Quantitative Evaluation Method and Device for Multipath Noise Interference of Ionospheric Scintillation

Abstract

The present application discloses a method and device for quantitatively evaluating multipath noise interference of ionospheric scintillation. The method includes: collecting original data; calculating result data according to the original data; constructing a spatio-temporal coordinate system, and performing three-dimensional division on the spatio-temporal coordinate system according to a preset azimuth step, elevation step, and observation time step to form a three-dimensional statistical grid; dividing the result data into the three-dimensional statistical grid according to the azimuth, elevation, and the time period it is in as a sample data set; traversing the sample data set, and using a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid. The present application effectively quantifies the multipath interference determination interval of the ionospheric scintillation index affected by multipath within different azimuths, elevations, and observation time ranges from the data samples.

Description

Technical Field

[0001] This application relates to the field of global satellite navigation technology, and particularly to a method and device for quantitatively evaluating multipath noise interference of ionospheric scintillation. Background Art

[0002] The Global Navigation Satellite System (GNSS) can provide all-weather high-precision global positioning, navigation, and timing functions, and plays a key role in fields such as aviation, resource environment, disaster prevention and mitigation, and surveying and mapping. However, due to the low power of satellite signals, they are easily interfered by environmental factors during propagation. Especially in low-latitude regions with extreme ionospheric disturbances, the impact of ionospheric scintillation on GNSS satellite signals is particularly obvious. Therefore, it is necessary to establish GNSS monitoring stations to collect and analyze the laws of ionospheric scintillation.

[0003] Currently, the ionospheric scintillation index is usually used to quantify the ionospheric scintillation phenomenon. Ionospheric scintillation usually causes changes in the amplitude of GNSS satellite signals. However, in addition to ionospheric disturbances, multipath noise factors can also cause similar changes in the signal amplitude. To study the situation of ionospheric disturbances, it is necessary to exclude the interference caused by multipath noise in the ionospheric scintillation index.

[0004] To reduce the impact of multipath interference on the monitoring results of ionospheric scintillation, the current common practice is to set an appropriate elevation mask angle to shield the part of GNSS satellite observation data below the elevation mask angle to suppress the influence of ground multipath noise. However, this mask angle setting relying on experience rather than quantification can only generally screen out the data with an elevation angle lower than the mask angle in the case of complex ground multipath noise interference, and cannot accurately shield the influence of multipath noise, nor can it make full use of effective observation data. Summary of the Invention

[0005] Embodiments of the present invention provide a method and device for quantitatively evaluating multipath noise interference of ionospheric scintillation, which solve the technical problems in the prior art that the influence of multipath noise cannot be accurately shielded and effective observation data cannot be fully utilized.

[0006] In a first aspect, the present application provides a method for quantitatively evaluating multipath noise interference of ionospheric scintillation. The method includes: collecting original data, where the original data includes satellite observation data and ephemeris data; calculating result data according to the original data, where the result data includes the ionospheric scintillation index at fixed time intervals, and the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index; constructing a spatio-temporal coordinate system, and three-dimensionally dividing the spatio-temporal coordinate system according to preset azimuth angle steps, elevation angle steps, and observation time steps to form a three-dimensional statistical grid; dividing the result data into the three-dimensional statistical grid according to the azimuth angle, elevation angle, and the time period it is in as a sample data set; traversing the sample data set; and using a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid.

[0007] In combination with the first aspect, in a possible implementation manner, the calculating result data according to the original data includes: calculating and outputting the ionospheric scintillation index at fixed time intervals; where the calculation formula of the ionospheric scintillation index is as follows: In the above formula, S4 represents the ionospheric scintillation index, <SI 2 > represents the mean value of the square of the signal intensity within the fixed time interval; <SI> 2 represents the square of the mean value of the signal intensity within the fixed time interval; S / N0 represents the signal-to-noise ratio; calculating the position of the satellite at each output moment of the ionospheric scintillation index according to the ephemeris data; and calculating the elevation angle and azimuth angle of the satellite at each output moment of the ionospheric scintillation index according to the phase center position of the monitoring station receiver antenna.

[0008] In combination with the first aspect, in a possible implementation manner, the constructing a spatio-temporal coordinate system includes: establishing the spatio-temporal coordinate system based on the phase center of the monitoring station signal receiving antenna, and the elevation angle, azimuth angle of the satellite, and the observation time based on the satellite operation period.

[0009] In combination with the first aspect, in a possible implementation manner, the method for determining the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid using a clustering algorithm includes: performing a first clustering on the ionospheric scintillation index in the sample dataset, and taking the number of maximum values of the sample density as the number of clusters in the clustering result; using the number of clusters obtained from the first clustering, performing a second clustering on the ionospheric scintillation index, clustering the ionospheric scintillation index in the sample dataset within the three-dimensional statistical grid into multiple initial clusters, and finding the target cluster with the largest number of samples; determining the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation index of all samples within the target cluster to the clustering center Cn; finding the maximum value dm that satisfies a preset criterion among all the distances dsn, and using Cn - dm and Cn + dm as the multipath interference determination threshold of the ionospheric scintillation index.

[0010] In combination with the first aspect, in a possible implementation manner, the first clustering includes a kernel density estimation clustering algorithm, and / or the second clustering includes a K-means clustering algorithm.

[0011] In combination with the first aspect, in a possible implementation manner, the method for quantitatively evaluating the multipath noise interference of ionospheric scintillation further includes: when traversing the sample dataset, determining whether the number of samples in the sample dataset reaches a preset critical value; if the number of samples in the sample dataset reaches the preset critical value, performing the method for determining the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid using a clustering algorithm; otherwise, setting the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid to be empty, and after all the three-dimensional statistical networks are traversed, completing all the multipath interference determination thresholds of the ionospheric scintillation index of the three-dimensional statistical grid.

[0012] In combination with the first aspect, in a possible implementation manner, the method for completing all the multipath interference determination thresholds of the ionospheric scintillation index of the three-dimensional statistical grid includes: performing a loop according to the observation time interval, and on the elevation angle and azimuth angle latitudes, using a two-dimensional nearest neighbor interpolation method to complete the empty multipath interference threshold of the ionospheric scintillation.

[0013] Second aspect, the present application provides a device for quantitatively evaluating multipath noise interference of ionospheric scintillation. The device includes: a collection module for collecting original data, where the original data includes satellite observation data and ephemeris data; a calculation module for calculating result data according to the original data, where the result data includes the ionospheric scintillation index at a fixed time interval, and the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index; a construction module for constructing a spatio-temporal coordinate system and performing three-dimensional division on the spatio-temporal coordinate system according to a preset azimuth angle step, elevation angle step, and observation time step to form a three-dimensional statistical grid; a division module for dividing the result data into the three-dimensional statistical grid according to the azimuth angle, elevation angle, and the time period it is in as a sample data set; a traversal module for traversing the sample data set; and a clustering module for using a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid.

[0014] In combination with the second aspect, in a possible implementation manner, the calculation module is specifically configured to: calculate and output the ionospheric scintillation index at a fixed time interval; where the calculation formula of the ionospheric scintillation index is as follows: In the above formula, S4 represents the ionospheric scintillation index, <SI 2 > represents the mean value of the square of the signal intensity within the fixed time interval; <SI> 2 represents the square of the mean value of the signal intensity within the fixed time interval; S / N0 represents the signal-to-noise ratio; calculate the position of the satellite at each output moment of the ionospheric scintillation index according to the ephemeris data; and calculate the elevation angle and azimuth angle of the satellite at each output moment of the ionospheric scintillation index according to the phase center position of the monitoring station receiver antenna.

[0015] In combination with the second aspect, in a possible implementation manner, the construction module is specifically configured to: establish the spatio-temporal coordinate system based on the phase center of the monitoring station signal receiving antenna, and the elevation angle, azimuth angle of the satellite, and the observation time based on the satellite operation period.

[0016] In combination with the second aspect, in a possible implementation manner, the clustering module is specifically configured to: perform a first clustering on the ionospheric scintillation index in the sample data set, and use the number of maximum values of the sample density as the number of clusters in the clustering result; use the number of clusters obtained from the first clustering to perform a second clustering on the ionospheric scintillation index, cluster the ionospheric scintillation index in the sample data set within the three-dimensional statistical grid into multiple initial clusters, and find the target cluster with the largest number of samples; determine the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation index of all samples within the target cluster to the clustering center Cn; find the maximum value dm that satisfies the preset criterion among all the distances dsn, and use Cn - dm and Cn + dm as the multi-path interference determination thresholds for the ionospheric scintillation index.

[0017] In combination with the second aspect, in a possible implementation manner, the first clustering includes a kernel density estimation clustering algorithm, and / or the second clustering includes a K-means clustering algorithm.

[0018] In combination with the second aspect, in a possible implementation manner, the multi-path noise interference quantization evaluation device for ionospheric scintillation further includes: a judgment module, configured to judge whether the number of samples in the sample data set reaches a preset critical value when traversing the sample data set; if the number of samples in the sample data set reaches the preset critical value, the clustering module uses a clustering algorithm to determine the multi-path interference determination threshold for the ionospheric scintillation index of the three-dimensional statistical grid; otherwise, the nulling module nulls the multi-path interference determination threshold for the ionospheric scintillation index of the three-dimensional statistical grid, and after all the three-dimensional statistical networks are traversed, the filling module fills in all the multi-path interference determination thresholds for the ionospheric scintillation index of the three-dimensional statistical grid.

[0019] In combination with the second aspect, in a possible implementation manner, the filling module is specifically configured to: perform a loop according to the observation time interval, and use two-dimensional nearest neighbor interpolation method to complete the nulled multi-path interference threshold for ionospheric scintillation in terms of elevation angle and azimuth angle.

[0020] In a third aspect, the present application provides a multi-path noise interference quantization evaluation device for ionospheric scintillation, the device includes a memory and a processor; the memory is used to store computer-executable instructions; the processor is used to execute the computer-executable instructions and can implement the method described in the first aspect and any possible implementation manner of the first aspect.

[0021] Fourthly, the present application provides a computer-readable storage medium storing executable instructions, and when a computer executes the executable instructions, the method described in the first aspect and any possible implementation manner of the first aspect can be implemented.

[0022] The technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0023] In the embodiments of the present invention, by adopting a method for quantifying and evaluating multipath noise interference of ionospheric scintillation, only using the data of the monitoring station itself, the multipath interference situation in each spatio-temporal region around the monitoring station is described through the quality of the data itself, and this is used as a criterion for judging whether the incremental data is affected by multipath. The multipath interference determination interval of the ionospheric scintillation index affected by multipath within different azimuth angles, elevation angles, and observation time ranges is effectively quantified from the data samples. It solves the problems that the traditional fixed elevation angle mask "cuts off" the observed data in a one-size-fits-all manner, resulting in the inability to accurately shield the multipath influence, and even causing the problems of incomplete screening of multipath influence and loss of "clean" data information. Description of the Drawings

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for describing the embodiments of the present invention or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0025] Figure 1 It is a flowchart of a specific implementation manner of the method for quantifying and evaluating multipath noise interference of ionospheric scintillation provided in the embodiments of the present invention;

[0026] Figure 2 It is a flowchart of another specific implementation manner of the method for quantifying and evaluating multipath noise interference of ionospheric scintillation provided in the embodiments of the present invention;

[0027] Figure 3 It is a flowchart of the calculation result data provided in the embodiments of the present invention;

[0028] Figure 4 It is a flowchart of using a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index of a three-dimensional statistical grid provided in the embodiments of the present invention;

[0029] Figure 5 It is a sample data list after the result data integration provided in the embodiments of the present invention;

[0030] Figure 6Distribution of samples in the three-dimensional statistical grid provided by the embodiment of the present invention (azimuth angle 0° to 2°, elevation angle 50° to 52°, observation time range 0 s to 1436 s);

[0031] Figure 7 Provided by the embodiment of the present invention Figure 6 Probability density distribution graph obtained after the first clustering of the sample data set of the three-dimensional statistical grid shown;

[0032] Figure 8 Schematic structural diagram of a multi-path noise interference quantization evaluation device for ionospheric scintillation provided by the embodiment of the present invention;

[0033] Figure 9 Another schematic structural diagram of a multi-path noise interference quantization evaluation device for ionospheric scintillation provided by the embodiment of the present invention;

[0034] Figure 10 Schematic structural diagram of a multi-path noise interference quantization evaluation device for ionospheric scintillation provided by the embodiment of the present invention. Specific implementation manners

[0035] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] The present application provides a method for quantifying and evaluating multi-path noise interference of ionospheric scintillation, and this method can be specifically applied to devices such as ground receivers, personal computers, and mobile terminals that can run computer programs.

[0037] Ionospheric scintillation refers to the phenomenon that when GNSS satellite signals pass through the ionosphere, affected by the inhomogeneity of the ionospheric structure, short-term irregular changes occur in signal amplitude, phase, etc. The ionospheric scintillation effect usually causes the signals received by ground receivers to have rapid random fluctuations in amplitude and phase, or causes signal fading, thereby increasing the signal transmission error rate, decreasing the signal-to-noise ratio, and losing satellite signal lock, etc., ultimately leading to a decline in the performance of the global navigation satellite system. In severe cases, the satellite communication link is interrupted, causing the communication system, satellite navigation system, and ground-air target monitoring system to be unavailable. Currently, the ionospheric scintillation index is generally used to quantify the ionospheric scintillation phenomenon, and the ionospheric scintillation index usually reflects the change of signal amplitude over a period of time.

[0038] Multipath noise interference means that in complex environments such as trees and buildings on the ground, satellite signals will generate reflected and diffracted signals in addition to the direct signal when approaching the ground. When these reflected and diffracted signals arrive at the receiver along different propagation paths with a small time difference, they interfere and superimpose with each other, resulting in a drastic change in the amplitude of the satellite signal, seriously affecting the accuracy of local ionospheric scintillation assessment.

[0039] A method for quantitatively evaluating multipath noise interference of ionospheric scintillation provided by this application includes steps S101 to S105, as Figure 1 shown.

[0040] Step S101: Collect raw data. The raw data includes satellite observation data and ephemeris data; specifically, the ephemeris data includes broadcast ephemeris or precise ephemeris data.

[0041] For example, collect GPS observation data with a sampling rate of 50 Hz, and the observation time range is from GPS day of year 059 to 158 in 2021, for a total of 100 days; at the same time, collect the broadcast ephemeris data for the corresponding period.

[0042] Step S102: Calculate the result data according to the raw data. The result data includes the ionospheric scintillation index at fixed time intervals, as well as the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index.

[0043] Step S102 specifically includes steps S301 to S303, as Figure 3 shown.

[0044] Step S301: Calculate and output the ionospheric scintillation index at fixed time intervals, such as once every 60 seconds. Among them, the calculation formula of the ionospheric scintillation index is as follows:

[0045]

[0046] In the above formula, S4 represents the ionospheric scintillation index; SI represents the signal intensity; <SI 2 > represents the mean value of the square of the signal intensity within a fixed time interval; <SI> 2 represents the square of the mean value of the signal intensity within a fixed time interval; S / N0 represents the signal-to-noise ratio. And the signal intensity and the signal-to-noise ratio can be obtained by parsing the receiver data.

[0047] Step S302: Calculate the position of the satellite at each output moment of the ionospheric scintillation index according to the ephemeris data. Specifically, use the broadcast ephemeris to solve the instantaneous position of the satellite corresponding to the output moment of the ionospheric scintillation index.

[0048] Step S303: Calculate the elevation angle and azimuth angle of the satellite at each output moment of the ionospheric scintillation index based on the phase center position of the receiver antenna of the monitoring station.

[0049] Meanwhile, the result data obtained from the above calculations can be stored according to the satellite number and time information, as Figure 5 shown.

[0050] Step S103: Construct a space-time coordinate system, and perform three-dimensional division on the space-time coordinate system according to the preset azimuth step, elevation step, and observation time step to form a three-dimensional statistical grid.

[0051] Specifically, constructing the space-time coordinate system specifically includes: establishing a space-time coordinate system based on the phase center of the signal receiving antenna of the monitoring station, as well as the elevation angle, azimuth angle of the satellite, and the observation time based on the satellite operation period. For example, set the azimuth range to 0 - 360°, and the elevation range to 0 - 90°; considering that the maximum operation period of GPS satellites is about 11 hours and 58 minutes, therefore, set the observation time range to 0 - 43080s, as shown in Figure 6 shown. Of course, these parameters such as the azimuth range, elevation range, and observation time range can be set to other values according to actual needs.

[0052] It should be noted that the maximum value of the time axis of the space-time coordinate system uses the operation period of the satellite, that is, the observation time range is the operation period of the satellite. Since the operation periods of different satellite systems are different, when constructing the space-time coordinate system for different satellite systems, it is different in the time dimension. For example, the operation period of GPS satellites is 11 hours and 58 minutes; for the geostationary orbit satellites of Beidou, the operation period is 24 hours; the operation period of Galileo satellites is 14 hours and 4 minutes. Therefore, the maximum time values of the space-time coordinate systems constructed by different satellite systems are different, and when dividing the three-dimensional statistical grid, the time division intervals are also different.

[0053] When performing three-dimensional division on the space-time coordinate system, the azimuth step d α can be set to 2°, the elevation step d θ to 2°, and the observation time step d t to 1436s, dividing the entire statistical area into 243000 three-dimensional statistical grids, as shown in Figure 6 shown. Of course, the azimuth step, elevation step, and observation time step set during three-dimensional division are not limited to the above values. The size of the three-dimensional statistical grid can be adjusted according to actual needs. When the data volume is small, the multipath interference determination index of each three-dimensional statistical grid can be roughly estimated. As the input data volume increases, the size of the three-dimensional statistical grid can be reduced to obtain a refined multipath interference determination index, so as to more accurately determine the multipath interference in ionospheric scintillation.

[0054] Step S104: Divide the result data into three-dimensional statistical grids according to the azimuth angle, elevation angle, and the time period it belongs to as the sample data set.

[0055] Step S105: Traverse the sample data set.

[0056] Step S106: Use a clustering algorithm to determine the multipath interference judgment threshold of the ionospheric scintillation index for the three-dimensional statistical grid.

[0057] For example, Figure 6 the spatio-temporal coordinate system parameters in [reference] are: the azimuth angle range is 0 to 360°, the elevation angle range is 0 to 90°, and the observation time range is 0 to 43080 s. Figure 6 The three-dimensional statistical grid parameters in [reference] are: the azimuth angle step d α = 2°, the elevation angle step d θ = 2°, and the observation time step d t = 1436 s. Figure 6 There are 55 samples in [reference]. Use the clustering algorithm for these 55 samples to determine the multipath interference judgment threshold of the ionospheric scintillation index. For example, if the multipath interference judgment threshold of the ionospheric scintillation index is 0.038158 and 0.068025, then the ionospheric scintillation multipath interference judgment interval is 0.038158 to 0.068025. Once the ionospheric scintillation index belongs to Figure 6 the three-dimensional statistical grid shown in [reference], and 0.038158 ≤ S4 ≤ 0.068025, it indicates that the index is necessarily affected by multipath interference and needs to be excluded.

[0058] Figure 6 There are 55 samples in the sample data set shown in [reference]. When the number of samples in the sample data set is small, the result of using the clustering algorithm is not of reference significance. To make the result of the clustering algorithm more accurate, a preset critical value can be set, and the clustering algorithm is used when the number of samples in the sample data set reaches the preset critical value. For example, the preset critical value is set to 10.

[0059] As Figure 2 shown, the multipath noise interference quantization evaluation method for ionospheric scintillation further includes Step S201 and Step S202.

[0060] Step S201: When traversing the sample data set, judge whether the number of samples in the sample data set reaches the preset critical value.

[0061] If the number of samples in the sample data set reaches the preset critical value, execute Step S106: Use a clustering algorithm to determine the multipath interference judgment threshold of the ionospheric scintillation index for the three-dimensional statistical grid.

[0062] If the number of data samples in the sample dataset does not reach the preset critical value, then step S202 is executed: set the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid to null. After all three-dimensional statistical networks are traversed, complete all the multipath interference determination thresholds of the ionospheric scintillation index of the three-dimensional statistical grid.

[0063] Step S106: Use a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index of the three-dimensional statistical grid, specifically including steps S401 to S404, as Figure 4 shown.

[0064] Step S401: Perform the first clustering on the ionospheric scintillation indices in the sample dataset, and use the number of occurrences of the maximum value of the sample density as the number of clusters in the clustering result.

[0065] Referring to Figure 7 shown, Figure 7 is Figure 6 the probability density distribution diagram after the first clustering of the sample dataset shown. It can be seen that there are 2 density maxima, so the number of clusters is set to 2.

[0066] Step S402: Use the number of clusters obtained from the first clustering to perform the second clustering on the ionospheric scintillation indices, cluster the ionospheric scintillation indices in the sample dataset within the three-dimensional statistical grid into multiple initial clusters, and find the target cluster with the largest number of samples.

[0067] Taking Figure 6 and Figure 7 as an example, perform the first clustering on the ionospheric scintillation indices of all samples in this three-dimensional statistical grid. According to the result of the first clustering, set the number of clusters to 2, and then perform the second clustering to obtain two clusters DC1 and DC2. The number of samples contained in the two clusters DC1 and DC2 is 37 and 18 respectively. Select the cluster DC1 with the largest number of samples and set the cluster DC1 as the target cluster.

[0068] Step S403: Determine the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation indices of all samples within the target cluster to the clustering center Cn. Still taking Figure 6 and Figure 7 as an example, calculate the distance ds1 from all samples in the target cluster to the clustering center C1.

[0069] Step S404: Find the maximum value dm that satisfies the preset criterion among all the distances dsn, and use Cn - dm and Cn + dm as the multipath interference determination thresholds of the ionospheric scintillation index. This preset criterion can be set to the 3σ criterion, and of course other criteria can also be adopted.

[0070] For example, ds1 is screened according to the 3σ standard, and it is obtained that the distances from a total of 36 samples in the target cluster to the clustering center meet the 3σ standard. The maximum value among the distances is used as the maximum bandwidth dm = 0.01493 of the multi-path interference determination threshold of the ionospheric scintillation index of this cluster.

[0071] Therefore, the final obtained multi-path interference judgment interval of the ionospheric scintillation is 0.038158 - 0.068025. Once the ionospheric scintillation index belongs to Figure 6 the three-dimensional statistical grid shown, and satisfies 0.038158 ≤ S4 ≤ 0.068025, it indicates that the ionospheric scintillation index is necessarily affected by multi-path interference and needs to be excluded.

[0072] Specifically, the first clustering includes the kernel density estimation clustering algorithm, and / or the second clustering includes the K-means clustering algorithm. Of course, other density-based clustering algorithms can be used for the first clustering, and other more suitable clustering algorithms can also be used for the second clustering.

[0073] All the multi-path interference determination thresholds of the ionospheric scintillation index for completing the three-dimensional statistical grid include: looping according to the observation time interval, and using the two-dimensional nearest neighbor interpolation method to complete the empty ionospheric scintillation multi-path interference thresholds in terms of the elevation angle and azimuth angle latitudes.

[0074] The multi-path noise interference quantization evaluation method of ionospheric scintillation provided by the embodiment of the present invention only uses the data of the monitoring station itself, describes the multi-path interference conditions of each spatio-temporal region around the monitoring station through the quality of the data itself, and uses this as the standard for judging whether the incremental data is affected by multi-path interference. It effectively quantifies the multi-path interference determination interval of the ionospheric scintillation index affected by multi-path in different azimuth angles, elevation angles, and observation time ranges from the data samples. It solves the problems caused by the traditional fixed elevation angle mask "one-size-fits-all" screening of observation data, such as the inability to accurately shield the multi-path influence, and even the problems of incomplete screening of multi-path influence and loss of "clean" data information.

[0075] Although this application provides method operation steps such as in the embodiment or flowchart, based on routine or non-creative labor, it may include more or fewer operation steps. The step order listed in this embodiment is only one way among the execution orders of numerous steps and does not represent the only execution order. When the actual device or client product is executed, it can be executed in the order shown in this embodiment or the drawings or executed in parallel (for example, in an environment of parallel processors or multi-threaded processing).

[0076] This application provides a multi-path noise interference quantization evaluation device 800 for ionospheric scintillation, as Figure 8As shown in the figure, the device includes a collection module 801, a calculation module 802, a construction module 803, a division module 804, a traversal module, and a clustering module 806.

[0077] The collection module 801 is used to collect raw data, where the raw data includes satellite observation data and ephemeris data.

[0078] For example, collect GPS observation data with a sampling rate of 50 Hz, and the observation time range is from GPS day of year 059 to 158 in 2021, for a total of 100 days; at the same time, collect the broadcast ephemeris data for the corresponding period.

[0079] The calculation module 802 is used to calculate result data based on the raw data. The result data includes the ionospheric scintillation index at fixed time intervals, as well as the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index. The calculation module 802 is specifically used to perform the following calculations.

[0080] Calculate and output the ionospheric scintillation index at fixed time intervals, such as once every 60 seconds. Among them, the calculation formula of the ionospheric scintillation index is as follows:

[0081]

[0082] In the above formula, S4 represents the ionospheric scintillation index; SI represents the signal strength; <SI 2 > represents the mean value of the square of the signal strength within a fixed time interval; <SI> 2 represents the square of the mean value of the signal strength within a fixed time interval; S / N0 represents the signal-to-noise ratio. And the signal strength and signal-to-noise ratio can be obtained by parsing the receiver data.

[0083] Calculate the position of the satellite at each output moment of the ionospheric scintillation index according to the ephemeris data. Specifically, use the broadcast ephemeris to solve the instantaneous position of the satellite corresponding to the output moment of the ionospheric scintillation index. According to the phase center position of the receiver antenna at the monitoring station, calculate the elevation angle and azimuth angle of the satellite at each output moment of the ionospheric scintillation index.

[0084] At the same time, the result data obtained from the above calculations can be stored according to the satellite number and time information, as Figure 5 shown.

[0085] The construction module 803 is used to construct a spatio-temporal coordinate system, and perform three-dimensional division on the spatio-temporal coordinate system according to preset azimuth angle step size, elevation angle step size, and observation time step size to form a three-dimensional statistical grid.

[0086] The construction module 803 is specifically used for: establishing a spatio-temporal coordinate system based on the phase center of the signal receiving antenna of the monitoring station, as well as the elevation angle, azimuth angle of the satellite, and the observation time based on the satellite's operating cycle. For example, the azimuth angle range is set to 0 to 360°, and the elevation angle range is set to 0 to 90°; considering that the maximum operating cycle of GPS satellites is about 11 hours and 58 minutes, therefore, the observation time range is set to 0 to 43080 s, as shown in Figure 6. Of course, these parameters such as the azimuth angle range, elevation angle range, and observation time range can be set to other values according to actual needs.

[0087] When performing three-dimensional division of the spatio-temporal coordinate system, the azimuth angle step size d α = 2°, the elevation angle step size d θ = 2°, and the observation time step size d t = 1436 s can be set, and the entire statistical area is divided into 243,000 three-dimensional statistical grids, as shown in Figure 6 Figure. Of course, the azimuth angle step size, elevation angle step size, and observation time step size set during three-dimensional division are not limited to the above values, and the size of the three-dimensional statistical grid can be adjusted according to actual needs. In the case of a small amount of data, the multi-path interference determination index of each three-dimensional statistical grid can be roughly estimated. As the input data volume increases, the size of the three-dimensional statistical grid can be reduced to obtain a refined multi-path interference determination index, so as to more accurately determine the multi-path interference in ionospheric scintillation.

[0088] The division module 804 is used to divide the result data into three-dimensional statistical grids according to the azimuth angle, elevation angle, and the time period it is in as a sample data set.

[0089] The traversal module 805 is used to traverse the sample data set.

[0090] The clustering module 806 uses a clustering algorithm to determine the multi-path interference determination threshold of the ionospheric scintillation index for the three-dimensional statistical grid.

[0091] For example, Figure 6 the spatio-temporal coordinate system parameters in Figure are: the azimuth angle range is 0 to 360°, the elevation angle range is 0 to 90°, and the observation time range is 0 to 43080 s. Figure 6 The three-dimensional statistical grid parameters in Figure are: the azimuth angle step size d α = 2°, the elevation angle step size d θ = 2°, and the observation time step size d t = 1436 s. Figure 6There are a total of 55 samples, and the clustering algorithm is used for these 55 samples to determine the multipath interference judgment threshold of the ionospheric scintillation index. For example, if the multipath interference judgment threshold of the ionospheric scintillation index is 0.038158 and 0.068025, then the ionospheric scintillation multipath interference judgment interval is 0.038158 to 0.068025. Once the ionospheric scintillation index belongs to Figure 6 the three-dimensional statistical grid shown, and 0.038158 ≤ S4 ≤ 0.068025, it indicates that the index is necessarily affected by multipath interference and needs to be excluded.

[0092] Figure 6 There are 55 samples in the sample dataset shown. When the number of samples in the sample dataset is small, the result of using the clustering algorithm is not of reference significance. To make the result of the clustering algorithm more accurate, a preset critical value can be set, and the clustering algorithm is used when the number of samples in the sample dataset reaches the preset critical value. For example, the preset critical value is set to 10.

[0093] Such as Figure 9 shown, the multipath noise interference quantization evaluation device 800 for ionospheric scintillation further includes: a judgment module 807, a nulling module 808, and a completion module 809. The judgment module 807 is used to judge whether the number of samples in the sample dataset reaches the preset critical value when traversing the sample dataset. If the number of samples in the sample dataset reaches the preset critical value, the clustering module 806 uses the clustering algorithm to determine the multipath interference judgment threshold of the ionospheric scintillation index of the three-dimensional statistical grid. Otherwise, the nulling module 808 nulls the multipath interference judgment threshold of the ionospheric scintillation index of the three-dimensional statistical grid, and the completion module 809 completes all the multipath interference judgment thresholds of the ionospheric scintillation index of the three-dimensional statistical grid after all the three-dimensional statistical networks are traversed.

[0094] The clustering module 806 is specifically used to perform the following steps.

[0095] Perform the first clustering on the ionospheric scintillation indices in the sample dataset, and use the number of samples with the maximum density as the number of clusters in the clustering result.

[0096] Refer to Figure 7 shown, Figure 7 is Figure 6 the probability density distribution diagram after the first clustering of the sample dataset shown. It can be seen that there are 2 density maxima, so the number of clusters is set to 2.

[0097] Use the number of clusters obtained from the first clustering to perform the second clustering on the ionospheric scintillation indices, cluster the ionospheric scintillation indices in the sample dataset within the three-dimensional statistical grid into multiple initial clusters, and find the target cluster with the largest number of samples.

[0098] TakingFigure 6 And Figure 7 Taking Figure 6 and Figure 7 as examples, the ionospheric scintillation index of all samples of the three-dimensional statistical grid is clustered for the first time. According to the results of the first clustering, the number of clusters is set to 2, and then the second clustering is performed to obtain two clusters DC1 and DC2. The number of samples included in the two clusters DC1 and DC2 is 37 and 18 respectively. Select the cluster DC1 with the largest number of samples and set the cluster DC1 as the target cluster.

[0099] Determine the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation index of all samples within the target cluster to the clustering center Cn. Still taking Figure 6 and Figure 7 as examples, calculate the distance ds1 from the ionospheric scintillation index of all samples in the target cluster to the clustering center C1. Figure 6 And Figure 7 Taking and

[0099] as examples, calculate the distance ds1 from the ionospheric scintillation index of all samples in the target cluster to the clustering center C1.

[0100] Find the maximum value dm that satisfies the preset standard among all distances dsn, and use Cn - dm and Cn + dm as the multi-path interference judgment thresholds for the ionospheric scintillation index. The preset standard can be set as the 3σ standard, and of course other standards can also be adopted.

[0101] For example, screening ds1 with the 3σ standard, it is obtained that a total of 36 samples within the target cluster satisfy the 3σ standard for the distance to the clustering center. Take the maximum value in the distances as the maximum bandwidth dm = 0.01493 of the multi-path interference judgment threshold for the ionospheric scintillation index of this cluster.

[0102] Therefore, the final obtained multi-path interference judgment interval for the ionospheric scintillation is 0.038158 - 0.068025. Once the ionospheric scintillation index belongs to the three-dimensional statistical grid shown in Figure 6 and satisfies 0.038158 ≤ S4 ≤ 0.068025, it indicates that the ionospheric scintillation index is necessarily affected by multi-path interference and needs to be excluded. Figure 6 As shown in Figure 6 , and satisfying 0.038158 ≤ S4 ≤ 0.068025, it indicates that the ionospheric scintillation index is necessarily affected by multi-path interference and needs to be excluded.

[0103] Specifically, the first clustering includes a kernel density estimation clustering algorithm, and / or the second clustering includes a K-means clustering algorithm. Of course, other density-based clustering algorithms can be used for the first clustering, and other more appropriate clustering algorithms can also be used for the second clustering.

[0104] The complementing module 809 is specifically used for: looping according to the observation time interval, and using two-dimensional nearest neighbor interpolation method to complement the empty ionospheric scintillation multi-path interference threshold at the elevation and azimuth latitudes.

[0105] The multipath noise interference quantization and evaluation device 800 for ionospheric scintillation provided by the embodiments of the present invention only uses the data of the monitoring station itself, describes the multipath interference conditions in each spatio-temporal region around the monitoring station through the quality of the data itself, and uses this as the standard for judging whether the incremental data is affected by multipath interference. It effectively quantifies the multipath interference determination interval of the ionospheric scintillation index affected by multipath within different azimuth angles, elevation angles, and observation time ranges from the data samples. It solves the problems caused by the traditional fixed elevation angle mask "one-size-fits-all" screening of observation data, such as the inability to accurately shield the influence of multipath, and even the problems of incomplete screening of multipath influence and loss of "clean" data information.

[0106] The device or module illustrated in the above embodiments can be specifically implemented by a computer chip or an entity, or by a product with a certain function. For the convenience of description, when describing the above device, it is divided into various modules according to functions and described separately. When implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware. Of course, the module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0107] The present application also provides a multipath noise interference quantization and evaluation device 1000 for ionospheric scintillation, as Figure 10 shown. The device includes a memory 1001 and a processor 1002; the memory 1001 is used to store computer-executable instructions; the processor 1002 is used to execute the computer-executable instructions and can implement the multipath noise interference quantization and evaluation method for ionospheric scintillation provided by the embodiments of the present invention.

[0108] The present application also provides a computer-readable storage medium. The computer-readable storage medium stores executable instructions, and when the computer executes the executable instructions, it can implement the multipath noise interference quantization and evaluation method for ionospheric scintillation provided by the embodiments of the present invention.

[0109] The above storage medium includes, but is not limited to, random access memory (English: Random Access Memory; abbreviation: RAM), read-only memory (English: Read-Only Memory; abbreviation: ROM), cache (English: Cache), hard disk (English: Hard Disk Drive; abbreviation: HDD), or memory card (English: Memory Card). The memory can be used to store computer program instructions.

[0110] The methods, devices or modules in this application can be implemented in the form of computer-readable program code. The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor, and a computer-readable medium that stores computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8061F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, it is entirely possible to logically program the method steps to enable the controller to be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers to achieve the same function. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0111] Some modules in the device of this application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0112] From the description of the above embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary hardware. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, or can also be reflected in the implementation process of data migration. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods of various embodiments or certain parts of the embodiments of this application.

[0113] The various embodiments in this specification are described in a progressive manner. For the same or similar parts among the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. All or part of this application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multi-processor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on.

[0114] The above embodiments are only used to illustrate the technical solutions of this application, rather than limiting this application; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of this application.

Claims

1. A method for quantitatively evaluating multipath noise interference of ionospheric scintillation, characterized in that Including: Collecting original data, where the original data includes satellite observation data and ephemeris data; Calculating result data based on the original data, where the result data includes the ionospheric scintillation index at fixed time intervals, as well as the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index; Constructing a space-time coordinate system, and three-dimensionally dividing the space-time coordinate system according to preset azimuth step sizes, elevation step sizes, and observation time step sizes to form three-dimensional statistical grids; Dividing the result data into the three-dimensional statistical grids according to the azimuth angle, elevation angle, and the time period it is in as a sample data set; Traversing the sample data set; Using a clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index for the three-dimensional statistical grid, including: performing a first clustering on the ionospheric scintillation index in the sample data set, and taking the number of occurrences of the maximum sample density as the number of clusters in the clustering result; Using the number of clusters obtained from the first clustering, performing a second clustering on the ionospheric scintillation index, clustering the ionospheric scintillation index in the sample data set within the three-dimensional statistical grid into multiple initial clusters, and finding the target cluster with the largest number of samples; Determining the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation index of all samples within the target cluster to the clustering center Cn; Finding the maximum value dm that satisfies the preset criteria among all the distances dsn, and taking Cn - dm and Cn + dm as the multipath interference determination threshold of the ionospheric scintillation index.

2. The method for quantifying and evaluating multipath noise interference of ionospheric scintillation according to claim 1, wherein The calculating the result data according to the original data includes: Calculating and outputting the ionospheric scintillation index at fixed time intervals; where the calculation formula of the ionospheric scintillation index is as follows: In the above formula, S4 represents the ionospheric scintillation index, <SI 2 > represents the mean value of the square of the signal intensity within the fixed time interval; <SI> 2 represents the square of the mean value of the signal intensity within the fixed time interval; S / N0 represents the signal-to-noise ratio; Calculating the position of the satellite at each output moment of the ionospheric scintillation index according to the ephemeris data; Calculating the elevation angle and azimuth angle of the satellite at each output moment of the ionospheric scintillation index according to the phase center position of the monitoring station receiver antenna.

3. The method for quantitatively evaluating multipath noise interference of ionospheric scintillation according to claim 1, wherein The constructing the space-time coordinate system includes: Establishing the space-time coordinate system based on the phase center of the monitoring station signal receiving antenna, as well as the elevation angle, azimuth angle of the satellite, and the observation time based on the satellite operation period.

4. The method for quantifying and evaluating multipath noise interference of ionospheric scintillation according to claim 1, wherein The first clustering includes a kernel density estimation clustering algorithm, and / or the second clustering includes a K-means clustering algorithm.

5. The multipath noise interference quantization evaluation method for ionospheric scintillation according to claim 1, characterized in that It also includes: When traversing the sample data set, determining whether the number of samples in the sample data set reaches a preset critical value; If the number of samples in the sample data set reaches the preset critical value, execute using the clustering algorithm to determine the multipath interference determination threshold of the ionospheric scintillation index for the three-dimensional statistical grid; Otherwise, set the multipath interference determination threshold of the ionospheric scintillation index for the three-dimensional statistical grid to be empty, and after all the three-dimensional statistical networks are traversed, complete all the multipath interference determination thresholds of the ionospheric scintillation index for the three-dimensional statistical grid.

6. The multi-path noise interference quantization evaluation method for ionospheric scintillation according to claim 5, characterized in that The completing all the multipath interference determination thresholds of the ionospheric scintillation index for the three-dimensional statistical grid includes: Perform a loop according to the observation time interval. On the elevation angle and azimuth angle latitudes, use the two-dimensional nearest neighbor interpolation method to complete the empty ionospheric scintillation multipath interference thresholds.

7. A multipath noise interference quantization evaluation device for ionospheric scintillation, characterized in that Including: A collection module for collecting raw data, where the raw data includes satellite observation data and ephemeris data; A calculation module for calculating result data based on the raw data, where the result data includes the ionospheric scintillation index at a fixed time interval, and the position, elevation angle, and azimuth angle of the satellite at each output moment of the ionospheric scintillation index; A construction module for constructing a spatio-temporal coordinate system and performing three-dimensional division on the spatio-temporal coordinate system according to a preset azimuth angle step size, elevation angle step size, and observation time step size to form a three-dimensional statistical grid; A division module for dividing the result data into the three-dimensional statistical grid according to the azimuth angle, elevation angle, and the time period it is in as a sample data set; A traversal module for traversing the sample data set; A clustering module for using a clustering algorithm to determine the ionospheric scintillation index multipath interference determination threshold of the three-dimensional statistical grid, including: performing a first clustering on the ionospheric scintillation index in the sample data set, and taking the number of occurrences of the maximum value of the sample density as the number of clusters in the clustering result; Using the number of clusters obtained from the first clustering, performing a second clustering on the ionospheric scintillation index, clustering the ionospheric scintillation index in the sample data set within the three-dimensional statistical grid into multiple initial clusters, and finding the target cluster with the largest number of samples; Determining the clustering center Cn of the ionospheric scintillation index of the target cluster, and the distance dsn from the ionospheric scintillation index of all samples within the target cluster to the clustering center Cn; Finding the maximum value dm that satisfies the preset standard among all the distances dsn, and using Cn - dm and Cn + dm as the ionospheric scintillation index multipath interference determination threshold.

8. A multipath noise interference quantization evaluation device for ionospheric scintillation, characterized in that, Including a memory and a processor; The memory is used to store computer-executable instructions; The processor is used to execute the computer-executable instructions and can implement the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores executable instructions, and when the computer executes the executable instructions, it can implement the method according to any one of claims 1-6.

Images