Short-wave communication frequency selection method and device based on ionosphere oblique return detection

Abstract

The application relates to a short-wave communication frequency selection method and device based on ionospheric oblique return detection, wherein the method comprises the following steps: performing oblique return detection by using an ionospheric detection system, acquiring an oblique return ionogram, separating a vertical sounding echo and an oblique return wave from the ionogram by a pattern recognition method, reading local ionospheric parameter information from the vertical sounding echo, tracing an oblique return wave front, then performing ionogram inversion, fusing the local ionospheric parameter information with the inversion result, reconstructing a reflection zone ionospheric model, constructing a two-dimensional electron concentration profile, calculating a corresponding passable frequency range by using a ray tracing method, and finally selecting an optimal communication frequency point according to signal-to-noise ratio information reflected by the ionogram. Thus, the problems that the existing short-wave communication frequency selection method does not consider the ionospheric factor which has an important influence on short-wave transmission and user frequency selection coordination, the accuracy and reliability of frequency selection are poor, and the stability is insufficient are solved.

Description

Technical Field

[0001] The present application relates to the technical field of ionospheric detection, and in particular to a shortwave communication frequency selection method and device based on ionospheric oblique return detection. Background Art

[0002] Shortwave communication is a key form of radio communication. After being transmitted, radio waves reflect off the ionosphere before reaching receiving devices, allowing for long-range communication. It is also the only long-distance communication method not constrained by active repeater systems. Through multiple reflections from the ionosphere, shortwave communication can provide global coverage, including areas beyond the reach of ultra-shortwave, such as mountainous areas, deserts, and oceans. Shortwave communication does not require satellites, is inexpensive to build and maintain, and offers exceptional flexibility, resilience, and stability.

[0003] The ionosphere is a highly dependent channel for shortwave communications, and its time-varying dispersion can affect their effectiveness. Because the state of the ionosphere is significantly affected by solar activity and seasonal variations, and abnormal conditions frequently occur, real-time shortwave communications require on-the-spot switching of communication frequencies based on the ionosphere's state to ensure quality and stability.

[0004] At present, although the autonomous frequency selection technology used in shortwave communication integrates spectrum sensing technology and historical communication data, it does not take into account the ionospheric factors that have a significant impact on shortwave transmission, but only performs real-time frequency selection based on noise and historical experience data. In addition, the existing autonomous frequency selection does not take into account the frequency selection coordination between users, and may face frequency selection conflicts when conducting regional networking. Especially in small areas, the frequency selection performance may decline, and it may encounter problems such as electromagnetic interference and location exposure, resulting in insufficient stability.

[0005] In summary, the existing shortwave communication frequency selection method does not take into account the ionospheric factors that have an important impact on shortwave transmission and the frequency selection coordination between users. The accuracy and reliability of frequency selection are poor, and the stability is insufficient, which needs to be solved urgently. Summary of the Invention

[0006] The present application provides a shortwave communication frequency selection method and device based on ionospheric oblique return detection to solve the problems that the existing shortwave communication frequency selection method does not take into account the ionospheric factors that have a significant impact on shortwave transmission and the frequency selection coordination between users, and the frequency selection accuracy and reliability are poor, and the stability is insufficient.

[0007] The first embodiment of the present application provides a shortwave communication frequency selection method based on ionospheric oblique return detection, comprising the following steps: obtaining the geographic coordinates of a target mobile station, and determining the great circle distance between the target mobile station and a main base station according to the geographic coordinates, so as to establish an initial ionospheric model through a link corresponding to the great circle distance; performing an oblique return sweep detection operation through the ionospheric detector of the main base station to obtain an oblique return ionogram, and performing echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, and extracting local ionospheric parameters from the vertical echo, and performing leading edge separation on the oblique return wave. Tracing to obtain the oblique return wave front tracing result; based on the initial ionosphere model, performing ionospheric parameter inversion on the oblique return wave front tracing result to obtain an inversion result, and using the local ionosphere parameters to constrain the inversion result to reconstruct the reflection area ionosphere model, and constructing a two-dimensional electron concentration profile through the reflection area ionosphere model; calculating the passable frequency range between the target mobile station and the main base station according to the two-dimensional electron concentration profile, and obtaining the signal-to-noise ratio characteristics corresponding to the oblique return ionogram, and using the signal-to-noise ratio characteristics to determine the target communication frequency, so as to construct a recommended communication frequency group through the passable frequency range and the target communication frequency.

[0008] Optionally, in one embodiment of the present application, the ionospheric detector of the main base station performs an oblique return frequency sweep detection operation to obtain an oblique return ionogram, and performs echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, including: determining a starting frequency, an ending frequency, and a step frequency of a frequency sweep modulation signal according to different ionospheric states, and generating a target frequency sweep modulation signal through the starting frequency, the ending frequency, and the step frequency, so as to transmit the target frequency sweep modulation signal through the main base station using a circular antenna; receiving an oblique return echo signal corresponding to the target frequency sweep modulation signal, and performing data processing on the oblique return echo signal to generate the oblique return ionogram; constructing an ionogram echo training data set, and training a pre-constructed ionogram echo recognition model through the ionogram echo training data set, and performing pattern recognition on the oblique return ionogram using the trained ionogram echo recognition model to obtain the vertical echo and oblique return wave corresponding to the oblique return ionogram.

[0009] Optionally, in one embodiment of the present application, the ionospheric parameter inversion is performed on the oblique return wave front tracing result based on the initial ionospheric model to obtain the inversion result, including: fitting the oblique return wave front tracing result based on an exponential function, a cubic polynomial function and a linear function, and obtaining fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function respectively; judging whether the fitting curve meets the preset incremental requirement within the target frequency range, wherein if the fitting curve meets the preset incremental requirement, then calculating the root mean square error and the self-correction of the fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function. Adjusting the R-squared by the degree of freedom; determining a target fitting method according to the root mean square error and the degree of freedom adjusted R-squared; determining a search space of the parameters critical frequency, peak height, and half thickness of the initial ionosphere model through the initial ionosphere model and the target fitting method; calculating a target front tracing set in the search space, and comparing the target front tracing set with the oblique return wave front tracing result to obtain a comparison result; based on the comparison result and a hybrid genetic algorithm, determining the ionosphere parameters of the search space of the parameters critical frequency, peak height, and half thickness when the preset matching requirements are met, and using the ionosphere parameters as the inversion result.

[0010] Optionally, in one embodiment of the present application, the two-dimensional electron concentration profile is used to calculate the communicable frequency range between the target mobile station and the main base station, and the signal-to-noise ratio characteristics corresponding to the oblique return ionization map are obtained, and the target communication frequency is determined using the signal-to-noise ratio characteristics, including: calculating the electron concentration distribution according to the inversion result and the preset ionospheric quasi-parabolic model, and solving the preset Haselgrove ordinary differential equations based on the preset numerical ray tracing strategy to obtain a radio wave propagation trajectory diagram; calculating the radio wave propagation trajectory diagram and the electron concentration distribution based on the target mobile station and the main base station. a passable frequency range between; obtaining a signal-to-noise ratio feature corresponding to the oblique return ionogram, and determining the energy distribution of the oblique return wave according to the signal-to-noise ratio feature; calculating the radio wave propagation group distance corresponding to the great circle distance based on the energy distribution, and searching the oblique return ionogram for at least one frequency value with a larger signal-to-noise ratio at the corresponding radio wave group distance according to a preset search frequency range, and using the at least one frequency value as the target communication frequency, wherein the minimum value of the search frequency range is the F2 layer critical frequency in the local ionosphere parameters, and the maximum value of the search frequency range is the maximum passable frequency value of the passable frequency range.

[0011] The second aspect embodiment of the application provides a short-wave communication frequency selection device based on ionospheric oblique return detection, comprising: a modeling module, configured to obtain geographical coordinates of a target mobile station, and determine a great circle distance between the target mobile station and a main base station according to the geographical coordinates, so as to establish an initial ionospheric model through a link corresponding to the great circle distance; a detection module, configured to perform an oblique return sweep detection operation through an ionospheric detector of the main base station, obtain an oblique return ionogram, and separate echoes of the oblique return ionogram to obtain a vertical sounding echo and an oblique return wave corresponding to the oblique return ionogram, extract local ionospheric parameters from the vertical sounding echo, and perform front tracing on the oblique return wave to obtain an oblique return wave front tracing result; an inversion module, configured to perform ionospheric parameter inversion on the oblique return wave front tracing result based on the initial ionospheric model to obtain an inversion result, and constrain the inversion result by using the local ionospheric parameters to reconstruct a reflection zone ionospheric model, and construct a two-dimensional electron concentration profile through the reflection zone ionospheric model; and a frequency selection module, configured to calculate a passable frequency range between the target mobile station and the main base station according to the two-dimensional electron concentration profile, obtain a signal-to-noise ratio feature corresponding to the oblique return ionogram, and determine a target communication frequency by using the signal-to-noise ratio feature, so as to construct a recommended communication frequency group through the passable frequency range and the target communication frequency.

[0012] Optionally, in an embodiment of the application, the detection module comprises: a transmitting unit, configured to determine a start frequency, a stop frequency and a step frequency of a sweep frequency modulation signal according to different ionospheric states, generate a target sweep frequency modulation signal through the start frequency, the stop frequency and the step frequency, and transmit the target sweep frequency modulation signal through a surrounding antenna of the main base station; a receiving unit, configured to receive an oblique return echo signal corresponding to the target sweep frequency modulation signal, and perform data processing on the oblique return echo signal to generate the oblique return ionogram; and an echo separation unit, configured to construct an ionogram echo training data set, train a pre-constructed ionogram echo recognition model through the ionogram echo training data set, and perform pattern recognition on the oblique return ionogram by using the trained ionogram echo recognition model to obtain the vertical sounding echo and the oblique return wave corresponding to the oblique return ionogram.

[0013] Optionally, in an embodiment of the present application, the inversion module comprises: a fitting unit configured to fit the oblique return wave front trace result based on an exponential function, a cubic polynomial function and a linear function to obtain a fitting curve corresponding to the exponential function, the cubic polynomial function and the linear function respectively; a judging unit configured to judge whether the fitting curve meets a preset increasing requirement in a target frequency range, wherein if the fitting curve meets the preset increasing requirement, the judging unit is further configured to calculate a root mean square error and a degree of freedom adjusted R square of the fitting curve corresponding to the exponential function, the cubic polynomial function and the linear function; a first determining unit configured to determine a target fitting mode according to the root mean square error and the degree of freedom adjusted R square; a second determining unit configured to determine a search space of a parameter critical frequency, a peak height and a half thickness of the initial ionospheric model based on the initial ionospheric model and the target fitting mode; a comparing unit configured to calculate a target front trace set in the search space and compare the target front trace set with the oblique return wave front trace result to obtain a comparison result; and a third determining unit configured to determine ionospheric parameters of the search space of the parameter critical frequency, the peak height and the half thickness when meeting a preset matching requirement based on the comparison result and a hybrid genetic algorithm, and take the ionospheric parameters as the inversion result.

[0014] Optionally, in an embodiment of the present application, the frequency selection module comprises: a first calculating unit configured to calculate an electron concentration distribution according to the inversion result and a preset ionospheric quasi-parabolic model, and solve a preset Haselgrove ordinary differential equation set based on a preset numerical ray tracing strategy to obtain an electric wave propagation trajectory diagram; a second calculating unit configured to calculate a passable frequency range between the target mobile station and the main base station based on the electric wave propagation trajectory diagram and the electron concentration distribution; an acquiring unit configured to acquire a signal-to-noise ratio feature corresponding to the oblique return ionospheric map, and determine an energy distribution of the oblique return wave according to the signal-to-noise ratio feature; and a searching unit configured to calculate an electric wave propagation group distance corresponding to the great circle distance based on the energy distribution, and search for at least one frequency value with a relatively large signal-to-noise ratio in the electric wave group distance in the oblique return ionospheric map according to a preset search frequency range, and take the at least one frequency value as the target communication frequency, wherein a minimum value of the search frequency range is an F2 layer critical frequency in the local ionospheric parameters, and a maximum value of the search frequency range is a passable frequency maximum value of the passable frequency range.

[0015] An electronic device is provided in the third aspect of the embodiments of the present application, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor. The processor executes the program to implement the shortwave communication frequency selection method based on ionospheric oblique return detection as described in the above embodiments.

[0016] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the ionospheric oblique return detection based short wave communication frequency selection method.

[0017] The fifth aspect of the present application provides a computer program product, which includes a computer program, and the computer program is executed to implement the ionospheric oblique return detection based short wave communication frequency selection method.

[0018] Therefore, the embodiments of the present application have the following beneficial effects:

[0019] The embodiments of the present application can perform oblique return detection by using an ionospheric detection system, obtain an oblique return ionogram, separate the vertical echo and the oblique return wave from the ionogram by a pattern recognition method, read out the local ionospheric parameter information from the vertical echo, trace the front of the oblique return wave, then perform ionogram inversion, fuse the local ionospheric parameter information with the inversion result, reconstruct the ionospheric model of the reflection area, construct a two-dimensional electron concentration profile, calculate the corresponding passable frequency range by using a ray tracing method, and finally select the optimal communication frequency point according to the signal-to-noise ratio information reflected by the ionogram. When performing frequency selection, the present application introduces real-time ionospheric detection data and fuses environmental monitoring data, thereby further improving the accuracy and reliability of frequency selection. Meanwhile, the present application only needs to perform detection by a single station, reduces the cost and workload, and improves the efficiency, which is of great significance and application prospect for the stability of communication between two users. Thus, the existing short wave communication frequency selection method does not consider the ionospheric factor which has an important influence on short wave transmission and the frequency selection coordination between users, and has poor accuracy and reliability and insufficient stability.

[0020] Additional aspects and advantages of the present application will be made apparent by the following description and the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood by practicing the application from the following detailed description, the accompanying drawings, and the appended claims.

[0022] Figure 1 A flow chart of an ionospheric oblique return detection based short wave communication frequency selection method according to an embodiment of the present application is shown in FIG. 1;

[0023] Figure 2 A logic architecture schematic diagram of an ionospheric oblique return detection based short wave communication frequency selection method according to an embodiment of the present application is shown in FIG. 2;

[0024] Figure 3 An execution logic schematic diagram of a short-wave communication frequency selection method based on ionospheric oblique return detection provided by an embodiment of the present application;

[0025] Figure 4 (a) in the above is an ionospheric oblique return ionogram result schematic diagram provided by an embodiment of the present application;

[0026] Figure 4 (b) in the above is a mode recognition-based vertical sounding echo separation schematic diagram provided by an embodiment of the present application;

[0027] Figure 4 (c) in the above is a pure oblique return wave result schematic diagram separated by mode recognition provided by an embodiment of the present application;

[0028] Figure 4 (d) in the above is a front trace extraction result schematic diagram of the oblique return wave provided by an embodiment of the present application;

[0029] Figure 5 A result schematic diagram of the oblique return wave extended by three fitting modes provided by an embodiment of the present application;

[0030] Figure 6 A link two-dimensional electron concentration distribution and ray tracing result schematic diagram constructed by ionospheric inversion provided by an embodiment of the present application;

[0031] Figure 7 A pD transformation schematic diagram obtained by ionospheric inversion provided by an embodiment of the present application;

[0032] Figure 8 A result schematic diagram of an optimal frequency provided by an embodiment of the present application;

[0033] Figure 9 An oblique sounding ionogram obtained by ionospheric oblique detection provided by an embodiment of the present application;

[0034] Figure 10 An example diagram of a short-wave communication frequency selection device based on ionospheric oblique return detection according to an embodiment of the present application;

[0035] Figure 11 A structure schematic diagram of an electronic device provided by an embodiment of the present application.

[0036] Among them, 10 is a short-wave communication frequency selection device based on ionospheric oblique return detection; 100 is a modeling module, 200 is a detection module, 300 is an inversion module, 400 is a frequency selection module; 1101 is a memory, 1102 is a processor, and 1103 is a communication interface. DETAILED DESCRIPTION

[0037] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0038] The following describes a shortwave communication frequency selection method and device based on ionospheric oblique return detection according to an embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a shortwave communication frequency selection method based on ionospheric oblique return detection. In this method, an ionospheric detection system is used to perform oblique return detection to obtain an oblique return ionogram. A pattern recognition method is used to separate the vertical echo and the oblique return wave from the ionogram. Local ionospheric parameter information is read from the vertical echo. The oblique return wave front is traced, and then the ionogram is inverted. The local ionospheric parameter information is fused with the inversion result, the reflection area ionosphere model is reconstructed, a two-dimensional electron concentration profile is constructed, and a ray tracing method is used to calculate the corresponding passable frequency range. Finally, the optimal communication frequency point is selected based on the signal-to-noise ratio information reflected in the ionogram. This application introduces real-time ionospheric detection data and integrates environmental monitoring data during frequency selection, further improving the accuracy and reliability of frequency selection. Furthermore, this application only requires a single station for detection, reducing costs and workload, improving efficiency, and having significant implications and promising applications for the stability of communications between users. This addresses the issues of existing shortwave communication frequency selection methods, which fail to consider ionospheric factors and inter-user frequency selection coordination, which have a significant impact on shortwave transmission, resulting in poor accuracy and reliability, as well as insufficient stability.

[0039] Specifically, Figure 1 A flowchart of a shortwave communication frequency selection method based on ionospheric oblique return detection provided in an embodiment of the present application.

[0040] like Figure 1 As shown, the shortwave communication frequency selection method based on ionospheric oblique return detection includes the following steps:

[0041] In step S101, the geographic coordinates of the target mobile station are obtained, and the great circle distance between the target mobile station and the master base station is determined according to the geographic coordinates, so as to establish an initial ionospheric model through the link corresponding to the great circle distance.

[0042] The embodiment of the present application firstly needs to obtain the geographic coordinates of the mobile station and the main base station for establishing a link, and the great circle distance D between the two stations, and to establish an initial ionospheric background model (i.e. initial ionospheric model) in the space of the link by using ionospheric model statistical data;

[0043] It should be noted that in the embodiment of the present application, the positions of the two stations can be represented by geographic longitude and latitude coordinates, and the great circle distance D between the two points can be calculated by geographic coordinates, wherein one station is taken as a probe signal transmitting station (i.e. main base station) for transmitting ionospheric probe signals and receiving ionospheric oblique return probe echoes.

[0044] In addition, the embodiment of the present application can use the International Reference Ionosphere (IRI) model to construct the initial ionospheric background model, i.e. by calling the IRI model, inputting geographic longitude, geographic latitude range, height range, time information, obtaining the distribution rules of ionospheric parameters such as ionospheric critical frequency, peak height, and half thickness of the link between the two stations with different great circle distances, and the distribution of electron concentration in space.

[0045] Therefore, the embodiment of the present application obtains the geographic coordinates of the transmitting station and the receiving station (i.e. target mobile station) by using ionospheric model statistical data to establish an initial ionospheric background model in the space of the link, thereby providing reliable data support for subsequent construction of oblique return ionograms and execution of ionospheric parameter inversion operations.

[0046] In step S102, the oblique return sweep detection operation is performed by the ionospheric probe of the main base station to obtain the oblique return ionogram, and the echo separation is performed on the oblique return ionogram to obtain the vertical sounding echo and the oblique return echo corresponding to the oblique return ionogram, and the local ionospheric parameters are extracted from the vertical sounding echo, and the front tracing is performed on the oblique return echo to obtain the oblique return echo front tracing result.

[0047] Further, the embodiment of the present application can use the ionospheric probe of the transmitting station to perform oblique return sweep detection to obtain the ionospheric oblique return ionogram, and use the pattern recognition method to perform echo separation on the oblique return ionogram to obtain the vertical sounding echo and the oblique return echo corresponding to the oblique return ionogram, as shown in Figure 2 and the local ionospheric parameters are extracted from the vertical sounding echo, and the front tracing is performed on the oblique return echo to obtain the oblique return echo front tracing result.

[0048] Optionally, in an embodiment of the present application, the oblique return sweep frequency detection operation is performed by the ionospheric probe of the main base station to obtain an oblique return ionogram, and the echo separation is performed on the oblique return ionogram to obtain the vertical sounding echo and the oblique return wave corresponding to the oblique return ionogram, including: determining the start frequency, the end frequency and the step frequency of the sweep frequency modulation signal according to different ionospheric states, and generating a target sweep frequency modulation signal through the start frequency, the end frequency and the step frequency, so that the target sweep frequency modulation signal is transmitted by the main base station through the surrounding antenna; receiving the oblique return echo signal corresponding to the target sweep frequency modulation signal, and performing data processing on the oblique return echo signal to generate an oblique return ionogram; constructing an ionogram echo training data set, and training a pre-constructed ionogram echo recognition model through the ionogram echo training data set, and using the trained ionogram echo recognition model to perform pattern recognition on the oblique return ionogram to obtain the vertical sounding echo and the oblique return wave corresponding to the oblique return ionogram.

[0049] In an embodiment of the present application, the ionospheric probe of the transmitting station can be used to perform oblique return sweep frequency detection to obtain an ionospheric oblique return ionogram, and a pattern recognition method can be used to separate the ionogram echo to extract local ionospheric parameters from the vertical sounding echo and to perform front trace on the oblique return wave.

[0050] It should be noted that, in the embodiments of the present application, the start frequency, the end frequency and the step frequency of the sweep frequency are set according to different ionospheric states, so that the transmitting station can transmit the m-sequence sweep frequency modulation signal through the surrounding antenna, and the oblique return echo signal can be received through the two-wire dipole antenna at the same place, and the received signal can be processed to draw an oblique return detection ionogram.

[0051] It can be understood that, since the transmitting antenna lobe is wide during oblique return detection, part of the transmitted signal energy may be emitted in the zenith direction, so that the obtained ionogram contains not only the oblique return wave but also the vertical sounding echo. Therefore, the embodiments of the present application can use a pattern recognition method to separate the echo, so as to obtain relatively pure vertical sounding echo and oblique return wave, and perform subsequent processing.

[0052] As an achievable approach, the pattern recognition method in the embodiment of the present application may adopt a machine learning model. Specifically, the embodiment of the present application may first construct an ionogram echo training data set, annotate the historical ionogram echoes, and divide them into two types of label values, "Vertical" and "Backscatter", corresponding to vertical echoes and oblique return waves, respectively. The ionogram echo training data set is used to train a pre-constructed ionogram echo recognition model (such as a YOLO model, etc.) to perform pattern recognition and separate the two types of echoes in the detected oblique return ionogram. In addition, the embodiment of the present application may obtain the local ionospheric F2 layer critical frequency foF2 from the extracted relatively pure vertical echo, and obtain the local ionospheric F2 layer peak height hmF2 value according to the empirical formula for the F2 layer peak height, as shown in Formula (1).

[0053] hmF2=h(foF2×0.83)(1)

[0054] Afterwards, the embodiment of the present application outlines the echo bottom of the extracted relatively pure oblique return wave, thereby obtaining the oblique return wave front tracing result.

[0055] Therefore, the embodiments of the present application can introduce the ionospheric factor, on which shortwave communication is highly dependent, into the frequency selection, and provide different communication frequencies in real time according to changes in the ionospheric state, thereby further improving the accuracy and stability of the frequency selection and meeting regional networking requirements.

[0056] In step S103, based on the initial ionospheric model, the ionospheric parameters are inverted for the oblique return wave front tracing results to obtain the inversion results, and the inversion results are constrained by the local ionospheric parameters to reconstruct the ionospheric model of the reflection area, and a two-dimensional electron concentration profile is constructed through the ionospheric model of the reflection area.

[0057] Furthermore, the embodiments of the present application use the initial ionospheric model as the initial value, use the ionogram inversion technology to invert the ionospheric parameters of the oblique return wave front tracing results, and use the detection results and inversion results to perform data fusion to reconstruct the ionospheric model of the reflection area, and calculate the two-dimensional information of the ionospheric electron concentration with respect to the ground great circle distance and altitude, thereby comprehensively describing the ionospheric situation in the reflection area.

[0058] Optionally, in one embodiment of the present application, based on the initial ionospheric model, the ionospheric parameter inversion is performed on the oblique return wave front tracing result to obtain the inversion result, including: fitting the oblique return wave front tracing result based on the exponential function, the cubic polynomial function and the linear function, and obtaining the fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function respectively; judging whether the fitting curve meets the preset incremental requirement within the target frequency range, wherein if the fitting curve meets the preset incremental requirement, then calculating the root mean square error and the root mean square error of the fitting curve corresponding to the exponential function, the cubic polynomial function and the linear function. The degrees of freedom are adjusted for R-square; the target fitting method is determined based on the root mean square error and the degrees of freedom adjusted for R-square; the search space of the critical frequency, peak height, and half-thickness parameters of the initial ionospheric model is determined through the initial ionospheric model and the target fitting method; the target front tracing set is calculated in the search space, and the target front tracing set is compared with the oblique return wave front tracing results to obtain a comparison result; based on the comparison result and the hybrid genetic algorithm, the ionospheric parameters of the search space of the critical frequency, peak height, and half-thickness parameters are determined when the preset matching requirements are met, and the ionospheric parameters are used as the inversion results.

[0059] It should be noted that the embodiments of the present application can use the ionospheric quasi-parabolic (QP) model to describe the electron concentration distribution and perform ionization map inversion. The mathematical expression of the QP model is as follows:

[0060]

[0061] Among them, N m is the maximum value of the corresponding ionospheric electron concentration. The general calculation method is f c It is the critical frequency shown on the ionospheric frequency diagram, usually calculated using o-waves; r m Indicates the maximum electron concentration N m The height at which it is located, referred to as peak height; r b Indicates the height of the bottom of the ionosphere; y m Represents half the thickness of the ionospheric electron concentration profile, calculated as y m =r m -r b .

[0062] In the actual implementation process, for the oblique return front trace, in order to invert the ionospheric parameters at a longer distance, the embodiment of the present application can fit and extend the front, and select three fitting methods: exponential function, cubic polynomial function, and linear function according to different situations to judge whether the three fitting curves increase consistently in the frequency range, and calculate the degree of freedom adjusted R square and relative root mean square error of the three fitting curves. After quantitative comparison, a relatively better fitting method is selected, and the root mean square error (RMSE) and the degree of freedom adjusted R square R 2 (adj) is calculated as follows:

[0063]

[0064] in, It represents the difference between the true value and the fitted value; represents the difference between the true value and its average value; n represents the number of samples; p is the number of variables; in the embodiment of the present application, R 2 The larger (adj) is, the better the fitting effect is.

[0065] In the process of inverting the leading edge trace, the embodiment of the present application can first select several points from the extracted leading edge trace, and according to the set initial ionosphere model, set the search space of the model parameters critical frequency foF2, peak height hmF2, and half thickness ymF2, and use a hybrid genetic algorithm to find the parameter group (i.e., the target inversion parameter group) that can achieve the best inversion effect within the corresponding parameter range, and use it as the inversion result. At the same time, the local ionosphere parameter information extracted from the vertical echo is used to constrain the inversion result.

[0066] Therefore, when performing frequency selection, the embodiments of the present application take into account the ionospheric factors that have an important impact on shortwave communications, introduce real-time ionospheric detection data, and integrate environmental monitoring data to further improve the accuracy and reliability of frequency selection, thereby enriching the research content in the field of data fusion, and serving as an attempt and exploration for frequency selection by integrating multiple influencing factors such as ionospheric detection data and environmental monitoring data in the field of shortwave communications.

[0067] In step S104, the passable frequency range between the target mobile station and the main base station is calculated based on the two-dimensional electron concentration profile, and the signal-to-noise ratio characteristics corresponding to the oblique return ionization map are obtained. The target communication frequency is determined using the signal-to-noise ratio characteristics to construct a recommended communication frequency group based on the passable frequency range and the target communication frequency.

[0068] Afterwards, the embodiments of the present application can calculate the passable frequency range of the distance D between the two stations based on the two-dimensional electron concentration profile and use ray tracing technology, and select the optimal communication frequency (i.e., the target communication frequency) based on the energy distribution of the oblique return detection echo, thereby constructing a recommended communication frequency group through the passable frequency range and the target communication frequency.

[0069] Therefore, in the embodiment of the present application, only a single station is required to perform detection during frequency selection, and no collaborative detection work is required between two stations, thereby reducing costs and workload and improving efficiency.

[0070] Optionally, in one embodiment of the present application, the communicable frequency range between the target mobile station and the main base station is calculated based on the two-dimensional electron concentration profile, and the signal-to-noise ratio characteristics corresponding to the oblique return ionization map are obtained, and the target communication frequency is determined using the signal-to-noise ratio characteristics, including: calculating the electron concentration distribution based on the inversion result and the preset ionospheric quasi-parabolic model, and solving the preset Haselgrove ordinary differential equations based on the preset numerical ray tracing strategy to obtain a radio wave propagation trajectory diagram; calculating the target mobile station and the main base station based on the radio wave propagation trajectory diagram and the electron concentration distribution. The communication frequency range between stations is obtained; the signal-to-noise ratio characteristics corresponding to the oblique return ionogram are obtained, and the energy distribution of the oblique return wave is determined according to the signal-to-noise ratio characteristics; based on the energy distribution, the radio wave propagation group distance corresponding to the great circle distance is calculated, and according to a preset search frequency range, at least one frequency value with a large signal-to-noise ratio at the corresponding radio wave group distance is searched in the oblique return ionogram, and at least one frequency value is used as the target communication frequency, wherein the minimum value of the search frequency range is the F2 layer critical frequency in the local ionosphere parameters, and the maximum value of the search frequency range is the maximum value of the passable frequency in the passable frequency range.

[0071] In the specific implementation process, the embodiments of the present application can obtain the great circle distance D between the two communicating stations through the relative geographic coordinate relationship, and can solve the Haselgrove ordinary differential equations through the numerical ray tracing technology in the ray tracing technology to obtain the radio wave propagation trajectory diagram, thereby finding the regular relationship between the ionospheric electron concentration and the signal propagation group path, ground distance, elevation angle, frequency, etc., and finally obtain the passable frequency range at the corresponding distance.

[0072] It should be noted that, in the embodiment of the present application, the energy distribution of the oblique return detection echo can be reflected by the echo signal-to-noise ratio in the oblique return ionogram. The embodiment of the present application can obtain the radio wave group distance p corresponding to D through ionospheric inversion based on the great circle distance D between the two stations, and then search for several frequency values ​​with a large signal-to-noise ratio at the corresponding group distance in the ionogram, and use it as the selected optimal communication frequency.

[0073] As an implementable manner, the embodiments of the present application can utilize the pD conversion technology, and obtain the corresponding wave group distance p according to the great circle distance D. In the ionospheric single-layer QP model, the relationship between the group distance p of the ray with the frequency f and the elevation angle a and the ground great circle distance D between the ray receiving point and the transmitting point can be directly obtained through ionospheric inversion, wherein the relationship between the group distance p and the great circle distance D is as follows:

[0074]

[0075] Wherein, the calculation methods of the above A, B, C, F and cosγ parameters are as follows:

[0076]

[0077] Wherein, γ is the incidence angle of the ray at the bottom of the ionosphere, β is the transmitting elevation angle of the signal, and r0 is the earth radius.

[0078] It should be noted that when searching for the optimal communication frequency in the search frequency range, the embodiments of the present application can first set the maximum value of the search frequency as the maximum value of the available frequency calculated by ray tracing, and set the minimum value of the frequency search as the F2 layer critical frequency foF2 obtained from the vertical echo, thereby avoiding the case that the selected frequency point corresponds to the existence of multi-mode propagation of the radio wave, and better improving the communication effect.

[0079] The execution logic of the shortwave communication frequency selection method based on ionospheric oblique return detection of the present application is described below in combination with the accompanying drawings.

[0080] Figure 3 The execution logic diagram of the shortwave communication frequency selection method based on ionospheric oblique return detection of the present application is shown in FIG. 1. Figure 3 As shown in FIG. 1, the execution logic of the shortwave communication frequency selection method based on ionospheric oblique return detection of the present application is described as follows:

[0081] S301: Obtain the geographic coordinates of the mobile station and the great circle distance between the mobile station and the main base station;

[0082] S302: Establish a spatial ionospheric background model using IRI model statistical data;

[0083] S303: Perform oblique return detection using the ionospheric detector of the main base station;

[0084] S304: Separate the echoes from the detected ionogram using the YOLO model;

[0085] S305: Extract local ionospheric parameters from the separated vertical echo, and perform front tracing on the oblique return wave;

[0086] S306: Using ionogram inversion technology to perform ionospheric parameter inversion on oblique return sounding data;

[0087] S307: Reconstruct the ionosphere model of the reflection region and construct a two-dimensional electron concentration profile using the inversion results and local ionosphere parameter information;

[0088] S308: Calculate the communicable frequency range between the two stations using ray tracing technology;

[0089] S309: Selecting the optimal communication frequency based on the energy distribution and signal-to-noise ratio of the oblique return detection echo;

[0090] S3010: The selected communicable frequency range and optimal communication frequency are used as a recommended communication frequency group.

[0091] The following describes the execution process and execution effect of the shortwave communication frequency selection method based on ionospheric oblique return detection of the present application through specific embodiments and in combination with the accompanying drawings.

[0092] In a specific embodiment of the present application, a conventional ionospheric detection system can be used to transmit an m-sequence frequency-sweep modulation signal to a circumferential antenna to perform ionospheric oblique return detection and obtain an oblique return ionogram, such as Figure 4 As shown in (a) in Figure 4 As shown in (a), the oblique return ionogram includes two regions: the oblique return wave and the vertical echo. Secondly, the pattern recognition method is used to separate the pure oblique return wave and the vertical echo, and the local ionospheric parameters are read from the separated vertical echo, such as Figure 4 As shown in (b), the critical frequency foF2 and peak height hmF2 of the local ionosphere F2 layer are obtained respectively. The pure oblique return wave separated by pattern recognition is shown as follows: Figure 4 As shown in (c) in the figure; then the separated oblique return wave is extracted by frontier tracing, as shown in Figure 4 As shown in (d), the thick solid line is the result of frontier tracing.

[0093] like Figure 5 As shown, the specific embodiment of the present application can fit and extend the oblique return wave through three fitting methods. The solid line represents the original oblique return front, the dotted line represents the exponential fitting result, the dotted line represents the cubic function fitting result, and the dot-dash line represents the linear fitting result. After quantitatively and comprehensively comparing the fitting effects of the three methods, the front fitting result that best conforms to the law of ionospheric change is selected. In the specific embodiment of the present application, the exponential fitting method has the highest degree of conformity.

[0094] Figure 6 The two-dimensional electron concentration distribution of the link and the ray tracing results constructed after inverting the ionization map are shown, as Figure 6As shown in the figure, the horizontal axis represents the great circle distance from the Wuhan station, the vertical axis represents the vertical height from the ground, and the color depth reflects the size of the electron concentration. The darker the color, the greater the electron concentration in the corresponding area. The search frequency of the ray is 7.0-25.0MHz, the step frequency is 0.5MHz, and the search range of the ray elevation angle is 15° to 60°, and the step angle is 5°. Figure 6 For the ray tracking result corresponding to the ray frequency 17.5MHz, from the trajectory of the ray, it can be seen that some rays with high elevation angles are reflected by the ionosphere and end up far away on the ground. Some rays with high elevation angles cannot be reflected by the ionosphere and directly penetrate through it, and after traversal, it can be obtained that when the required communication distance on the link is 915km, the available frequency range is 8.0-19.0MHz.

[0095] The pD transformation schematic diagram of the specific embodiment of the present application can be obtained by ionospheric inversion, as shown in the figure, the horizontal axis represents the great circle distance D, and the vertical axis represents the group distance p. Figure 7

[0096] The schematic result of selecting the optimal frequency in the specific embodiment of the present application is shown in the figure, and it can be known from the figure that Figure 8 Figure 8 It can be known that the picture background is the same as (a) in Figure 4 , which is the oblique return ionospheric map obtained by detection. The blue horizontal line represents the group distance p corresponding to the great circle distance D, and the value is obtained by pD transformation. From Figure 7 , the corresponding group distance is obtained, and the three frequency points with the best signal-to-noise ratio are 17.0MHz, 16.5MHz and 16.2MHz.

[0097] In the specific embodiment of the present application, Figure 9 is the oblique measurement ionospheric map result obtained by oblique detection of the ionosphere, which is used to verify the shortwave communication frequency selection method based on oblique return detection of the ionosphere of the present application; Figure 9 In the figure, the maximum available frequency is about 19.0MHz, and from Figure 9 , it can be seen that there are oblique measurement echoes in the frequency band from 8.0MHz to 19.0MHz. The frequency range obtained by ray tracing is in the frequency band, and the best communication frequency points selected from the oblique return ionospheric map are all in the oblique measurement echo range. It is proved that the frequency selected by the oblique return map can be used for effective communication.

[0098] ​​According to the shortwave communication frequency selection method based on ionospheric oblique return detection proposed in the embodiment of the present application, an ionospheric detection system is used to perform oblique return detection to obtain an oblique return ionogram, and a pattern recognition method is used to separate the vertical echo and the oblique return wave from the ionogram. The local ionospheric parameter information is read from the vertical echo, the oblique return wave front is traced, and then the ionogram is inverted. The local ionospheric parameter information and the inversion result are data-fused, the ionosphere model of the reflection area is reconstructed, a two-dimensional electron concentration profile is constructed, and the corresponding passable frequency range is calculated using the ray tracing method. Finally, the optimal communication frequency point is selected based on the signal-to-noise ratio information reflected in the ionogram. When performing frequency selection, the present application introduces real-time ionospheric detection data and integrates environmental monitoring data, thereby further improving the accuracy and reliability of frequency selection. At the same time, the present application only requires a single station for detection, which reduces cost and workload, improves efficiency, and has important significance and application prospects for the stability of communication between users on both sides.

[0099] Secondly, a shortwave communication frequency selection device based on ionospheric oblique return detection proposed in an embodiment of the present application is described with reference to the accompanying drawings.

[0100] Figure 10 It is a block diagram of a shortwave communication frequency selection device based on ionospheric oblique return detection according to an embodiment of the present application.

[0101] like Figure 10 As shown, the shortwave communication frequency selection device 10 based on ionospheric oblique return detection includes: a modeling module 100, a detection module 200, an inversion module 300 and a frequency selection module 400.

[0102] The modeling module 100 is used to obtain the geographic coordinates of the target mobile station and determine the great circle distance between the target mobile station and the main base station based on the geographic coordinates, so as to establish an initial ionospheric model through the link corresponding to the great circle distance.

[0103] The detection module 200 is used to perform an oblique return frequency sweep detection operation through the ionospheric sounder of the main base station to obtain an oblique return ionogram, perform echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, extract local ionospheric parameters from the vertical echo, and perform leading edge tracing on the oblique return wave to obtain an oblique return wave leading edge tracing result.

[0104] The inversion module 300 is used to perform ionospheric parameter inversion on the oblique return wave front tracing results based on the initial ionospheric model to obtain an inversion result, and to constrain the inversion result using local ionospheric parameters to reconstruct the ionospheric model of the reflection area, and to construct a two-dimensional electron concentration profile through the ionospheric model of the reflection area.

[0105] The frequency selection module 400 is used to calculate the passable frequency range between the target mobile station and the main base station based on the two-dimensional electron concentration profile, obtain the signal-to-noise ratio characteristics corresponding to the oblique return ionization map, and use the signal-to-noise ratio characteristics to determine the target communication frequency, so as to construct a recommended communication frequency group based on the passable frequency range and the target communication frequency.

[0106] Optionally, in one embodiment of the present application, the detection module 200 includes: a transmitting unit, a receiving unit and an echo separation unit.

[0107] Among them, the transmitting unit is used to determine the starting frequency, ending frequency and step frequency of the sweep frequency modulation signal according to different ionospheric states, and generate the target sweep frequency modulation signal through the starting frequency, ending frequency and step frequency, so as to transmit the target sweep frequency modulation signal through the main base station using the surrounding antenna.

[0108] The receiving unit is used to receive the oblique return echo signal corresponding to the target sweep frequency modulation signal, and perform data processing on the oblique return echo signal to generate an oblique return ionization map.

[0109] The echo separation unit is used to construct an ionogram echo training data set, and train a pre-constructed ionogram echo recognition model through the ionogram echo training data set, and use the trained ionogram echo recognition model to perform pattern recognition on the oblique return ionogram to obtain the vertical echo and oblique return wave corresponding to the oblique return ionogram.

[0110] Optionally, in one embodiment of the present application, the inversion module 300 includes: a fitting unit, a judgment unit, a first determination unit, a second determination unit, a comparison unit, and a third determination unit.

[0111] Among them, the fitting unit is used to fit the oblique return wave front tracing results based on the exponential function, the cubic polynomial function and the linear function, and obtain the fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function respectively.

[0112] A judgment unit is used to judge whether the fitting curve meets the preset incremental requirement within the target frequency range, wherein if the fitting curve meets the preset incremental requirement, the root mean square error and the degree of freedom adjusted R square of the fitting curve corresponding to the exponential function, the cubic polynomial function and the linear function are calculated.

[0113] The first determining unit is configured to determine a target fitting method according to a root mean square error and a degree of freedom adjusted R square.

[0114] The second determining unit is used to determine the search space of the parameters critical frequency, peak height, and half thickness of the initial ionosphere model through the initial ionosphere model and the target fitting method.

[0115] The comparison unit is configured to calculate a target front trace set in the search space, and compare the target front trace set with the oblique return wave front trace result to obtain a comparison result.

[0116] The third determination unit is configured to determine ionospheric parameters of the search space of the parameter critical frequency, the peak height and the half thickness when the preset matching requirement is met based on the comparison result and the hybrid genetic algorithm, and take the ionospheric parameters as the inversion result.

[0117] Optionally, in an embodiment of the present application, the frequency selection module 400 comprises a first calculation unit, a second calculation unit, an acquisition unit and a search unit.

[0118] The first calculation unit is configured to calculate the electron concentration distribution according to the inversion result and the preset ionospheric quasi-parabolic model, and solve the preset Haselgrove ordinary differential equation set based on a preset numerical ray tracing strategy to obtain the radio wave propagation trajectory diagram.

[0119] The second calculation unit is configured to calculate the passable frequency range between the target mobile station and the main base station based on the radio wave propagation trajectory diagram and the electron concentration distribution.

[0120] The acquisition unit is configured to acquire the signal-to-noise ratio feature corresponding to the oblique return ionospheric map, and determine the energy distribution of the oblique return wave according to the signal-to-noise ratio feature.

[0121] The search unit is configured to calculate the radio wave propagation group distance corresponding to the great circle distance based on the energy distribution, and search for at least one frequency value with a larger signal-to-noise ratio in the corresponding radio wave group distance in the oblique return ionospheric map according to a preset search frequency range, and take the at least one frequency value as the target communication frequency, wherein the minimum value of the search frequency range is the F2 layer critical frequency in the local ionospheric parameters, and the maximum value of the search frequency range is the passable frequency maximum value of the passable frequency range.

[0122] It should be noted that the foregoing explanation and description of the embodiment of the shortwave communication frequency selection method based on ionospheric oblique return detection also applies to the embodiment of the shortwave communication frequency selection device based on ionospheric oblique return detection, which will not be described here.

[0123] The short wave communication frequency selection device based on ionosphere oblique return detection provided by the embodiment of the application comprises a modeling module, which is used to obtain geographical coordinates of a target mobile station, and determine a great circle distance between the target mobile station and a main base station according to the geographical coordinates, so as to establish an initial ionosphere model through a link corresponding to the great circle distance; a detection module, which is used to perform an oblique return sweep detection operation through an ionosphere detector of the main base station, obtain an oblique return ionogram, and separate echoes of the oblique return ionogram to obtain a vertical measurement echo and a slant return wave corresponding to the oblique return ionogram, and extract local ionosphere parameters from the vertical measurement echo, and perform front tracing on the slant return wave to obtain a front tracing result of the slant return wave; an inversion module, which is used to perform ionosphere parameter inversion on the front tracing result of the slant return wave based on the initial ionosphere model to obtain an inversion result, and constrain the inversion result by using the local ionosphere parameters to reconstruct a reflection zone ionosphere model, and construct a two-dimensional electron concentration profile through the reflection zone ionosphere model; and a frequency selection module, which is used to calculate a passable frequency range between the target mobile station and the main base station according to the two-dimensional electron concentration profile, obtain a signal-to-noise ratio feature corresponding to the oblique return ionogram, and determine a target communication frequency by using the signal-to-noise ratio feature, so as to construct a recommended communication frequency group through the passable frequency range and the target communication frequency. When the frequency selection is performed, the real-time detection data of the ionosphere is introduced, and the environmental monitoring data is fused, so that the accuracy and reliability of the frequency selection are further improved, meanwhile, the application only needs to perform detection by using a single station, the cost and workload are reduced, the efficiency is improved, and the stability of communication of both users is of great significance and application prospect.

[0124] Figure 11 The structure schematic diagram of the electronic device provided by the embodiment of the application is provided. The electronic device can comprise:

[0125] The memory 1101, the processor 1102 and the computer program stored in the memory 1101 and executable on the processor 1102.

[0126] The processor 1102 implements the short wave communication frequency selection method based on ionosphere oblique return detection provided in the above embodiment when executing the program.

[0127] Further, the electronic device further comprises:

[0128] The communication interface 1103 is used for communication between the memory 1101 and the processor 1102.

[0129] The memory 1101 is used for storing the computer program executable on the processor 1102.

[0130] The memory 1101 can contain a high-speed RAM memory, and can also include a non-volatile memory, for example, at least one disk memory.

[0131] If the memory 1101, the processor 1102 and the communication interface 1103 are implemented independently, the communication interface 1103, the memory 1101 and the processor 1102 can be connected with each other through a bus and complete communication between each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 11 In the figure, only one thick line is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0132] Optionally, in a specific implementation, if the memory 1101, the processor 1102 and the communication interface 1103 are integrated on a chip, the memory 1101, the processor 1102 and the communication interface 1103 can complete communication between each other through an internal interface.

[0133] The processor 1102 can be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement one or more embodiments of the present application.

[0134] The embodiment of the present application further provides a computer readable storage medium, which has a computer program stored thereon, and the program is executed by a processor to implement the ionospheric oblique return detection based short wave communication frequency selection method.

[0135] The embodiment of the present application further provides a computer program product, which includes a computer program, and the computer program is executed to implement the ionospheric oblique return detection based short wave communication frequency selection method.

[0136] In the description of the application, reference to "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that a particular feature, structure, material, or characteristic being described is included in at least one embodiment or example of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment or example. Furthermore, the described specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples. In addition, the usage of "N" means at least two, for example, two, three or the like, unless explicitly stated otherwise.

[0137] Furthermore, the terms "first", "second", or the like, are used merely as a designation of certain elements or features of the application, and do not imply or connote relative importance or a specific order of precedence. Thus, features designated by these terms can include at least one of the features. In the description of the application, the term "N" means at least two, for example, two, three or the like, unless explicitly stated otherwise.

[0138] Any process or method descriptions or blocks in flow charts or otherwise described herein represent embodiments which can be managed as one or more modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions or steps, and alternate implementations are possible. In some embodiments, the processes and methods described can be executably encoded on a machine- readable medium in a data signal embodied in an electromagnetic signal, a wireless signal, or a propagated signal.

[0139] The logic and / or steps represented in the flowcharts and / or described herein, for example, can be considered as a sequence of instructions to implement logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device, such as a computer-based system, processor- based system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be a computer- readable storage medium or a computer-readable signal medium. The computer- readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires (electrical connections), a portable computer diskette (a magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for example, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

[0140] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware and in another embodiment, any of the following technologies, known in the art, or their combinations can be used: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

[0141] Those skilled in the art can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing related hardware, and the programs can be stored in a computer-readable storage medium. When the programs are executed, one or a combination of the steps of the method embodiments is included.

[0142] In addition, each of the functional units in the various embodiments of the present application can be integrated in one processing module, or each of the units can be physically present separately, or two or more units can be integrated in one module. The integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0143] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A shortwave communication frequency selection method based on ionospheric oblique return detection, characterized in that: The following steps are involved: Obtaining geographic coordinates of a target mobile station, and determining a great circle distance between the target mobile station and a master base station based on the geographic coordinates, so as to establish an initial ionospheric model through a link corresponding to the great circle distance; Performing an oblique return frequency sweep detection operation through the ionospheric sounder of the master base station to obtain an oblique return ionogram, performing echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, extracting local ionospheric parameters from the vertical echo, and performing front tracing on the oblique return wave to obtain an oblique return wave front tracing result; Based on the initial ionosphere model, ionosphere parameter inversion is performed on the oblique return wave front tracing result to obtain an inversion result, and the inversion result is constrained by the local ionosphere parameter to reconstruct the reflection area ionosphere model, and a two-dimensional electron concentration profile is constructed using the reflection area ionosphere model; A communicable frequency range between the target mobile station and the master base station is calculated based on the two-dimensional electron concentration profile, and a signal-to-noise ratio characteristic corresponding to the oblique return ionization diagram is obtained. A target communication frequency is determined using the signal-to-noise ratio characteristic, so as to construct a recommended communication frequency group using the communicable frequency range and the target communication frequency.

2. The method according to claim 1, characterized in that The method includes performing an oblique return frequency sweep detection operation by the ionospheric sounder of the master base station to obtain an oblique return ionogram, and performing echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, comprising: determining a starting frequency, an ending frequency, and a step frequency of a frequency sweep modulation signal according to different ionospheric states, and generating a target frequency sweep modulation signal using the starting frequency, the ending frequency, and the step frequency, so as to transmit the target frequency sweep modulation signal through the main base station using a circumferential antenna; receiving an oblique return echo signal corresponding to the target frequency sweep modulation signal, and performing data processing on the oblique return echo signal to generate the oblique return ionogram; An ionogram echo training data set is constructed, and a pre-constructed ionogram echo recognition model is trained using the ionogram echo training data set. The trained ionogram echo recognition model is used to perform pattern recognition on the oblique return ionogram to obtain the vertical echo and oblique return wave corresponding to the oblique return ionogram.

3. The method according to claim 2, characterized in that The method of performing ionospheric parameter inversion on the oblique return wave front trace result based on the initial ionospheric model to obtain an inversion result includes: Based on an exponential function, a cubic polynomial function and a linear function, fitting the oblique return wave front tracing result to obtain fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function respectively; determining whether the fitting curve satisfies a preset incremental requirement within a target frequency range, wherein if the fitting curve satisfies the preset incremental requirement, calculating a root mean square error and a degree of freedom adjusted R-squared of the fitting curves corresponding to the exponential function, the cubic polynomial function, and the linear function; Determining a target fitting method based on the root mean square error and the degree of freedom adjusted R square; Determine the search space of the parameters critical frequency, peak height, and half thickness of the initial ionosphere model by using the initial ionosphere model and the target fitting method; Calculating a target frontier trace set in the search space, and comparing the target frontier trace set with the oblique return wave frontier trace result to obtain a comparison result; Based on the comparison result and the hybrid genetic algorithm, the ionospheric parameters of the search space of the parameter critical frequency, the peak height and the half thickness are determined when the preset matching requirements are met, and the ionospheric parameters are used as the inversion results.

4. The method according to claim 3, characterized in that Calculating the communicable frequency range between the target mobile station and the master base station based on the two-dimensional electron concentration profile, obtaining a signal-to-noise ratio feature corresponding to the oblique return ionization map, and determining a target communication frequency using the signal-to-noise ratio feature includes: Calculating the electron concentration distribution according to the inversion results and a preset ionospheric quasi-parabolic model, and solving a preset Haselgrove ordinary differential equation system based on a preset numerical ray tracing strategy to obtain a radio wave propagation trajectory diagram; Calculating a communicable frequency range between the target mobile station and the master base station based on the radio wave propagation trajectory diagram and the electron concentration distribution; Acquiring a signal-to-noise ratio feature corresponding to the oblique return ionogram, and determining the energy distribution of the oblique return wave according to the signal-to-noise ratio feature; Based on the energy distribution, the radio wave propagation group distance corresponding to the great circle distance is calculated, and according to a preset search frequency range, at least one frequency value with a larger signal-to-noise ratio at the corresponding radio wave group distance is searched in the oblique return ionogram, and the at least one frequency value is used as the target communication frequency, wherein the minimum value of the search frequency range is the F2 layer critical frequency in the local ionosphere parameters, and the maximum value of the search frequency range is the maximum value of the passable frequency in the passable frequency range.

5. A shortwave communication frequency selection device based on ionospheric oblique return detection, characterized in that: include: a modeling module, configured to obtain geographic coordinates of a target mobile station, and determine a great circle distance between the target mobile station and a master base station based on the geographic coordinates, so as to establish an initial ionospheric model through a link corresponding to the great circle distance; a detection module, configured to perform an oblique return frequency sweep detection operation through the ionospheric sounder of the master base station to obtain an oblique return ionogram, perform echo separation on the oblique return ionogram to obtain a vertical echo and an oblique return wave corresponding to the oblique return ionogram, extract local ionospheric parameters from the vertical echo, and perform a front tracing on the oblique return wave to obtain an oblique return wave front tracing result; an inversion module, configured to perform ionospheric parameter inversion on the oblique return wave front tracing result based on the initial ionospheric model to obtain an inversion result, and to constrain the inversion result using the local ionospheric parameters to reconstruct the reflection region ionospheric model, and to construct a two-dimensional electron concentration profile using the reflection region ionospheric model; A frequency selection module is configured to calculate a communicable frequency range between the target mobile station and the master base station based on the two-dimensional electron concentration profile, obtain a signal-to-noise ratio characteristic corresponding to the oblique return ionization diagram, and determine a target communication frequency using the signal-to-noise ratio characteristic, so as to construct a recommended communication frequency group based on the communicable frequency range and the target communication frequency.

6. The device according to claim 5, characterized in that The detection module includes: a transmitting unit, configured to determine a starting frequency, an ending frequency, and a step frequency of a frequency sweep modulation signal according to different ionospheric states, and generate a target frequency sweep modulation signal using the starting frequency, the ending frequency, and the step frequency, so as to transmit the target frequency sweep modulation signal through the main base station using a circumferential antenna; a receiving unit, configured to receive an oblique return echo signal corresponding to the target frequency sweep modulation signal, and perform data processing on the oblique return echo signal to generate the oblique return ionogram; The echo separation unit is used to construct an ionogram echo training data set, and train a pre-constructed ionogram echo recognition model through the ionogram echo training data set, and use the trained ionogram echo recognition model to perform pattern recognition on the oblique return ionogram to obtain the vertical echo and oblique return wave corresponding to the oblique return ionogram.

7. The device according to claim 6, characterized in that The inversion module includes: A fitting unit is used to fit the oblique return wave front tracing result based on an exponential function, a cubic polynomial function and a linear function, and obtain fitting curves corresponding to the exponential function, the cubic polynomial function and the linear function respectively; a judgment unit, configured to judge whether the fitting curve satisfies a preset incremental requirement within a target frequency range, wherein if the fitting curve satisfies the preset incremental requirement, calculating a root mean square error and a degree of freedom adjusted R-squared of the fitting curves corresponding to the exponential function, the cubic polynomial function, and the linear function; A first determining unit is configured to determine a target fitting mode according to the root mean square error and the degree of freedom adjusted R square; A second determining unit is configured to determine a search space of parameters including critical frequency, peak height, and half thickness of the initial ionosphere model by using the initial ionosphere model and the target fitting method; a comparison unit, configured to calculate a target front tracing set in the search space, and compare the target front tracing set with the oblique return wave front tracing result to obtain a comparison result; A third determination unit is used to determine, based on the comparison result and the hybrid genetic algorithm, the ionospheric parameters of the search space of the parameter critical frequency, the peak height, and the half thickness when the preset matching requirements are met, and use the ionospheric parameters as the inversion result.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the shortwave communication frequency selection method based on ionospheric oblique return detection as described in any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the shortwave communication frequency selection method based on ionospheric oblique return detection as described in any one of claims 1 to 4.

10. A computer program product comprising a computer program, characterized in that The computer program is executed by a processor to implement the shortwave communication frequency selection method based on ionospheric oblique return detection as described in any one of claims 1 to 4.

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