14 results about "Ionospheric sounding" patented technology

The invention relates to the technical field of satellite navigation and ionosphere detection, in particular to a low-latitude ionosphere disturbance and non-uniform body multi-means collaborative detection and classification method. A multi-network cooperation-multi-source fusion observation mode is adopted, full space-time coverage of low-latitude ionosphere disturbance is achieved, in addition, a data fusion method based on physical constraints is applied, an ionosphere-middle atmosphere-troposphere multi-physics field coupling constraint mechanism is constructed, space-time consistency of data obtained through different observation means is optimized, and the low-latitude ionosphere disturbance is obtained. And finally, key characteristic parameters are extracted by using a multi-scale signal processing method, a disturbance characteristic matrix is constructed in combination with radar observation data (such as drift speed and spectral width), a'three-axis nine-element 'disturbance / non-uniform body classification standard is proposed firstly, then deep learning classification is used, accurate classification of low-latitude ionosphere disturbance is realized, and GNSS signal anomaly recognition capability is improved.

The embodiment of the invention provides a Beidou water vapor ionosphere detection system calibration method, device and equipment, and is applied to the technical field of detection calibration. The method comprises the following steps: performing double-frequency combination observation according to observation values of any two frequency bands in Beidou multi-frequency observation data, and calculating residual information after first-order delay elimination of an ionized layer; performing optimization combination on the residual information based on a preset combination optimization rule to generate high-order residual information; calculating the moisture delay of the troposphere according to the meteorological parameters; performing filtering correction on the high-order residual error information and the wet delay based on a preset dynamic filtering model to obtain high-order residual error correction information and corrected wet delay; based on a preset navigation positioning equation, static term delay is calculated according to the corrected wet delay; the high-order residual error correction information is used as ionosphere delay, the correction wet delay and the static term delay are used as zenith troposphere delay, and the Beidou water vapor ionosphere detection system is calibrated. In conclusion, the precision of the Beidou system in water vapor and ionosphere detection can be improved.

The invention belongs to the field of ionosphere detection, artificial intelligence and deep learning, and particularly relates to a lightning electromagnetic pulse-based large-area ionosphere D layer height measurement method, system and equipment. The problems that a traditional detection method is high in cost, limited in coverage range and prone to being interfered by natural disasters and strong electromagnetic pulses are solved. The method comprises the following steps: acquiring lightning event information based on an electromagnetic pulse detection station; calculating a ground wave and sky wave arrival time difference based on a pre-trained deep learning model, and calculating to obtain the ionosphere D layer height of a single position; performing gridding processing on the obtained ionosphere D layer height data at different positions according to certain time and spatial resolution, performing interpolation null value filling on the gridded data, and performing smoothing processing; and outputting a calculation result of the D layer height of the large-area ionized layer. According to the invention, wide-area low-cost ionosphere detection is realized by adopting the natural lightning radiation source, and the measurement precision is improved by optimizing the model for different lightning types.

The invention provides an ionosphere parameter and short wave frequency band prediction method and electronic equipment, and the method comprises the steps: obtaining the ionosphere parameter data in a corresponding IRI model above the midpoint of a great circle through obtaining the geographic coordinates of two places of a communication link and the midpoint of the great circle, obtaining the geomagnetic solar activity data of an open-source data website, and obtaining the geomagnetic solar activity data of the open-source data website; the method comprises the following steps: carrying out ionosphere oblique detection by using ionosphere detectors at two communication places, obtaining an ionosphere oblique detection ionogram, obtaining frequency band data available for short-wave communication from the oblique detection ionogram, carrying out data preprocessing, selecting different tasks, setting corresponding Transform-LSTM model hyper-parameters, carrying out model training, and storing optimal model parameters; and performing an ionosphere parameter prediction task or a short-wave communication available frequency band prediction task by using the corresponding model. The ionosphere detection data, the environment monitoring data and the like are fused in the deep learning field and the short-wave communication field, and the method has important significance and application prospects.

The invention relates to an ionosphere detection method and device. The method comprises the following steps: acquiring satellite observation data; performing quality detection on the satellite observation data and outputting a state file; judging whether the satellite observation data is qualified or not based on the state file; if the satellite observation data is qualified, performing data processing based on the satellite observation data to obtain first processing data; performing calculation based on the first processing data to obtain the ionized layer electron content; and outputting a display signal based on the satellite observation data and the ionized layer electron content. The method and the device have the effect of obtaining accurate ionosphere data.

The invention provides a double-baseline elevation angle estimation method based on an ionized layer detection radar. The ionized layer detection radar comprises M units of linear main arrays and N units of linear sub-arrays. The method comprises the following steps: adding an antenna at a set position; canceling an antenna at the edge of the main array to form a new main array; the set position is located between the main array and the sub-array and outside the view field of the sub-array; calibrating an amplitude-phase error of the newly-added antenna; and estimating a double-baseline elevation angle. The radar antenna array has the advantages that the occupied area of the radar antenna array does not need to be increased, and the performance of other components of the radar does not need to be greatly improved. And the antenna array layout has high flexibility. The elevation angle estimation algorithm has high applicability.

The present invention provides a frequency-height map denoising and recognition method based on DnCNN and YOLOv8. The method includes: inputting an ionospheric sounding image into the DnCNN model to obtain a denoised clear image; inputting the denoised clear image into the YOLOv8 model to obtain recognized objects and output ionospheric parameters. Through the precisely adjusted DnCNN model, the noise in the ionospheric image is effectively removed, and the key echo information is retained, providing high-quality input for subsequent image processing; through the fine-tuning of the YOLOv8 model, the resource consumption is reduced, and the efficiency of model training and the accuracy of object recognition are improved; the automation and intelligence of ionospheric sounding image processing are realized, and the processing efficiency and practicality are improved; it is applicable to scientific research and monitoring applications that require high-precision ionospheric image analysis, and has important practical value and scientific significance.

The application provides a double-baseline elevation angle estimation method based on an ionospheric sounding radar, the ionospheric sounding radar comprising an M-unit linear main array and an N-unit linear subarray; the method comprising: adding an antenna at a set position; canceling an antenna at the edge of the main array to form a new main array; the set position being located between the main array and the subarray and outside the field of view of the subarray; calibrating the amplitude and phase errors of the added antenna; and estimating the double-baseline elevation angle. The application has the advantages that: the antenna array pattern proposed in the application does not need to increase the floor area of the radar antenna array, and does not need to greatly improve the performance of other components of the radar. The antenna array layout has strong flexibility. The elevation angle estimation algorithm has strong applicability.

The application discloses a method for estimating the elevation angle of a slant ionospheric sounding incoming wave based on polarization response, which comprises the following steps: obtaining the polarization response information of the incoming wave through an orthogonal receiving antenna, so as to determine the limit polarization of the incoming wave signal from the ionosphere into free space, and determining the direction of the incoming wave through the relationship between the limit polarization and the elevation angle of the incoming wave and the geomagnetic field. The method for estimating the elevation angle of the slant ionospheric sounding incoming wave based on polarization response can be applied to the acquisition of the elevation angle information of the incoming wave through the processing and estimation of the polarization information of the electromagnetic wave, and can also be used as an auxiliary means of the traditional short-wave direction finding method.

The application relates to the technical field of space environment detection, in particular to an ion generation and introduction device for planetary atmosphere and ionosphere detection. The ion generation and introduction device comprises a gas sampling assembly located at the top of an ionization chamber (3), symmetrically arranged electron emission and control assemblies located in the ionization chamber (3), an ionization chamber voltage regulation assembly located between the electron emission and control assemblies, and an ion extraction lens assembly located at the side of the ionization chamber (3). The ion generation and introduction device meets the requirement of ion generation and introduction device output ions for the measurement of neutral gas and ion isotope in the atmosphere and ionosphere of the earth and extraterrestrial planets and small celestial bodies, and has the ability to support subsequent high-precision and large-range mass resolution.

A method of predicting parameters of an earthquake uses an array of ionosondes to scan an observed volume of an ionosphere located above a seismically active zone. The method includes monitoring ionograms provided by the array of ionosondes; detecting the presence of at least one seismic-induced irregularity (SII); determining a first predicted parameter corresponding to an epicenter location; and determining one or more predicted parameters selected from a group consisting of a magnitude, a time of occurrence, and a hypocenter depth. Algorithms for calculating the predicted parameters are presented in detail.

The invention provides an ionospheric sounding rocket test foundation observation combined measurement and calibration data processing system, and relates to the technical field of ionospheric sounding rocket tests, the system comprises a test window forecasting subsystem, a rocket ground data summarization analysis subsystem and a rocket ground data calibration comparison subsystem; the test window forecasting subsystem is used for collecting ionosphere parameters; the rocket-ground data summarization and analysis subsystem is used for reporting critical height of an ionized layer according to the foundation encrypted observation data, and obtaining a standard data product in combination with rocket-borne Langmuir probe detection data and sun and geomagnetic activity data; the rocket-ground data calibration and comparison subsystem is used for calibrating the detection data of the rocket-borne Langmuir probe after comparison analysis and standardization processing to obtain a calibration data product; according to the scheme, the rocket-ground data can be automatically read and analyzed, the rocket-ground joint measurement data can be automatically processed and calibrated, tedious steps and errors caused by manual operation are avoided, and the data processing speed and accuracy are improved.

The invention discloses a method for detecting the D layer of the lower ionosphere based on dual-station signal inversion, and specifically relates to the technical field of low ionosphere detection. A magnetic loop antenna is used to receive VLF signals from dual communication stations, and the sampling frequency is 1 MHz. S2. After filtering and amplifying 8000 times, the received electrical signal is converted into a magnetic signal according to the law of electromagnetic induction, and then the magnetic signal is converted into an electrical signal in dBμ by using Maxwell's equations. S3. The angle and height of the transmitting antenna and the path information are used to obtain an arrival phase difference information table corresponding to each sharpness β and a virtual high H' value. S4. The sharpness β and the virtual high H' value of the point where the phase of the actual measured signal is closest to that of the simulated signal are obtained by looking up the table, and the path low ionosphere information is obtained. The invention can realize accurate detection of the D layer of the ionosphere at any time, solve the multi-value problem in amplitude positioning, and further improve the detection accuracy of the D layer of the ionosphere.

The invention discloses an iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method, and belongs to the technical field of low ionosphere detection. According to the iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method, an iron resonance fluorescence laser radar simulation model is constructed, and photon echo signals are simulated in combination with an NRLMSIS-00 atmosphere model and actually measured iron atom density data; analyzing the influence of laser frequency jitter and light quantum noise on the inversion precision by adopting a Monte Carlo method; then, the error performance of a frequency scanning method and the error performance of a three-frequency ratio method are compared, it is proved that the error of the frequency scanning method in temperature inversion is lower, and the iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method can provide guidance for systematic error modeling and parameter design of an iron resonance fluorescence laser radar; and the accuracy of atmospheric temperature and wind speed inversion can be improved.