring a stable initial model by using a frequency domain suppression method; S4, taking the stable initial model and a magnetic anomaly with an arbitrary magnetization direction as inputs of a FCN network structure, taking a magnetic anomaly perpendicular to the magnetization direction as a label, and training the FCN reduction network structure; and S5, taking measured data and the stable initial model as inputs of the trained FCN reduction network structure to obtain a reduction prediction result. The application can obtain more accurate reduction results and provide technical support for geological interpretation.

The application discloses a method for classifying and analyzing super low frequency electromagnetic disturbance at middle and low latitudes based on satellite observation, which comprises the following steps: obtaining electric field component disturbance values and electron density relative change values through feature processing, constructing a classification feature set, inputting in-situ observation data into a disturbance existence determination model to obtain significant disturbance data, calculating cross-covariance and multivariate mutual information between the significant disturbance data, performing multistage disturbance classification to obtain disturbance results and calculate disturbance indexes, constructing a disturbance factor gradient boosting regression model, and inputting in-situ observation data to be processed into the disturbance factor gradient boosting regression model to obtain disturbance prediction indexes and disturbance influencing factors. The method can efficiently and accurately extract and classify super low frequency electromagnetic disturbance at middle and low latitudes, and can also perform disturbance prediction and quantitative attribution of influencing factors, which has important significance for deepening the research on the dynamic mechanism of the magnetosphere-ionosphere coupling process and improving the space environment monitoring capability.

The invention discloses an ionosphere prediction method and device based on a white spectrum method and deep learning, and belongs to the technical field of intersection of spatial physics and satellite navigation, and the method comprises the steps: carrying out the preprocessing of multi-source observation data, obtaining time series data, carrying out the white spectrum method analysis of the time series data, and obtaining a disturbance time series; processing the disturbance time sequence to generate a global solar activity level index, a middle and low latitude geomagnetic disturbance index and a polar region geomagnetic disturbance index; the indexes and satellite inversion data serve as input, a deep learning reconstruction model formed by a multi-layer full-connection feedforward neural network is adopted, and ionosphere four-dimensional electron density distribution is output; ionized layer four-dimensional electron density distribution and total electron content observation data serve as input, a space-time prediction model is adopted, and an ionosphere prediction result at the future moment is output. The problems that a traditional spatial index is poor in timeliness and low in resolution and cannot effectively capture the complex time-space characteristics of the ionized layer can be solved.

The application provides a fusion communication gateway suitable for polar navigation. The fusion communication gateway comprises a core control module, a 5G communication module, a multi-interface adaptation module, a network detection module, a data forwarding module, a position positioning module, a polar signal enhancement module and a power module. The core control module pre-stores a maritime satellite coverage map, and according to the real-time position and network state, the active link is automatically selected in the priority order of 5G first, VSAT second and Iridium last; when switching, the differentiated cache time length is selected according to the switching type to ensure data integrity. The application realizes seamless switching of communication in nearshore, mid-low latitude ocean and high latitude areas, and guarantees communication continuity, adaptability and cost economy.

The invention provides a low-latitude ionospheric scintillation multi-step prediction method based on a Nonstandard Transform, and belongs to the technical field of navigation. The method comprises the following steps: firstly, complementing missing data of an electronic altimeter through a neural network, dynamically weighting and integrating multi-source signal amplitude flicker indexes at the same moment in combination with a satellite elevation angle, and constructing a flicker characterization index strongly related to a receiver positioning error; secondly, quantitatively screening characteristics such as geomagnetic activity and solar activity by using a maximum mutual information value, and reducing redundant interference; further based on a non-stationary time sequence modeling architecture, capturing non-stationary evolution characteristics of ionospheric scintillation, and realizing multi-step prediction of scintillation intensity at future continuous time points; and finally, the prediction reliability of the model in different flicker scenes is verified through a strength interval evaluation mechanism. According to the method, the problems of discontinuous single-point prediction and weak sudden change capture capability of the existing model are solved, the support capability of a prediction result on a receiver end dynamic suppression strategy is remarkably improved, and the stability of a navigation system in a complex ionized layer environment is effectively enhanced.

The present invention provides a method and system for joint adjustment of the mass and stiffness of the entire surface of a hemispherical resonator, belonging to the field of solid-state vibrating gyroscopes. In order to solve the problem that the existing hemispherical resonator adjustment process does not etch on the entire hemispherical shell, mass-stiffness coupling occurs during the adjustment frequency cracking process, resulting in low adjustment efficiency. A laser Doppler vibrometer is used to obtain the low-frequency axis and high-frequency axis orientation and frequency cracking value of the hemispherical resonator, and the focused ion beam is controlled to fine-tune the stiffness of the four high-frequency axis positions in high-latitude areas, and to fine-tune the mass-stiffness coupling on the four low-frequency axis positions in low-latitude areas. Etching on the entire hemispherical shell can decouple the mass and stiffness of the hemispherical resonator and improve the adjustment efficiency of the hemispherical resonator; through the mass-stiffness joint adjustment, the mass and stiffness are decoupled, and the uniformity of the mass and stiffness of the hemispherical resonator gyroscope is improved; this method has a certain universality and can be extended to the mass-stiffness adjustment of resonators of different shapes.

The application discloses a low-latitude ionospheric total electron content prediction method based on equatorial ionization anomaly feature coding, and the method comprises the following steps: acquiring and preprocessing historical observation data of low-latitude ionospheric total electron content; identifying and quantitatively extracting key feature parameters representing the spatial and temporal evolution form of equatorial ionization anomaly; constructing a feature coding network to code the key feature parameters into low-dimensional feature vectors to learn the dynamic feature representation thereof; constructing and training a sequence prediction model capable of fusing the feature representation, and using the coded feature vectors and historical total electron content data to realize high-precision prediction of the total electron content at a future time. By introducing the quantitative physical features of equatorial ionization anomaly, further designing a deep fusion mechanism of double-branch coding and hierarchical attention weighting, the precision of low-latitude ionospheric total electron content prediction and the interpretability of the model are effectively improved.

The application belongs to the technical field of ionospheric physics, and particularly relates to a Chinese low-latitude region ionospheric TEC empirical model based on multi-source data fusion, and a modeling process comprises the following steps: selecting multi-source TEC data in a solar activity week in the Chinese low-latitude region as a multi-source data set; determining the weight of each kind of data by weighting each kind of data through a Helmer mode variance component estimation method; obtaining a modeling data set by fusing various data in the multi-source data set through a 15th order 15th time spherical harmonic function and the determined weight; setting a component of the TEC empirical model, establishing a nonlinear mathematical expression to represent all components; calculating the to-be-estimated parameters in the nonlinear mathematical expression of each component through a nonlinear least square fitting calculation to form the TEC empirical model and complete the final modeling. The application effectively improves the modeling accuracy in the Chinese low-latitude region, and can more accurately describe the temporal and spatial variation law of TEC.