Ionized layer disturbance monitoring method and cloud platform

Abstract

According to the ionosphere disturbance monitoring method and the cloud platform, ionosphere disturbance monitoring calculation is carried out through the cloud platform aiming at the situation that the data volume of a base station site is large, the cloud computing power advantage is exerted, and high cost and high power consumption of positioning terminal calculation are avoided; a multi-frequency multi-system observation data real-time stream of which the sampling rate is greater than a preset frequency is utilized to solve a high-precision observation station satellite oblique path ionospheric delay (STEC), so that a disturbance monitoring result is ensured to be stable and credible; according to a receiver end hardware delay deviation (DCB) and oblique path ionosphere delay after ambiguity is fixed, an ionosphere TEC change rate index (ROTI) and a vertical total electron content (VTEC) are calculated, an ionosphere disturbance index is calculated according to the ROTI and the VTEC, and on the basis, the ionosphere disturbance intensity and the electron density are comprehensively considered in disturbance monitoring, so that the disturbance monitoring accuracy is improved. The change of the ionized layer under the interaction of disturbance and electron density is accurately captured, and the accuracy of disturbance monitoring is improved.

Description

Technical Field

[0001] This article relates to satellite positioning technology, and in particular to a method and cloud platform for monitoring ionospheric disturbances. Background Art

[0002] The ionosphere is an important component of the Earth's upper atmosphere, with an altitude of approximately 60-1000 kilometers from the ground. It is an important research area for space weather. There are a large number of free electrons and ions in the ionosphere, which is of great significance for studying the temporal and spatial variations of the ionosphere, satellite navigation and positioning, and electromagnetic signal propagation. Ionospheric delay is one of the most serious sources of error in the navigation and positioning services of the Global Navigation Satellite System (GNSS). The ionospheric total electron content (TEC) is the sum of the number of free electrons within the entire ionospheric height range per unit area. It can directly characterize the impact of ionospheric magnetic storms on satellite navigation and is one of the important physical parameters that characterize the state of the ionosphere. The ionospheric delay is proportional to the size of TEC.

[0003] There is a complex and close connection between solar activity, geomagnetic activity and the ionosphere. Severe solar activity, such as coronal mass ejections and sunspots, will not only lead to sudden ionospheric disturbances (SIDs), but also cause changes in the Earth's magnetic field, leading to geomagnetic storms. Ionospheric gradient anomalies caused by sudden ionospheric disturbances will eventually affect L-band GNSS positioning. Ionospheric scintillation often occurs in high and low latitudes, which can reduce the quality of GNSS observations, increase cycle slips and the probability of loss of lock, thereby affecting GNSS high-precision positioning. As GNSS develops towards multi-frequency, multi-system, multi-constellation and high sampling rate, its all-weather, high-precision, high-efficiency, high-reliability and low-cost characteristics have been widely used in ionospheric disturbance monitoring, providing extensive data support for ionospheric disturbance monitoring; the non-differential non-combined PPP technology combined with precise ephemeris and clock error has greatly improved the accuracy of ionospheric parameter solution; technologies such as the Global Ionospheric Model (GIM) and tropospheric delay correction provide reliable background data and error elimination methods for ionospheric disturbance monitoring; in addition, the introduction of high-performance computing and data fusion algorithms meets the needs of real-time processing of large-scale GNSS data, further improving the efficiency and accuracy of ionospheric disturbance monitoring.

[0004] At present, ionospheric disturbance monitoring is subject to factors such as ionospheric TEC accuracy, quantitative classification of disturbance indicators, and computational efficiency and reliability of algorithms. Among them, ionospheric TEC accuracy is the prerequisite for building a reliable ionospheric disturbance monitoring model. Ionospheric TEC accuracy is affected by multiple error sources such as pseudorange, carrier, satellite clock error, orbit error and hardware delay. The pseudorange observation value has large noise and is significantly affected by the multipath effect, resulting in poor accuracy and reliability of the extracted ionospheric TEC. Phase-smoothed pseudorange can effectively weaken the influence of pseudorange multipath and observation noise, making the ionospheric TEC accuracy higher, but it is easily affected by the length of the smoothing arc segment. Ionospheric disturbances have multi-scale and multi-morphological characteristics. How to achieve reliable and stable ionospheric disturbance monitoring is a problem to be solved. Summary of the invention

[0005] The present application provides a method for monitoring ionospheric disturbances, including: The cloud platform solves the DCB at the satellite end and the DCB at the receiver end according to the real-time stream of multi-frequency and multi-system observation data, wherein the sampling rate of the real-time stream of multi-frequency and multi-system observation data is greater than the preset frequency; According to the real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data, the slant path ionospheric delay STEC of the ionospheric piercing point of the station is determined. In the process of determining the ionospheric piercing point STEC of the station, the ionospheric delay of the ionospheric piercing point of the station is obtained after the ambiguity is fixed; According to the resolved receiver DCB, the determined station ionospheric piercing point STEC and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, the ionospheric TEC rate of change index ROTI and the vertical total electron content VTEC are calculated; The ionospheric disturbance information is determined based on the calculated ROTI and VTEC.

[0006] On the other hand, an embodiment of the present application further provides a computer storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned method of ionospheric disturbance monitoring is implemented.

[0007] On the other hand, an embodiment of the present application further provides a terminal, comprising: a memory and a processor, wherein the memory stores a computer program; wherein: The processor is configured to execute the computer program in the memory; When the computer program is executed by the processor, the method for monitoring ionospheric disturbances as described above is implemented.

[0008] On the other hand, the embodiment of the present application also provides a cloud platform for ionospheric disturbance monitoring, including: a solution unit, a determination unit, a calculation unit and a monitoring processing unit; wherein, The solving unit is configured to solve the DCB at the satellite end and the DCB at the receiver end according to the real-time stream of multi-frequency and multi-system observation data, wherein the sampling rate of the real-time stream of the multi-frequency and multi-system observation data is greater than a preset frequency; The determination unit is set to: determine the slant path ionospheric delay STEC of the ionospheric piercing point of the measuring station according to the real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data, and obtain the ionospheric delay of the ionospheric piercing point of the measuring station after the ambiguity is fixed in the process of determining the ionospheric piercing point STEC of the measuring station; The calculation unit is set as follows: according to the resolved receiver DCB, the determined station ionospheric piercing point STEC and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, the ionospheric TEC change rate index ROTI and the vertical total electron content VTEC are calculated; The monitoring processing unit is configured to determine ionospheric disturbance information based on the calculated ROTI and VTEC.

[0009] In view of the huge amount of data at the base station site, the disclosed embodiment uses a cloud platform to perform calculations for ionospheric disturbance monitoring, takes advantage of cloud computing power, and avoids the cost and high power consumption of using a positioning terminal for calculations; uses a real-time stream of multi-frequency and multi-system observation data with a sampling rate greater than a preset frequency to calculate a high-precision station satellite slant path ionospheric delay (STEC), thereby ensuring that the results of ionospheric disturbance monitoring are stable and reliable; calculates the ionospheric TEC rate of change index (ROTI) and the vertical total electron content (VTEC) based on the receiver-side differential code bias (DCB), the station ionospheric piercing point STEC, and the station ionospheric piercing point ionospheric delay after ambiguity is fixed, and calculates the ionospheric disturbance index based on ROTI and VTEC. Based on this, ionospheric disturbance monitoring comprehensively considers the intensity of ionospheric disturbance and the level of electron density, accurately captures the ionospheric changes under the interaction of disturbance and electron density, and improves the accuracy of ionospheric disturbance monitoring.

[0010] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by implementing the present application. Other advantages of the present application can be realized and obtained by the schemes described in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to provide an understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0012] Figure 1 A flowchart of a method for monitoring ionospheric disturbances according to an embodiment of the present disclosure; Figure 2This is a structural block diagram of a cloud platform for ionospheric disturbance monitoring according to an embodiment of the present disclosure; Figure 3 It is a schematic diagram of the structure of the system for monitoring ionospheric disturbances according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0013] The present application describes multiple embodiments, but the description is exemplary rather than restrictive, and it is obvious to those skilled in the art that there may be more embodiments and implementations within the scope of the embodiments described in the present application. Although many possible feature combinations are shown in the drawings and discussed in the specific embodiments, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with any other feature or element in any other embodiment, or may replace any other feature or element in any other embodiment.

[0014] The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in the present application may also be combined with any conventional features or elements to form a unique invention scheme. Any features or elements of any embodiment may also be combined with features or elements from other invention schemes to form another unique invention scheme. Therefore, it should be understood that any feature shown and / or discussed in the present application may be implemented individually or in any appropriate combination. Therefore, except for the limitations made according to the attached claims and their equivalents, the embodiments are not subject to other restrictions. In addition, various modifications and changes may be made within the scope of protection of the attached claims.

[0015] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not rely on the specific order of the steps described herein, the method or process should not be limited to the steps of the specific order described. As will be understood by those of ordinary skill in the art, other sequences of steps are also possible. Therefore, the specific sequence of the steps set forth in the specification should not be interpreted as a limitation to the claims. In addition, the claims for the method and / or process should not be limited to the steps of performing them in the order written, and those skilled in the art can easily understand that these sequences can be changed and still remain within the spirit and scope of the embodiments of the present application.

[0016] Figure 1 Flow chart of the method for monitoring ionospheric disturbances according to an embodiment of the present disclosure, as shown in FIG. Figure 1 As shown, including: Step 101, the cloud platform solves the satellite-side hardware delay bias (DCB) and the receiver-side DCB according to the real-time stream of multi-frequency and multi-system observation data, wherein the sampling rate of the real-time stream of multi-frequency and multi-system observation data is greater than a preset frequency; Step 102, determining the slant path ionospheric delay (STEC) of the ionospheric piercing point of the station according to the real-time stream of multi-frequency and multi-system observation data, the resolved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data, and determining the ionospheric delay of the ionospheric piercing point of the station after the ambiguity is fixed in the process of STEC of the ionospheric piercing point of the station; Step 103, calculating the ionospheric TEC rate of change index (ROTI) and the vertical total electron content (VTEC) according to the resolved receiver-side DCB, the determined station ionospheric piercing point STEC, and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed; Step 104: Determine ionospheric disturbance information according to the calculated ROTI and VTEC.

[0017] In view of the huge amount of data at the base station site, the disclosed embodiment uses a cloud platform to perform calculations for ionospheric disturbance monitoring, takes advantage of cloud computing power, and avoids the cost and high power consumption of using a positioning terminal for calculations; uses a real-time stream of multi-frequency and multi-system observation data with a sampling rate greater than a preset frequency to calculate a high-precision station satellite slant path ionospheric delay (STEC), thereby ensuring that the results of ionospheric disturbance monitoring are stable and reliable; calculates the rate of change index of total electron content per unit time (ROTI) and vertical total electron content (VTEC) based on the differential code bias (DCB) at the receiver end, the STEC of the station ionospheric piercing point, and the ionospheric delay of the station ionospheric piercing point after the ambiguity is fixed, and calculates the ionospheric disturbance index based on ROTI and VTEC. Based on this, ionospheric disturbance monitoring comprehensively considers the intensity of ionospheric disturbance and the level of electron density, accurately captures the ionospheric changes under the interaction of disturbance and electron density, and improves the accuracy of ionospheric disturbance monitoring.

[0018] In an exemplary instance, the high-precision coordinates in the embodiment of the present disclosure can be the high-precision XYZ coordinates of the GNSS base station in the ITRF20 frame, with an error accurate to millimeters, and the real-time orbit and clock error data are real-time high-precision satellite orbit position data and satellite atomic clock data; the precision and high accuracy in the embodiment of the present disclosure represent that the accuracy reaches a preset error accuracy.

[0019] In an exemplary embodiment, the sampling frequency of the real-time stream of multi-frequency and multi-system observation data of the embodiment of the present disclosure can be 1 Hz to detect smaller-scale ionospheric disturbances; the frequency used in the embodiment of the present disclosure can also be 5s, 30s, etc., which can be set by technical personnel in this field according to the needs of ionospheric disturbance monitoring.

[0020] The high-precision and high-resolution ionospheric disturbance monitoring of the disclosed embodiment can provide a basis for the study of ionospheric anomaly phenomena and the correction of ionospheric delays in fields such as comprehensive and reliable PNT (Positioning Navigation Timing) services and radio communications, and can also effectively prevent the adverse effects of ionospheric anomaly disturbances on human production and life.

[0021] In an exemplary embodiment, before step 101 of solving the DCB at the satellite end and the DCB at the receiver end, the method of the embodiment of the present disclosure further includes: The cloud platform receives real-time streams of multi-frequency and multi-system observation data; multi-frequency and multi-system observation data are positioning data acquired at multiple frequencies through multiple satellite navigation systems (such as GPS, Beidou, GLONASS, and Galileo), generated by GNSS base stations; The real-time stream of multi-frequency and multi-system observation data is saved as the original format file of the International Radio Technical Committee for Maritime Affairs (RTCM), and then converted into an offline RINEX format file.

[0022] In an exemplary instance, the method of the embodiment of the present disclosure further includes: using the RTCM original format file as a backup; the embodiment of the present disclosure uses RTCM as the original format file as a backup so that it can be used during troubleshooting and replay.

[0023] The cloud platform of the disclosed embodiment receives the real-time stream of multi-frequency and multi-system observation data through the network dedicated line NTRIP protocol; the RTCM original format file included in the disclosed embodiment can be converted into an offline RINEX format file according to the RINEX3.04 standard. The disclosed embodiment realizes the real-time reception of massive observation data based on the cloud platform, simplifies the data structure as needed, reduces the broadcast frequency, takes advantage of the storage advantages of the cloud platform, reduces the consumption of chip resources, and reduces the communication cost and the requirements for communication quality.

[0024] After the offline RINEX format file is obtained through conversion in the embodiment of the present disclosure, the processing performed in steps 101 and 102 according to the real-time stream of multi-frequency and multi-system observation data is performed based on the offline RINEX format file.

[0025] In an exemplary instance, the method of the embodiment of the present disclosure further includes: broadcasting the real-time data stream of multi-frequency and multi-system observation data to a downstream application unit according to an internal protocol for performing non-differential and non-combined PPP operation processing.

[0026] In an exemplary embodiment, the embodiment of the present disclosure solves the DCB at the satellite end and the DCB at the receiver end, including: Using the pseudorange and phase observations of the joint geometry-free combination (GF), the phase-smoothed pseudorange is used to obtain the ionospheric TEC, and the satellite DCB and the receiver DCB are jointly solved based on the ionospheric spherical harmonics model. The calculation process of the satellite DCB and the receiver DCB in the embodiment of the present disclosure may include:

[0027] Conventional 30s sampling rate observation data is used to construct GNSS pseudorange and phase observation equations. In the embodiment of the present disclosure, considering only the influence of the first-order term of the ionosphere and other errors, the GNSS pseudorange and phase observation equations are: (1) in, and denote the pseudorange and carrier phase observations of satellite s at frequency j, respectively; is the geometric distance from the receiver r to the satellite s; c is the propagation speed of light in vacuum; and denote the clock differences of the receiver r and the satellite s respectively; represents the ionospheric delay on the observation path from receiver r to satellite s; represents the tropospheric delay on the observation path from receiver r to satellite s; and denote the pseudorange hardware delays of receiver r and satellite s at frequency j respectively; represents the j-frequency carrier phase wavelength; represents the j-frequency carrier phase ambiguity; and denote the phase hardware delay of receiver r and satellite s at frequency j, and Represent the multipath effect errors of pseudorange and carrier respectively; and They represent other errors of pseudorange and carrier phase, including receiver and satellite antenna phase center error, relativistic effect error, earth rotation error, and solid tide and ocean load tide errors.

[0028] The GNSS dual-frequency geometry-free distance combination observation equation is: (2) in, DCB for the receiver; DCB for satellite; is the pseudorange without geometric observation value, The pseudorange observation value at frequency point 1 is: The pseudorange observation value at frequency point 2 is: Ionospheric delay at frequency 1, Ionospheric delay at frequency 2, and Represent the frequencies of the two frequency points used, There is no geometric observation value for the carrier. The wavelength of frequency 1, The wavelength of frequency 2, The fuzziness of frequency point 1, The fuzziness of frequency 2.

[0029] Extracting ionospheric TEC based on carrier phase smoothed pseudorange; The embodiment of the present disclosure constructs a carrier phase smoothed pseudorange equation based on the characteristics that the ionospheric errors of the pseudorange and carrier phase have the same magnitude and opposite signs: (3) in, Represents the parameter after incorporating the phase fractional deviation term into the integer ambiguity.

[0030] GNSS dual-frequency geometry-free observations combined with spherical harmonics are used to model the ionosphere to estimate DCB at the satellite end and DCB at the receiver end. The cutoff elevation angle is 20°, and the ionosphere spherical harmonics model expression is: (4) in, represents the ionospheric piercing point ( , ) at VTEC, and is the latitude and longitude of the ionospheric piercing point in the Sun-solid geomagnetic coordinate system; represents the normalized Legendre function of degree n and order m, represents the maximum degree of spherical harmonics; , are the spherical harmonic model coefficients to be estimated.

[0031] The ionosphere modeling is performed using the GNSS dual-frequency geometry-free observation equation combined with spherical harmonics to estimate the DCB at the satellite end and the DCB at the receiver end. The observation equation is: (5) Where F is the projection function, It is the conversion factor between the hardware delay deviation (DCB) unit ns and TECU. It is the conversion coefficient between the combined observation unit m and TECU. The meanings of the remaining parameters are consistent with those of the previous formula parameters.

[0032] The embodiment of the present disclosure may use a method of adding additional constraints to distinguish hardware delay deviations of satellites and stations, for example, a method of assuming the sum of all satellite hardware delays of each system to be zero as a barycentric reference: ; The least squares adjustment is used to simultaneously estimate the ionospheric spherical harmonic coefficients, the satellite-side DCB, and the receiver-side DCB; in the embodiment of the present disclosure, the satellite-side DCB is added to the normal equation as a virtual observation value, and the observation equation and the error equation are: (6) Among them, the least squares solution , are the coefficients of the ionospheric spherical harmonics model, and B represents the coefficient matrix of the least squares adjustment; In an exemplary embodiment, the disclosed embodiment separates the satellite DCB and the receiver DCB of each system from the estimated satellite DCB and the receiver DCB, and saves them as an offline BSX file.

[0033] In an exemplary embodiment, the present disclosure determines the station ionospheric piercing point STEC, including: The real-time stream of multi-frequency and multi-system observation data, the resolved DCB of the satellite end, high-precision coordinates, real-time orbit and clock error data are solved by the non-differential and non-combined PPP-AR model to obtain the STEC of the ionospheric puncture point of the observation station; Among them, the sampling frequency of the real-time stream of multi-frequency and multi-system observation data includes 1 Hz.

[0034] When the sampling frequency of the real-time stream of multi-frequency and multi-system observation data in the embodiment of the present disclosure is 1 Hz, the corresponding non-difference non-combined PPP-AR model for solving STEC is also 1 Hz high-frequency data, thereby achieving high-precision STEC solution. In an exemplary embodiment, step 102 of the embodiment of the present disclosure, determining the STEC of the ionospheric puncture point of the measuring station, includes:

[0035] Construct the non-differenced non-combined (PPP) observation equation; Commonly used PPP models for precise point positioning include the ionosphere-free combination model, the UofC half-sum model and the non-differenced non-combined model; The ionosphere-free combination model and the UofC half-sum model both form an ionosphere-free combination observation model through the combination of pseudorange and carrier observation values, which weakens the influence of ionospheric delay on positioning accuracy, but also loses some useful information; The non-differenced non-combined model is based on the original observation value and reflects the changes of various errors to the greatest extent. The non-differenced non-combined PPP model retains the slant path ionospheric delay (STEC) as a parameter to be estimated in the observation equation, and extracts the ionosphere delay value while solving other parameters in PPP; The dual-frequency observation equation is constructed based on the real-time stream of S2's 1HZ observation data, and its expression is: (7) in, , They represent the pseudorange and carrier phase observation values ​​of the GNSS signal of satellite S at the corresponding frequency j received by receiver r; represents the geometric distance from the phase center of the satellite antenna to the phase center of the receiver antenna; c is the speed of light in vacuum; and are receiver and satellite clock errors respectively; is the slant path ionospheric delay at frequency 1, is the coefficient of frequency j with reference to the reference frequency 1; is the tropospheric zenith wet delay, is the projection function of the tropospheric zenith wet delay; and represent the pseudorange hardware delays of the receiver and the satellite respectively; is the wavelength of frequency j; is the integer ambiguity corresponding to frequency j; and represent the initial phase deviation and phase hardware delay of the receiver and satellite respectively; and They are the unmodeled errors of pseudorange and phase observations, including multipath error, observation noise, etc. In addition to the errors described above, there are corresponding models to correct errors such as tropospheric zenith delay, antenna phase center deviation (PCO) and antenna phase center variation (PCV) between satellite and receiver, phase winding, relativistic effect, and tide.

[0036] The non-difference non-combined PPP estimation model based on SSR corrections is: (8) in, and The OMC (Observed-minus-computed) values ​​of the pseudorange and carrier observations, respectively. is the unit vector from the receiver to the satellite, is the receiver position correction, It is the receiver clock error that absorbs the receiver pseudorange hardware delay. is the satellite clock error that absorbs the satellite pseudorange hardware delay, is the ionospheric delay at frequency 1 that absorbs the hardware delay between the receiver and the satellite pseudorange. It absorbs the ambiguity of pseudorange and carrier hardware delay. is the pseudorange frequency deviation, is the satellite clock frequency deviation; the precise satellite orbit correction number broadcast by the SSR service is used to correct OMC, It can be obtained from the precise satellite clock correction number. It can also be provided by SSR service. , , , , , is the parameter to be estimated, In the SSR service, it is a pseudo-range clock, which absorbs the satellite pseudo-range hardware delay. Absorbs pseudorange and carrier hardware delays.

[0037] The non-differenced non-combined PPP estimation of the disclosed embodiment can obtain the floating point ambiguity of each frequency point , a hierarchical ambiguity fixing strategy is adopted, that is, the floating point ambiguity of each frequency point is converted into an ultra-wide lane floating point ambiguity and wide lane floating point ambiguity , (9) Using the Uncalibrated Phase Bias (UPD) products provided by SSR, including wide lane UPD and narrow lane UPD products: , and , and eliminate the hardware delay at the receiver end through inter-satellite single difference: , and , which can be achieved , and The ambiguity is fixed and the integer ambiguity is obtained: , , And the integer ambiguity: , ; Substituting the fixed integer ambiguity into formula (8), we can get the ionospheric delay after the ambiguity is fixed and the corresponding floating point ionospheric delay is .

[0038] The ionospheric TEC rate of change index (ROTI) of the disclosed embodiment is defined as the standard deviation of the detrended ROT within a certain time interval, with a unit of TECU / min. ROT is defined as the rate of change of ionospheric TEC on the slant path, with a unit of TEC / min. The ionospheric STEC containing the receiver-side DCB after the ambiguity is fixed is estimated by the non-differenced non-combined PPP-AR model according to the ionospheric TEC. When the adopted frequency of the real-time stream of multi-frequency and multi-system observation data can be 1 Hz, the ionospheric STEC containing the receiver-side DCB also has a sampling rate of 1 Hz. It is necessary to deduct it from the ionospheric STEC according to the obtained receiver-side DCB result to obtain the high-precision STEC information that does not contain the receiver-side DCB for calculating ROTI and VTEC.

[0039] In an exemplary embodiment, the embodiment of the present disclosure calculates the ionospheric TEC rate of change index (ROTI) and vertical total electron content (VTEC) according to the resolved receiver-side DCB, the determined station ionospheric piercing point STEC, and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, including: The ionospheric STEC after the ambiguity is fixed, which is estimated by the non-differenced non-combined PPP-AR model, is deducted from the DCB at the receiver end to obtain the STEC of the satellite received by each station; the ionospheric STEC is deducted from the DCB at the receiver end to obtain the high-precision STEC, which is expressed as: ; Calculate the ionospheric TEC change rate index ROTI; The disclosed embodiment needs to calculate the ionospheric TEC change rate ROT. Assuming that a single station observes N satellites, satellites with a cutoff elevation angle greater than 30° are screened, and their STEC is inter-epoch difference to obtain N-1 ROT values. The calculation formula is: (10) To ensure that the calculated ROTI result is continuous and reliable, the embodiment of the present disclosure calculates ROTI according to a sliding window of a preset duration. It is necessary to ensure that each window has more than 50 ROTs before calculating ROTI. The ROTI calculation formula is: (11) in, Represents the ROT mean within a 5-minute window; the preset duration in the embodiment of the present disclosure may be 1 minute or 5 minutes. In order to better detect small-scale ionospheric disturbances, the preset duration is 1 minute.

[0040] The ionospheric STEC of the disclosed embodiment can be calculated by a triangular projection function Converted to VTEC, the formula is: (12) Where Z is the satellite zenith distance; the projection function The formula is: , , , R is the radius of the earth.

[0041] In an exemplary embodiment, step 104 of the disclosed embodiment determines ionospheric disturbance information according to the calculated ROTI and VTEC, including: The calculated ROTI and VTEC are weighted and accumulated according to the preset weighting strategy to obtain the index information of ionospheric disturbance.

[0042] In an exemplary embodiment, the index information of the ionospheric disturbance in the embodiment of the present disclosure is , whose expression is: (13) in, , is the weight coefficient, which can be fitted using a regression model. Indicates the duration of the sliding window, in min.

[0043] In an exemplary embodiment, the embodiment of the present disclosure performs weighted accumulation calculation on the calculated ROTI and VTEC according to a preset weighting strategy to obtain index information of ionospheric disturbance, including: Divide the ionospheric disturbance monitoring area into grids according to the preset spatial resolution to obtain grid units; for example, divide the grid units into grid units according to the spatial resolution of 1°×1°. The resolution can be adjusted according to the computing power. The smaller the grid division, the higher the computing power requirement. Traverse and determine each grid cell, and determine the corresponding ROTI and VTEC within the grid cell; Based on the determined ROTI and VTEC within the grid cell range, the ionospheric disturbance index information IonLevel of each grid cell is calculated using the time-based inverse distance weighted strategy (IDW).

[0044] In an exemplary embodiment, the embodiment of the present disclosure divides the ionospheric disturbance into the following four disturbance levels according to the value of IonLevel: When IonLevel is less than the first level threshold, the ionospheric disturbance is classified as calm; when IonLevel is greater than or equal to the first level threshold and less than the second level threshold, the ionospheric disturbance is classified as primary disturbance; when IonLevel is greater than or equal to the second level threshold and less than the third level threshold, the ionospheric disturbance is classified as moderate disturbance; when onLevel is greater than or equal to the third level threshold, the ionospheric disturbance is classified as severe disturbance.

[0045] In an exemplary embodiment, the first level threshold, the second level threshold and the third level threshold of the embodiment of the present disclosure can be set and adjusted by a technician; for example, the first level threshold can be set to 2, the second level threshold can be set to 3, and the third level threshold can be set to 4.

[0046] In an exemplary embodiment, the method of the present disclosure further includes: The divided disturbance levels are sent to the positioning terminal so as to display the disturbance levels on the positioning terminal; wherein the positioning terminal displays the disturbance levels in a manner including: displaying in a grid map manner.

[0047] In an exemplary embodiment, the method of the embodiment of the present disclosure further includes: displaying a grid corresponding to the user location through a preset interactive interface according to the received user location and time information, and one or any combination of the following information of the received time information: ROTI, VTEC and ionospheric disturbance information. The preset interactive interface of the embodiment of the present disclosure may be a positioning terminal.

[0048] The disclosed embodiment only requires the user to query the reference ionospheric disturbance information scenario, and the ionospheric disturbance information can be displayed in the following two ways according to the location and time information provided by the user: one is to obtain the ROTI, VTEC and ionospheric disturbance index information of the ionosphere of the grid unit where the location is located according to the location and time information, which can be displayed in a bar chart time series; the other is to display the ionospheric disturbance index information at the current moment through the full-area ionospheric disturbance monitoring grid map displayed on the web page.

[0049] In an exemplary embodiment, the method of the embodiment of the present disclosure further includes: obtaining the index information of the ionospheric disturbance of the current epoch, and when a preset level of disturbance is determined according to the index information of the ionospheric disturbance, reminding the customer to pay attention to the positioning accuracy of the current epoch. The embodiment of the present disclosure can also transmit ROTI and VTEC to the positioning terminal for the user to perform positioning accuracy analysis.

[0050] The disclosed embodiments break through the limitations of standardized protocols, adaptively and flexibly implement deep coupling algorithms, improve service robustness, provide various types of correction data quality factors (QI) on the cloud side, and perform algorithm adaptation on the chip terminal side.

[0051] The embodiment of the present disclosure also provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned method of ionospheric disturbance monitoring is implemented.

[0052] The embodiment of the present disclosure further provides a terminal, comprising: a memory and a processor, wherein a computer program is stored in the memory; The processor is configured to execute the computer program in the memory; When the computer program is executed by a processor, the method for monitoring ionospheric disturbance as described above is implemented.

[0053] Figure 2 The structure block diagram of the cloud platform for ionospheric disturbance monitoring according to the embodiment of the present disclosure is as follows: Figure 2 As shown, it includes: a solving unit, a determining unit, a calculating unit and a monitoring processing unit; wherein, The solving unit is configured to solve the satellite-side hardware delay deviation DCB and the receiver-side DCB according to the real-time stream of multi-frequency and multi-system observation data, wherein the sampling rate of the real-time stream of the multi-frequency and multi-system observation data is greater than a preset frequency; The determination unit is set to: determine the slant path ionospheric delay STEC of the ionospheric piercing point of the measuring station according to the real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates and the real-time orbit and clock error data, and obtain the ionospheric delay of the ionospheric piercing point of the measuring station after the ambiguity is fixed in the process of determining the ionospheric piercing point STEC of the measuring station; The calculation unit is set as follows: according to the resolved receiver DCB, the determined station ionospheric piercing point STEC and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, the ionospheric TEC change rate index ROTI and the vertical total electron content VTEC are calculated; The monitoring processing unit is configured to determine ionospheric disturbance information based on the calculated ROTI and VTEC.

[0054] In an exemplary embodiment, the sampling frequency of the real-time stream of multi-frequency and multi-system observation data in the embodiment of the present disclosure is 1 Hz.

[0055] In an exemplary embodiment, the cloud platform of the embodiment of the present disclosure further includes a receiving processing unit, which is configured to: Receiving a real-time stream of multi-frequency and multi-system observation data, wherein the multi-frequency and multi-system observation data is positioning data acquired at multiple frequencies through multiple satellite navigation systems and is generated by a GNSS base station; The real-time stream of multi-frequency and multi-system observation data is saved as the original format file of the International Radio Technical Committee for Maritime Affairs (RTCM), and then converted into an offline RINEX format file.

[0056] In an exemplary embodiment, the determination unit of the embodiment of the present disclosure is configured as follows: The real-time stream of multi-frequency and multi-system observation data, the resolved DCB of the satellite end, high-precision coordinates, real-time orbit and clock error data are solved by the non-differential and non-combined PPP-AR model to obtain the STEC of the ionospheric puncture point of the observation station; Among them, the sampling frequency of the real-time stream of multi-frequency and multi-system observation data includes 1 Hz.

[0057] When the sampling frequency of the real-time stream of multi-frequency and multi-system observation data in the embodiment of the present disclosure is 1 Hz, correspondingly, the non-difference non-combination PPP-AR model for solving STEC is also 1 Hz high-frequency data, thereby achieving high-precision STEC solution.

[0058] In an exemplary embodiment, the calculation unit of the embodiment of the present disclosure is configured to: calculate ROTI according to a sliding window of a preset duration; wherein the preset duration includes 1 minute.

[0059] In an exemplary embodiment, the monitoring processing unit of the embodiment of the present disclosure is configured as follows: The calculated ROTI and VTEC are weighted and accumulated according to the preset weighting strategy to obtain the index information of ionospheric disturbance.

[0060] In an exemplary embodiment, the monitoring processing unit of the embodiment of the present disclosure is configured to perform weighted accumulation calculation on the calculated ROTI and VTEC according to a preset weighting strategy to obtain index information of ionospheric disturbance, including: Divide the ionospheric disturbance monitoring area into grids according to a preset spatial resolution to obtain grid units; Traverse and determine each grid cell, and determine the corresponding ROTI and VTEC within the grid cell; Based on the determined ROTI and VTEC within the grid cell range, the index information of ionospheric disturbance of each grid cell is calculated using the time-sensitive inverse distance weighted (IDW) strategy.

[0061] In an exemplary embodiment, the index information of the ionospheric disturbance in the embodiment of the present disclosure is , the expression is: ; in, and is the weight coefficient, It is the duration of the sliding window, in min.

[0062] In an exemplary embodiment, the monitoring processing unit of the embodiment of the present disclosure is further configured to classify the ionospheric disturbance into the following disturbance levels according to the value of IonLevel: When IonLevel is less than the first level threshold, the ionospheric disturbance is classified as calm; when IonLevel is greater than or equal to the first level threshold and less than the second level threshold, the ionospheric disturbance is classified as primary disturbance; when IonLevel is greater than or equal to the second level threshold and less than the third level threshold, the ionospheric disturbance is classified as moderate disturbance; when IonLevel is greater than or equal to the third level threshold, the ionospheric disturbance is classified as severe disturbance.

[0063] In an exemplary embodiment, the monitoring processing unit of the embodiment of the present disclosure is further configured to: sending the divided disturbance levels to a positioning terminal so as to display the disturbance levels on the positioning terminal; The manner in which the positioning terminal displays the disturbance level includes: displaying in a grid map manner.

[0064] In an exemplary embodiment, the monitoring processing unit of the embodiment of the present disclosure is further configured to: According to the received user location and time information, the grid cell corresponding to the user location and the corresponding time information are displayed through a preset interactive interface, and the following information or any combination thereof: ROTI, VTEC and ionospheric disturbance information.

[0065] In an exemplary embodiment, the cloud platform and the positioning terminal of the embodiment of the present disclosure can form a system for ionospheric disturbance monitoring.

[0066] The following briefly describes the embodiments of the present disclosure through application examples. The application examples are only used to illustrate the embodiments of the present disclosure and are not used to limit the protection scope of the embodiments of the present disclosure.

[0067] Application Examples Figure 3 The present invention is a schematic diagram of the structure of a system for implementing ionospheric disturbance monitoring in an application example of the present invention, including a cloud platform for ionospheric disturbance monitoring and a positioning terminal; wherein the cloud platform for ionospheric disturbance monitoring establishes a communication connection with more than two GNSS base stations (for example, more than 500).

[0068] According to actual computing power and hardware resources, the cloud platform for ionospheric disturbance monitoring in the application example of the present disclosure includes: a data center module, a non-differential non-combined PPP-AR module and a real-time ionospheric monitoring module; wherein, The data center module is used to implement the functions to be realized by the above-mentioned receiving and processing unit; A non-difference non-combination PPP-AR module, used to implement the functions of the above-mentioned solution unit and determination unit; A real-time ionosphere monitoring module, used to implement the functions of the above-mentioned calculation unit and monitoring processing unit; The positioning terminal may include a chip terminal and a host computer terminal; wherein, The positioning terminal can receive the following information or any combination of information that the host terminal can use to display ionospheric disturbance monitoring: ROTI, VTEC and ionospheric disturbance information, and can also be set with the function of issuing an alarm based on the ionospheric disturbance information; The host terminal can be used to display one or any combination of the following information of ionospheric disturbance monitoring: ROTI, VTEC and ionospheric disturbance information. It can display part of the information according to the user's location and time, or display all the information.

[0069] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A method for monitoring ionospheric disturbances, characterized in that: include: The cloud platform solves the satellite-side hardware delay deviation DCB and the receiver-side DCB based on the real-time stream of multi-frequency and multi-system observation data, where the sampling rate of the real-time stream of multi-frequency and multi-system observation data is greater than the preset frequency; According to the real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data, the slant path ionospheric delay STEC of the ionospheric piercing point of the station is determined. In the process of determining the ionospheric piercing point STEC of the station, the ionospheric delay of the ionospheric piercing point of the station is obtained after the ambiguity is fixed; According to the resolved receiver DCB, the determined station ionospheric piercing point STEC and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, the ionospheric TEC rate of change index ROTI and the vertical total electron content VTEC are calculated; The ionospheric disturbance information is determined based on the calculated ROTI and VTEC.

2. The method according to claim 1, characterized in that: The sampling frequency of the real-time stream of multi-frequency and multi-system observation data is 1 Hz.

3. The method according to claim 1, characterized in that Before solving the satellite-side DCB and the receiver-side DCB, the method further includes: The cloud platform receives the real-time stream of multi-frequency and multi-system observation data, wherein the multi-frequency and multi-system observation data is positioning data acquired at multiple frequencies by multiple satellite navigation systems and is generated by a GNSS base station; The real-time stream of the multi-frequency and multi-system observation data is saved as an original format file of the International Radio Technical Committee for Maritime Affairs RTCM, and then converted into an offline RINEX format file.

4. The method according to claim 1, characterized in that The method of determining the slant path ionospheric delay STEC of the ionospheric puncture point of the measuring station comprises: The real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data are solved by the non-difference non-combined PPP-AR model to obtain the ionospheric puncture point STEC of the observation station; Wherein, the sampling frequency of the real-time stream of multi-frequency and multi-system observation data includes 1 Hz.

5. The method according to claim 1, characterized in that Calculate the ROTI according to a sliding window of a preset duration; Among them, the preset duration includes 1 minute.

6. The method according to any one of claims 1 to 5, characterized in that: Determining the ionospheric disturbance information according to the calculated ROTI and VTEC includes: The calculated ROTI and VTEC are weighted and accumulated according to a preset weighting strategy to obtain index information of ionospheric disturbance.

7. The method according to claim 6, characterized in that The calculated ROTI and VTEC are weighted and accumulated according to a preset weighting strategy to obtain index information of ionospheric disturbance, including: Dividing the ionospheric disturbance monitoring area into grids according to a preset spatial resolution to obtain grid units; Traversing and determining each of the grid cells, and determining the corresponding ROTI and VTEC within the range of the grid cells; According to the determined ROTI and VTEC within the range of the grid cell, the index information of the ionospheric disturbance of each grid cell is calculated by adopting the inverse distance weighting strategy IDW taking into account time.

8. The method according to claim 6, characterized in that The index information of the ionospheric disturbance is , the expression is: ； in, and is the weight coefficient, is the duration of the sliding window, in minutes.

9. The method according to claim 8, characterized in that The method further comprises classifying the ionospheric disturbance into the following disturbance levels according to the value of IonLevel: When the IonLevel is less than the first level threshold, the ionospheric disturbance is classified as calm; When the IonLevel is greater than or equal to the first level threshold and less than the second level threshold, the ionospheric disturbance is classified as a primary disturbance; When the IonLevel is greater than or equal to the second level threshold and less than the third level threshold, the ionospheric disturbance is classified as a medium disturbance; The IonLevel is greater than or equal to the third level threshold, and the ionospheric disturbance is classified as a severe disturbance.

10. The method according to claim 9, characterized in that The method further comprises: sending the divided disturbance levels to a positioning terminal so as to display the disturbance levels on the positioning terminal; The manner in which the positioning terminal displays the disturbance level includes: displaying in a grid map manner.

11. The method according to claim 7, characterized in that The method further comprises: According to the received user location and time information, the grid unit corresponding to the user location and the corresponding time information are displayed through a preset interactive interface, and the following one or any combination of information: the ROTI, the VTEC and the ionospheric disturbance information.

12. A cloud platform for ionospheric disturbance monitoring, comprising: A solving unit, a determining unit, a calculating unit and a monitoring processing unit; wherein, The solving unit is configured to solve the satellite-side hardware delay deviation DCB and the receiver-side DCB according to the real-time stream of multi-frequency and multi-system observation data, wherein the sampling rate of the real-time stream of the multi-frequency and multi-system observation data is greater than a preset frequency; The determination unit is set to: determine the slant path ionospheric delay STEC of the ionospheric piercing point of the measuring station according to the real-time stream of multi-frequency and multi-system observation data, the solved DCB of the satellite end, the high-precision coordinates, the real-time orbit and the clock error data, and obtain the ionospheric delay of the ionospheric piercing point of the measuring station after the ambiguity is fixed in the process of determining the ionospheric piercing point STEC of the measuring station; The calculation unit is set as follows: according to the resolved receiver DCB, the determined station ionospheric piercing point STEC and the obtained station ionospheric piercing point ionospheric delay after the ambiguity is fixed, the ionospheric TEC change rate index ROTI and the vertical total electron content VTEC are calculated; The monitoring processing unit is configured to determine ionospheric disturbance information based on the calculated ROTI and VTEC.

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