A method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles

Abstract

The present invention provides a method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles, comprising: obtaining GNSS observation data and navigation message files, parsing ionospheric related parameters; using a multi-resolution ionospheric tomography algorithm to obtain the electron density distribution of the inversion region, reconstructing the TEC distribution image of the inversion region, and judging whether plasma bubbles appear in combination with the TEC distribution image; if the plasma bubble phenomenon appears, obtaining continuous measurement data of the GNSS satellite within the measurement time period by a GNSS receiver, and preprocessing these measurement data, calculating the ionospheric delay according to the processed measurement data; calculating the ionospheric TEC spatial gradient value, and determining the ionospheric TEC spatial gradient value generated by the plasma bubble. The present invention fully and systematically determines the ionospheric TEC spatial gradient value generated by the plasma bubble. The whole process is simple and easy to execute, and the result is accurate.

Description

Technical Field

[0001] The present invention belongs to the technical field of ionosphere monitoring, and in particular relates to a method for detecting ionosphere TEC spatial gradient caused by plasma bubbles. Background Art

[0002] During severe ionospheric activity, extreme ionospheric disturbances pose an integrity threat to users of the Global Navigation Satellite System (GNSS) and Ground-Based Augmentation System (GBAS). The TEC spatial gradient caused by ionospheric anomalies seriously affects the safety of aircraft landing. Therefore, a method to detect the ionospheric TEC spatial gradient caused by plasma bubbles is necessary.

[0003] Existing technologies can be used to reduce ionospheric delay errors to a negligible level in practical operations using differential corrections from the Ground-Based Augmentation System (GBAS). However, when ionospheric anomalies occur, the differential corrections provided by GBAS ground stations cannot reduce the ionospheric error to a safe level. Ionospheric anomalies often occur in low-latitude regions. For example, plasma bubbles generated in the ionosphere after sunset can pose a significant safety hazard to GBAS-guided aircraft landings. Therefore, a method is needed to detect the TEC spatial gradient caused by plasma bubbles. For GBAS systems facing ionospheric anomaly threats such as plasma bubbles, a short-baseline dual-station method and a time-step method are used to determine the TEC spatial gradient caused by ionospheric anomalies. Multi-resolution ionospheric tomography is then used to invert the TEC distribution image at the time of the anomaly to determine whether the plasma bubble is the cause. Finally, the TEC spatial gradient caused by the plasma bubble is determined.

[0004] Ionospheric tomography utilizes modern satellite navigation resources and establishes a network of ground-based receiving stations to perform tomographic scanning of vast spatial regions. Ionospheric electron density is then inverted using tomography and ionospheric slant-range TEC information, yielding spatial distribution images of physical parameters such as ionospheric electron density. As an all-weather, large-scale ionospheric detection technology, ionospheric tomography offers numerous advantages, including low cost, ease of operation, and a wide detection range. It is of great significance for monitoring ionospheric structural changes at various scales and the global ionospheric environment. With the development of ionospheric tomography, the accuracy of tomographic inversion has also improved, and the inversion results are gradually approaching the ideal state. Therefore, using tomography to analyze ionospheric anomalies is reliable.

[0005] Plasma bubbles are ionospheric plasma density depletions frequently observed at night in equatorial and low-latitude regions. Rayleigh-Taylor instabilities, caused by ion disturbances, are widely believed to be the mechanism responsible for their appearance. Plasma bubbles are a common ionospheric anomaly in low-latitude regions. They represent a localized ionospheric depletion, with large ionospheric TEC spatial gradients at their edges, posing a threat to GBAS performance. Therefore, developing a method to detect ionospheric TEC spatial gradients caused by plasma bubbles is of great significance. Summary of the Invention

[0006] In view of this, the present invention provides a method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles, which can accurately determine the ionospheric TEC spatial gradient value generated by plasma bubbles.

[0007] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0008] A method for detecting ionospheric TEC spatial gradient caused by plasma bubbles comprises the following steps:

[0009] Step 1: Obtain GNSS observation data and navigation message files from the IGS data center and parse out ionospheric parameters;

[0010] Step 2: Use the multi-resolution ionospheric tomography algorithm to obtain the electron density distribution in the inversion area, then reconstruct the TEC distribution image of the inversion area and determine whether there are plasma bubbles;

[0011] Step 3: If plasma bubbles occur, obtain continuous measurement data from the GNSS satellite during the measurement period through the GNSS receiver and preprocess the measurement data;

[0012] Step 4: Calculate the ionospheric delay based on the processed measurement data;

[0013] Step 5: Calculate the ionospheric TEC spatial gradient value using the obtained ionospheric delay value and determine the ionospheric TEC spatial gradient value parameters generated by the plasma bubble.

[0014] Furthermore, in step 2, using a multi-resolution ionospheric tomography algorithm to obtain the electron density distribution in the inversion region, and then reconstructing the TEC distribution image of the inversion region includes:

[0015] The tilted total electron content required for the multi-resolution ionospheric tomography algorithm is calculated using GNSS observation data;

[0016] Based on the above tilted total electron content, the ionospheric electron density is obtained by inversion using a multi-resolution ionospheric tomography algorithm;

[0017] The ionospheric TEC distribution image is reconstructed based on the electron density obtained above.

[0018] Furthermore, in step 5, the obtained ionospheric delay value is used to calculate the ionospheric TEC spatial gradient value using the short baseline dual-station method or the time step method to determine the ionospheric TEC spatial gradient value parameters generated by the plasma bubble.

[0019] Furthermore, the short baseline dual-station method is used to calculate the ionospheric TEC spatial gradient value, and the ionospheric TEC spatial gradient value parameters generated by the plasma bubble are determined specifically including:

[0020] During the measurement period, two different GNSS receivers are selected to observe the same GPS satellite. Based on the processed measurement data, the ionospheric delay values in the slant range domain between the two receivers and the satellite are calculated. The baseline distance between the two GNSS receivers is less than 45 kilometers.

[0021] Based on the ionospheric thin shell model, the ionospheric delay values in the slant range domain on the line of sight between the two receivers and the satellite are converted into ionospheric delay values in the vertical domain;

[0022] The ionospheric TEC spatial gradient value is calculated based on the ionospheric delay in two vertical domains using the short baseline dual-station method, and finally the magnitude of the ionospheric TEC spatial gradient value generated by the plasma bubble is determined.

[0023] Furthermore, the time step method is used to calculate the ionospheric TEC spatial gradient value, and determining the ionospheric TEC spatial gradient value parameters generated by the plasma bubble specifically includes:

[0024] Selecting two different moments within a measurement period, and calculating the ionospheric delay values of the GNSS satellite in the slant range domain at the two different moments based on the processed measurement data;

[0025] Based on the ionospheric thin shell model, the ionospheric delays in the two slant range domains are converted into ionospheric delay values in two vertical domains respectively;

[0026] The ionospheric TEC spatial gradient value is calculated according to the ionospheric delays in the two vertical domains using a time step method, and finally the ionospheric TEC spatial gradient value generated by the plasma bubble is determined.

[0027] Compared with the prior art, the method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles described in the present invention has the following advantages: the present invention first uses multi-resolution ionospheric tomography technology to reconstruct the TEC distribution image to determine whether a plasma bubble phenomenon occurs. If a plasma bubble phenomenon occurs, the present invention then obtains continuous measurement data from the GNSS satellite during the measurement period for preprocessing, removes low-elevation angle data with large errors due to factors such as multipath interference, and removes satellite and receiver hardware deviations to obtain more accurate measurement data. Based on the processed measurement data, the ionospheric delay value of the GNSS satellite using the two methods is calculated, and then the TEC spatial gradient value generated by the plasma bubble is determined based on the ionospheric delay value. This method establishes a method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles. The entire detection process is simple and easy to perform. The results obtained by the two different methods for detecting the plasma bubble gradient are almost the same, confirming the accuracy of the TEC spatial gradient caused by the plasma bubble. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0029] Figure 1 A flow chart of a method for detecting ionospheric TEC spatial gradients caused by plasma bubbles provided in an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a method for determining the ionospheric TEC spatial gradient provided by an embodiment of the present invention;

[0031] Figure 3 Schematic diagram of the ionospheric TEC spatial gradient caused by plasma bubbles provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0033] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0034] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0035] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0036] like Figure 1-2 As shown, the present invention provides a method for detecting the ionospheric TEC spatial gradient caused by plasma bubbles, which specifically includes the following steps:

[0037] Step 1: Obtain GNSS observation data and navigation message files from the IGS data center;

[0038] Step 2: Obtain the ionosphere-related parameters required by the multi-resolution ionosphere tomography algorithm;

[0039] Step 3: Use a multi-resolution ionospheric tomography algorithm to invert the regional electron density distribution, then reconstruct the TEC distribution image and determine whether plasma bubbles appear;

[0040] Specifically include:

[0041] Step 301: Calculate the STEC in the slant range domain required by the ionospheric tomography algorithm using GNSS observation data;

[0042] The GPS measurement data recorded in the GNSS receiver RINEX file contains the following information:

[0043] Code pseudorange information (P1 and P2)

[0044]

[0045]

[0046] Information on carrier phase measurements (L1 and L2)

[0047]

[0048]

[0049] Where P1 and P2 are pseudorange measurements obtained from the precise code, L1 and L2 represent the carrier phase measurements of the signal, P0 represents the ionosphere-free pseudorange, f1 and f2 represent the first and second carrier signal frequencies of GPS, n1 and n2 represent the integer ambiguities observed using the first and second carrier frequencies, λ1 and λ2 represent the carrier wavelengths corresponding to the first and second carrier signal frequencies of GPS, and ε1 and ε2 represent the hardware biases of the satellite and receiver, respectively.

[0050]

[0051]

[0052] The slant total electron content STEC is calculated by the noise term in equation (5) or by the bias term of the integer ambiguity associated with it in equation (6).

[0053] Step 302: Based on the above-mentioned tilted total electron content STEC, the ionospheric electron density X is obtained by inversion using a multi-resolution ionospheric tomography algorithm; specifically,

[0054] First, the ionosphere is divided into grids. Let the transmission path between the GNSS satellite and the GNSS receiver be h, and the vertical intercept of the radio wave ray when it passes through each voxel be H1, H2...H i ..., assuming that the electron density in each grid is a constant value X1, X2...X i ..., then the tilted total electron content STEC in the unit grid is H i X i , then the inclined total electron content on a ray obtained in step 301 can be considered as the sum of the products of the intercept of the line of sight passing through the grid and the electron density in the corresponding grid, that is, STEC=H1X1+H2X2+......+H i X i +......;

[0055] Then the total electron content on all lines of sight is Z = HX, where X is the required ionospheric electron density, and H is the intercept matrix of all rays passing through the grid. In order to solve the problem of incomplete paths through the grid, the IRI model is used to construct an empirical orthogonal function and a compensation mapping matrix M, and the compensation mapping matrix M is regularized. At this time, the equation HX = Z becomes (HM)X = Z, where X is the solution of the transformed basis set. Then the regularization matrix R is introduced to construct the normal equation H T H+KR T R=H T Z, where K represents the user-defined regularization constant. Finally, the solution of the normal equation is calculated using the minimum residual method to obtain the electron density X of the original basis;

[0056] Step 303: reconstructing the ionospheric TEC distribution image based on the original basis electron density X obtained above;

[0057] Step 4: Obtain continuous measurement data of the GNSS satellite during the measurement period through the GNSS receiver;

[0058] Step 5: Preprocess the measurement data to obtain processed measurement data.

[0059] Step 6: Calculate the ionospheric delay value based on the processed measurement data.

[0060] Step 7: Calculate the ionospheric TEC spatial gradient value using the obtained ionospheric delay value using the short baseline dual-station method or the time step method to determine the ionospheric TEC spatial gradient value parameters generated by the plasma bubble;

[0061] When IGS receiving stations are densely distributed, two different GNSS receivers (the baseline distance between the two receivers must be less than 45 kilometers) are selected to observe the same GPS satellite during the measurement period. Based on the processed measurement data, the ionospheric delay values in the slant range domain on the line of sight between the two receivers and the satellite are calculated respectively. Based on the ionospheric thin shell model, the ionospheric delays in the two slant range domains are converted into ionospheric delay values in the vertical domain, and the vertical ionospheric delay required for the short-baseline dual-station method is calculated.

[0062] When IGS receiving stations are sparsely distributed, two different moments are selected within the measurement period. Based on the processed measurement data, the ionospheric delay values of the GNSS satellite in the slant range domain at the two different moments are calculated respectively. Based on the ionospheric thin shell model, the ionospheric delays in the two slant range domains are converted into ionospheric delay values in two vertical domains respectively. The vertical ionospheric delay required for the time step method is calculated.

[0063] Specifically include:

[0064] Select a GNSS receiver with good performance to collect observation data with an interval of 30 seconds and calculate the STEC of the radio wave in the line of sight. The specific steps are as follows:

[0065] Based on the observation data collected by the GNSS receiver at an interval of 30 seconds, the carrier phase measurements L1 and L2 in the observation file are extracted, and then the STEC on the line of sight between the satellite and the receiver is calculated using the following formula:

[0066]

[0067] In formula 7), f1 and f2 represent the first carrier signal frequency and the second carrier signal frequency of GPS, respectively. λ1 and λ2 are the carrier signal wavelengths corresponding to the first and second carrier signal frequencies of GPS. L1 and L2 are GPS satellite carrier phase measurement values. Here, the first carrier signal frequency f1 of GPS is selected as 1575.42 MHz, and the second carrier signal frequency f2 of GPS is selected as 1227.60 MHz.

[0068] (b) To obtain more accurate STEC, we need to process the calculated STEC based on the hardware bias of the satellite and receiver. The specific steps are as follows:

[0069] Q is corrected using the following equation (8) and the hardware delay bias correction / differential code biases (DCB) file provided by the IGS official website. GPS Perform the solution:

[0070]

[0071] In formula (8), f1 and f2 are the first and second carrier signal frequencies of GPS; c is the speed of light; and Δt is the sum of the total group delay (TGD) and inter-frequency biases (IFB) in the DCB file.

[0072] The corrected STEC is:

[0073] STEC(t)=STEC(t)+Q GPS (9)

[0074] Based on the processed STEC values, the ionospheric delay values in the slant range domain of the same satellite radio wave observed by two different GNSS receivers during the measurement period are calculated respectively.

[0075] Based on the ionospheric thin shell model, the ionospheric delay values in the two slant range domains are converted into the ionospheric delay values in the two vertical domains respectively.

[0076] In this step, ionospheric statistics require the use of ionospheric gradients in the vertical domain, because the ionospheric delay changes with the elevation angle of the GNSS satellite. The ionospheric delay in the slant range domain can be converted into an equivalent ionospheric delay in the vertical domain using the ionospheric thin shell model.

[0077] In this ionospheric thin shell model, the tilt factor can be expressed as follows:

[0078]

[0079] Where Re is the radius of the Earth, h is the height of the ionospheric shell model, and el is the elevation angle of the GNSS satellite.

[0080] The ionospheric delay values in the two tilt domains can be converted into the ionospheric delay values in the vertical domain at the equivalent puncture point by the tilt factor I vert , which can be calculated by the following formulas:

[0081]

[0082] In formula (11), I slant is the ionospheric delay value in the slant range domain, I vert is the ionospheric delay value in the vertical domain, and FPP is the tilt factor.

[0083] Based on the ionospheric delays in two vertical domains, the short baseline two-station method or the time step method is used to determine the ionospheric TEC spatial gradient.

[0084] In the above process, the short baseline dual-station method is used to calculate the ionospheric gradient value. The specific steps are as follows:

[0085] First, calculate the baseline distance ΔS between the S1 receiver and the S2 receiver. Based on this baseline distance, calculate the ionospheric gradient value using the following formula:

[0086]

[0087] in, It represents the vertical ionospheric delay calculated by the S1 receiver observing the GPS satellite. It represents the vertical ionospheric delay calculated by the S2 receiver observing the GPS satellite;

[0088] In the above process, the time step method is used to calculate the ionospheric gradient value. The specific steps are as follows:

[0089] First, calculate the straight-line distance d between the GNSS satellite's puncture point IPP1 at time T1 and the puncture point IPP2 at time T2. Then, based on this straight-line distance, calculate the ionospheric gradient value using the following formula:

[0090] g=(Ivert (T2)-I vert (T1)) / d (7)

[0091] According to the calculated ionospheric TEC gradient value, the magnitude of the ionospheric TEC spatial gradient generated by the plasma bubble is determined.

[0092] Taking a densely distributed area on the ground as an example, the short baseline double station method is used to calculate the gradient of the plasma bubble. The time step method is not affected by the distribution of ground receivers, so it can also be used to calculate the TEC spatial gradient caused by the plasma bubble. Both the short baseline double station method and the time step method are applicable to densely distributed areas on the ground. Figure 3 The results of calculating the TEC spatial gradient caused by plasma bubbles using two methods are shown in Fig.

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting ionospheric TEC spatial gradients caused by plasma bubbles, characterized by: The steps include: Step 1: Obtain GNSS observation data and navigation message files from the IGS data center and parse out ionospheric parameters; Step 2: Use the multi-resolution ionospheric tomography algorithm to obtain the electron density distribution in the inversion area, then reconstruct the TEC distribution image of the inversion area and determine whether there are plasma bubbles; Step 3: If plasma bubbles occur, obtain continuous measurement data from the GNSS satellite during the measurement period through the GNSS receiver and preprocess the measurement data; Step 4: Calculate the ionospheric delay based on the processed measurement data; Step 5: Calculate the ionospheric TEC spatial gradient value using the obtained ionospheric delay value and determine the ionospheric TEC spatial gradient value parameters generated by the plasma bubble.

2. The method for detecting ionospheric TEC spatial gradient caused by plasma bubbles according to claim 1, characterized in that: In step 2, the electron density distribution in the inversion region is obtained using a multi-resolution ionospheric tomography algorithm, and then the TEC distribution image of the inversion region is reconstructed, which includes: The tilted total electron content required for the multi-resolution ionospheric tomography algorithm is calculated using GNSS observation data; Based on the above tilted total electron content, the ionospheric electron density is obtained by inversion using a multi-resolution ionospheric tomography algorithm; The ionospheric TEC distribution image is reconstructed based on the electron density obtained above.

3. The method for detecting ionospheric TEC spatial gradient caused by plasma bubbles according to claim 1, characterized in that: In step 5, the obtained ionospheric delay value is used to calculate the ionospheric TEC spatial gradient value using the short baseline dual-station method or the time step method to determine the ionospheric TEC spatial gradient value parameters generated by the plasma bubble.

4. The method for detecting ionospheric TEC spatial gradient caused by plasma bubbles according to claim 3, characterized in that: The method of calculating the ionospheric TEC spatial gradient value by the short baseline dual-station method and determining the ionospheric TEC spatial gradient value parameters generated by the plasma bubble specifically includes: During the measurement period, two different GNSS receivers are selected to observe the same GPS satellite. Based on the processed measurement data, the ionospheric delay values in the slant range domain between the two receivers and the satellite are calculated. The baseline distance between the two GNSS receivers is less than 45 kilometers. Based on the ionospheric thin shell model, the ionospheric delay values in the slant range domain on the line of sight between the two receivers and the satellite are converted into ionospheric delay values in the vertical domain; The ionospheric TEC spatial gradient value is calculated based on the ionospheric delay in two vertical domains using the short baseline dual-station method, and finally the magnitude of the ionospheric TEC spatial gradient value generated by the plasma bubble is determined.

5. The method for detecting ionospheric TEC spatial gradient caused by plasma bubbles according to claim 3, characterized in that: The method of calculating the ionospheric TEC spatial gradient value by the time step method and determining the ionospheric TEC spatial gradient value parameter generated by the plasma bubble specifically includes: Selecting two different moments within a measurement period, and calculating the ionospheric delay values of the GNSS satellite in the slant range domain at the two different moments based on the processed measurement data; Based on the ionospheric thin shell model, the ionospheric delays in the two slant range domains are converted into ionospheric delay values in two vertical domains respectively; The ionospheric TEC spatial gradient value is calculated according to the ionospheric delays in the two vertical domains using a time step method, and finally the ionospheric TEC spatial gradient value generated by the plasma bubble is determined.

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