10 results about "Ionospheric electron density" patented technology

Disclosed in the present invention are an ionospheric electron density calculation method and device, and an electron content calculation method and device. The ionospheric electron density calculation method comprises: acquiring an electron content observation value of an ionospheric pierce point and an ionospheric electron density background value of a three-dimensional network; performing data assimilation on the electron content observation value and the ionospheric electron density background value to obtain an expression of an ionospheric electron density analysis value; constructing an observation error analysis function on the basis of the expression of the ionospheric electron density analysis value, the electron content observation value, and the ionospheric electron density background value; taking minimization of the observation error analysis function as an objective function, solving for a target position variance factor; and on the basis of the target position variance factor, calculating a corrected ionospheric electron density analysis value. In the present invention, a calculation result of ionospheric electron density is calibrated, such that the spatial distribution of electrons can be more accurately described, thereby improving the prediction accuracy of a model.

The invention discloses an ionized layer electron density profile abnormal fluctuation detection method, system and equipment. The method comprises the following steps: calculating a relative electron density change rate between adjacent height points of each effective electron density profile; the height axis is divided into a plurality of intervals, for each effective electron density profile, the robust percentile index of the relative electron density change rate is counted in each height interval, and a noise upper limit threshold value, a sawtooth amplitude threshold value and an extreme sudden change threshold value are generated; formulating a three-level progressive judgment process comprising a high noise background criterion, an extreme single-point jump criterion and an effective sawtooth structure criterion based on a noise upper limit threshold, an extreme sudden change threshold and a sawtooth amplitude threshold; and if any criterion is triggered, determining that the electron density profile is invalid. According to the method, non-physical sawtooth oscillation and extreme jump can be efficiently and accurately identified, and the quality control capability of data before ionosphere modeling is remarkably improved.

The application discloses a three-dimensional modeling and data assimilation method for ionospheric electron density, belongs to the field of space environment monitoring and information technology, and comprises the following steps: constructing a hybrid basis function system based on spherical harmonics and empirical orthogonal functions and establishing a state space model, independently perturbing through key geophysical driving parameters, combining a physical empirical model to construct a physical-statistical dynamic model, fusing multi-source heterogeneous observation data, obtaining an analysis state vector set through a set Kalman filtering algorithm and an asynchronous assimilation window, and reconstructing a three-dimensional electron density field and uncertainty products through the hybrid basis function system based on the analysis state vector set.

The application discloses a three-dimensional ionospheric disturbance extraction method, which comprises the following steps: acquiring double-frequency observation data of a research area from a GNSS receiving station; then, calculating STEC from the GNSS double-frequency signal and converting the STEC into dSTEC to highlight the ionospheric disturbance signal; secondly, constructing an observation matrix containing prior ionospheric model information and utilizing an improved three-dimensional tomography algorithm to iteratively correct and gradually approach the real electron density distribution; thirdly, in the iteration process, adopting inverse distance weighted interpolation to correct the pixels not being passed through, so as to ensure the overall smoothness; finally, inputting the dSTEC data into the improved three-dimensional tomography model, obtaining the three-dimensional ionospheric electron density distribution through iterative solution, and comparing the three-dimensional ionospheric electron density distribution with the actual observation data to verify the accuracy of the method. The method can effectively extract the three-dimensional structure of the ionospheric disturbance, improve the reconstruction accuracy and resolution, and provide an effective tool for studying the response of the ionosphere to events such as earthquakes.

This invention discloses a method for quantifying the memory time of solar extreme ultraviolet radiation based on ionospheric electron density. The method comprises: S1, constructing an EDPRNN; S2, inputting historical solar extreme ultraviolet (EUV) radiation, solar activity index, geomagnetic index, time, and altitude information into the EDPRNN, and optimizing it through a loss function to learn the memory time parameter τ for each altitude layer. i S3. Utilize LSTM layers to extract temporal features of historical solar radiation sequences, and then weight them using a Gaussian kernel module based on the learnable and memorizable time parameter τ. i The invention employs a multilayer perceptron (MLP) to weight temporal features, simulating the decay memory of electron density over historical radiation. In step S4, a one-dimensional convolutional module captures high-dimensional structural features, and a preliminary electron density profile is output by the MLP. A smoothing module enhances the vertical continuity of the profile through residual connections, completing the reconstruction of the ionospheric electron density profile. In step S5, the memory time of each altitude layer is extracted and quantified to obtain the distribution of ionospheric electron density memory time to solar EUV radiation. This invention achieves high-precision reconstruction of the ionospheric electron density profile and quantitative extraction of solar radiation memory time.

This invention discloses a method for constructing a multilayer ionospheric model based on prior constraints, comprising the following steps: obtaining the ionospheric electron density matrix output by the NeQuick-G model; processing the ionospheric electron density matrix using principal component analysis, and determining the number of ionospheric layers based on the cumulative contribution rate of the principal components; clustering the ionospheric electron density and corresponding height using the K-means clustering algorithm based on the number of layers to obtain the height and boundary of each layer; obtaining simulated total electron content data based on the height and boundary of each layer; selecting the optimal polynomial order for each layer and each modeling time period from multiple candidate polynomial orders using the Akaike information content criterion, and constructing a polynomial function model for each layer and each time period; constructing an ionospheric model using the original GNSS observation data based on the number of layers, the height and boundary of each layer, and the polynomial function model, and solving the ionospheric model parameters.

The application belongs to the technical field of satellite ionospheric electron density modeling system, and particularly relates to a Zhangheng No.1 satellite ionospheric electron density modeling system based on a CNN-LSTM hybrid architecture, which is realized through the cooperation of four modules, namely a data preprocessing module, a feature engineering module, a model construction and training module, and a model verification and application module. Each module is adaptively designed in view of the 97° high-inclination orbit characteristics of the Zhangheng No.1 satellite, the EDP data characteristics of the L03 level ionospheric occultation, and special application requirements, and sequentially completes the processing of satellite ionospheric data, feature extraction and optimization, construction and training of the CNN-LSTM hybrid model, model verification, and special scene application, thereby performing high-precision modeling of the ionospheric electron density of the Zhangheng No.1 satellite.

The invention discloses an ionosphere occultation additional phase correction method and system without auxiliary side data, which are used for realizing accurate inversion of ionosphere electron density under the condition of only occultation side observation. The method comprises the following steps: preprocessing additional phase and satellite positioning data, sorting according to collision height and screening according to intervals to finish initial accurate correction; calculating the initial total electron content at each collision height based on a quasi-correction result, and iteratively solving a top electron density coefficient and an elevation coefficient; calculating a top electron density parameter, an elevation parameter and a total electron content compensation item of each height by using the final coefficient; and adding the compensation item into the initial total electron content to obtain a correction result, and further generating an electron density profile. According to the method, high-precision inversion can be carried out without auxiliary side data, the limitation of a traditional differential correction method is overcome, the inversion precision and stability in a low-orbit satellite task are remarkably improved, and the application range of an occultation technology is expanded.

The application discloses a method and device for calculating ionospheric electron density and electron content, wherein the method for calculating ionospheric electron density comprises the following steps: obtaining an electron content observation value of an ionospheric piercing point and an ionospheric electron density background value of a three-dimensional regular network; performing data assimilation on the electron content observation value and the ionospheric electron density background value to obtain an expression of an ionospheric electron density analysis value; constructing an observation error analysis function according to the expression of the ionospheric electron density analysis value, the electron content observation value and the ionospheric electron density background value; taking minimization of the observation error analysis function as an objective function to obtain a target position variance factor; and calculating a corrected ionospheric electron density analysis value according to the target position variance factor. The application can calibrate the calculation result of the ionospheric electron density, can more accurately describe the distribution of electrons in space, and thus improves the prediction accuracy of the model.

The invention discloses a GNSS-based large-scale marching type ionosphere disturbance three-dimensional monitoring method and system. The method comprises the following steps: calculating the total electron content of an oblique ionosphere between a satellite and a receiver by adopting non-difference non-combination precise point positioning; based on Savitzky-Golay smoothing and Butterworth band-pass filtering, the total electron content of the detrending oblique ionized layer is obtained; based on spatial and temporal distribution formed by multiple stations, multiple satellites and multiple elevation puncture points, a three-dimensional ionosphere electron density disturbance model is constructed, and ionosphere disturbance three-dimensional propagation characteristics are solved. According to the method, the total electron content of the detrended oblique ionized layer is obtained based on Savitzky-Golay smoothing and Butterworth band-pass filtering, trend removal and disturbance reservation can be better balanced, and the signal-to-noise ratio and reliability of the extracted large-scale marching type ionized layer disturbance signal are improved; meanwhile, the constructed three-dimensional ionosphere electron density disturbance model not only can reveal vertical coupling characteristics of ionosphere disturbance, but also can stably extract key propagation elements and improve monitoring accuracy.