Frequency quality analysis method, apparatus, electronic device, and system

Abstract

The present application relates to a kind of frequency quality analysis method, device, electronic equipment and system, belong to short wave communication technical field, wherein, the frequency quality analysis method includes: obtaining the Chirp probe data of periodic short wave communication link;Based on the Chirp probe data, the stationary signal intensity data and time delay data of probe frequency are calculated;From the monitoring data of target station, the average noise intensity data and monitoring occupancy degree data of short wave channel are extracted;Based on the stationary signal intensity data, the average noise intensity data and the monitoring occupancy degree data, the signal-to-noise ratio data of short wave channel is generated;According to the time delay data, the signal-to-noise ratio data and the monitoring occupancy degree data of each short wave channel, frequency quality analysis result is determined. Using Chirp probe data combines monitoring data to carry out frequency quality evaluation more directly reflects ionospheric channel state, improves short wave frequency prediction accuracy, provides important data support for frequency prediction planning.

Description

Technical Field

[0001] This invention relates to the field of shortwave communication technology, and in particular to a frequency quality analysis method, apparatus, electronic device, and system. Background Technology

[0002] Shortwave communication is one of the important means of long-distance and ultra-long-distance communication. It mainly uses skywave propagation and plays a crucial role in long-span communication.

[0003] In the prediction and calculation methods for shortwave skywave propagation, existing technical solutions mainly construct characteristic parameters of ionospheric emission points (including the reflection point positions, virtual heights, critical frequencies, transmission factors, electron activity indexes, electron density distributions, etc. of the E, F1, and F2 layers of the ionosphere), elevation angles, transmission paths, and transmission path control points through traditional semi-empirical formulas generated by Fourier transform. Then, transmission performance data such as shortwave propagation path loss and the highest available frequency of the link are obtained through trajectory calculation by ray tracing, thereby predicting the performance of shortwave communication.

[0004] Such forecasting methods often fail to accurately reflect the shortwave channel characteristics of a specific time and region. Summary of the Invention

[0005] In view of this, it is necessary to provide a frequency quality analysis method, apparatus, electronic equipment and system to solve the problem of inaccurate frequency quality assessment of shortwave links.

[0006] To address the above problems, this invention provides a frequency quality analysis method, comprising: Acquire Chirp probe data for periodic shortwave communication links; Based on the Chirp detection data, calculate the stable signal strength data and time delay data of the detection frequency; Extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station; Based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, the signal-to-noise ratio data of the shortwave channel is generated; The frequency quality analysis results are determined based on the time delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel.

[0007] In one possible implementation, the calculation of stationary signal strength data and time delay data at the detection frequency based on the Chirp detection data includes: The Chirp probe data is converted into binary data to generate the binary data required for frequency quality calculation. Based on the binary data, extract the signal strength data and time delay distribution data for each detection frequency; Construct a signal data matrix and a time delay data matrix in the time domain and frequency domain based on the signal strength data and the time delay distribution data; Based on the signal data matrix and the time delay data matrix, calculate the stable signal strength data and time delay data for each detection frequency.

[0008] In one possible implementation, the calculation of stationary signal strength data and time delay data for each detection frequency based on the signal data matrix and the time delay data matrix includes: Calculate the time-domain weighting coefficients; The stationary data within the period of each detection frequency are calculated based on the time-domain weighting coefficients, the signal data matrix, and the time delay data matrix. The stable data within the period is smoothed to obtain stable signal strength data and time delay data.

[0009] In one possible implementation, extracting the average noise intensity data and channel monitoring occupancy data of the shortwave channel from the monitoring data of the target station includes: Acquire monitoring data from the target station; Based on the frequency range of the shortwave channel, the shortwave frequency in the monitoring data is offline into multiple channel frequencies; Average noise intensity data and channel occupancy monitoring data of the shortwave channel are extracted from each channel frequency.

[0010] In one possible implementation, based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, signal-to-noise ratio (SNR) data for the shortwave channel is generated, including: Obtain the preset linear interpolation formula; The signal-to-noise ratio (SNR) of the shortwave channel is obtained by calculating the signal strength data, the average noise intensity data, and the monitoring occupancy data using the linear interpolation formula.

[0011] In one possible implementation, determining the frequency quality analysis result based on the delay data, the signal-to-noise ratio data, and the monitoring occupancy data of each shortwave channel includes: Based on the delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel, delay quality analysis results, signal-to-noise ratio quality analysis results, and occupancy quality analysis results are generated according to frequency quality standards. The frequency quality analysis results are determined based on the delay quality analysis results, the signal-to-noise ratio quality analysis results, and the occupancy quality analysis results.

[0012] In one possible implementation, determining the frequency quality analysis result based on the delay quality analysis result, the signal-to-noise ratio quality analysis result, and the occupancy quality analysis result includes: Obtain the application scenario information of the target station; The quality weight allocation information is determined based on the application scenario information. The frequency quality analysis results are obtained by weighting the delay quality analysis results, the signal-to-noise ratio quality analysis results, and the occupancy quality analysis results based on the quality weight allocation information.

[0013] Secondly, embodiments of this application also provide a frequency quality analysis device, comprising: an acquisition module, a processing module, an extraction module, a calculation module, and an analysis module; the acquisition module is used to acquire periodic Chirp detection data of shortwave communication links; the processing module is used to calculate stationary signal strength data and time delay data of the detection frequency based on the Chirp detection data; the extraction module is used to extract average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station; the calculation module is used to generate signal-to-noise ratio data of the shortwave channel based on the stationary signal strength data, the average noise intensity data, and the monitoring occupancy data; the analysis module is used to determine the frequency quality analysis result based on the time delay data, the signal-to-noise ratio data, and the monitoring occupancy data of each shortwave channel.

[0014] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the frequency quality analysis method described in any of the above implementations.

[0015] Fourthly, the present invention also provides a frequency quality analysis system, which includes the electronic device, data acquisition device and output device as described above. The electronic device is connected to the data acquisition device and the output device respectively. The data acquisition device is used to acquire periodic Chirp probe data of shortwave communication links, and the output device is used to generate and output frequency quality analysis results.

[0016] Fifthly, the frequency quality analysis system provided by the present invention includes the aforementioned electronic device and a computer-readable storage medium, wherein the storage medium is used to store a computer-readable program or instruction, and the program or instruction, when executed by the processor of the electronic device, is capable of implementing the steps in the frequency quality analysis method described in any of the above implementations.

[0017] The beneficial effects of this invention are as follows: The frequency quality analysis method provided by this invention acquires chirp probe data from periodic shortwave communication links, and then calculates the signal strength, delay-to-noise ratio, and monitoring occupancy data corresponding to the target station, thereby comprehensively evaluating frequency quality. Using chirp probe data in combination with monitoring data for frequency quality assessment more directly reflects the ionospheric channel state, improves the accuracy of shortwave frequency prediction, and provides important data support for frequency prediction planning. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the steps of a frequency quality analysis method provided in an embodiment of this application; Figure 2 A schematic diagram of the overall architecture of a frequency quality analysis method provided in an embodiment of this application; Figure 3 Another flowchart of the frequency quality analysis method provided in an embodiment of this application Figure 4 A functional block diagram of a frequency quality analysis device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0021] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] This invention provides a frequency quality analysis method, apparatus, electronic device, and system, which are described below.

[0024] Figure 1 This is a schematic flowchart of an embodiment of the frequency quality analysis method provided by the present invention. The execution subject of the frequency quality analysis method is a computer or server, or a portable smart terminal. This embodiment does not limit it to this.

[0025] like Figure 1 As shown, frequency quality analysis methods include: S101. Acquire Chirp probe data for periodic shortwave communication links.

[0026] It should be noted that the solution in this embodiment analyzes the performance characteristics of the shortwave communication link in multiple dimensions by combining the shortwave chirp detection data within the link composed of the fixed station and the designated grid area with the electromagnetic spectrum monitoring data. This includes signal strength, latency, electromagnetic background monitoring intensity, channel occupancy, etc., thereby evaluating the quality information of the shortwave channel frequency.

[0027] It should be understood that for each detection frequency, the signal energy is obtained from the FFT processing result of the detection receiver.

[0028] S102. Calculate the stable signal strength data and time delay data of the detection frequency based on the Chirp detection data.

[0029] In the actual implementation, after obtaining the Chirp probe data, the stationary signal strength data and time delay data are calculated.

[0030] In some embodiments, step S102 includes: performing binary data conversion processing on the Chirp probe data to generate binary data required for frequency quality calculation; extracting signal strength data and time delay distribution data for each probe frequency based on the binary data; constructing a time-domain and frequency-domain signal data matrix and a time delay data matrix based on the signal strength data and the time delay distribution data; and calculating the stationary signal strength data and time delay data for each probe frequency based on the signal data matrix and the time delay data matrix.

[0031] It should be noted that after the Fourier transform, the modulus of the signal exceeding the threshold peak value is taken as the signal energy P. i The detection frequency signal energy intensity E is generated by superimposing the signal energies and taking the logarithm. i It is converted into a binary data stream and saved.

[0032] It should be understood that, based on the binary data stream corresponding to the Chirp probe data, information within a specified data segment is extracted during frequency quality calculation to generate signal strength data E for each probe frequency. Scatter matrix data is generated from the binary data stream, and time delay distribution data D for each probe frequency is generated through pattern recognition methods.

[0033] In the specific implementation, signal data matrices and delay data matrices in the time and frequency domains are constructed. Through time-domain weighting and frequency-domain smoothing, the stationary signal strength data and delay data of the detection frequency are calculated.

[0034] In some embodiments, calculating the stationary signal strength data and time delay data for each detection frequency based on the signal data matrix and the time delay data matrix includes: calculating time-domain weighting coefficients; calculating periodic stationary data for each detection frequency based on the time-domain weighting coefficients, the signal data matrix, and the time delay data matrix; and smoothing the periodic stationary data to obtain stationary signal strength data and time delay data.

[0035] It should be noted that, firstly, the signal data matrix and the time delay data matrix are constructed.

[0036] Where n is the number of periodic samples in the time domain, m is the number of sample detection points in the frequency domain, and Z can be used as the signal energy data sample space or the time delay data sample space.

[0037] It should be understood that the time-domain weighting coefficients are then recalculated.

[0038] in, These are time-domain weighting coefficients. Through weighted analysis, the stationary signal energy intensity and time delay data for all detection frequencies within the current cycle can be generated.

[0039]

[0040] The calculated value for each probe is... E ij This refers to the element in the i-th row and j-th column of the matrix. At this point, the stationary numerical calculation within the period of each detection frequency is complete.

[0041] Specifically, to prevent jitter caused by frequency differences in the data receiving and processing, the data that has already undergone periodic stable processing needs to be smoothed in the frequency domain. The formula for signal energy smoothing is shown below.

[0042]

[0043] The time delay smoothing formula is as follows:

[0044] in These are the signal energy weighting coefficients for the shortwave channel frequency. This is the signal delay weighting coefficient for the shortwave channel frequency.

[0045] S103. Extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station.

[0046] It should be noted that the target station is the radio monitoring station that needs to be evaluated.

[0047] It should be understood that the average noise intensity data and monitoring occupancy data of the shortwave channel are then extracted by combining real-time monitoring data.

[0048] In some embodiments, step S103 includes: acquiring monitoring data of the target station; dividing the shortwave frequency in the monitoring data into multiple channel frequencies offline based on the frequency range of the shortwave channel; and extracting the average noise intensity data and channel monitoring occupancy data of each channel frequency.

[0049] In the specific implementation, monitoring data from the stations is acquired, and based on the frequency range of the shortwave channel, the shortwave frequency is divided into K channel frequencies offline. For each channel frequency, the average noise intensity data Q of the shortwave channel is extracted. k and channel monitoring occupancy data L k .

[0050] S104. Based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, generate the signal-to-noise ratio data of the shortwave channel.

[0051] It should be noted that the signal-to-noise ratio data is calculated again to facilitate subsequent quality analysis.

[0052] In some embodiments, step 104 includes: obtaining a preset linear interpolation formula; calculating the signal strength data, the average noise intensity data, and the monitoring occupancy data using the linear interpolation formula to obtain the signal-to-noise ratio data of the shortwave channel.

[0053] It should be understood that signal strength data and monitoring occupancy data are combined to generate the signal-to-noise ratio (SNR) data for the shortwave channel. .

[0054] Specifically, the key lies in calculating the signal strength and delay data of the shortwave channel frequency based on the detected frequency signal strength and delay data. Based on the observation of shortwave Chirp detection data and the analysis of radio wave propagation models, it can be assumed that the air propagation characteristics of radio waves are similar within a relatively narrow channel bandwidth. Therefore, in order to reduce the amount of computation and take into account the shortwave propagation characteristics, a linear interpolation method is used to calculate the signal strength and delay of the shortwave channel frequency.

[0055] The frequencies of the shortwave channel are discretized to generate K shortwave channel frequencies, each denoted as . ,and Two adjacent detection frequencies are denoted as follows: and The linear interpolation formula is as follows:

[0056]

[0057] The frequency signal-to-noise ratio of the shortwave channel is:

[0058] This completes the calculation of signal strength, delay, occupancy, signal-to-noise ratio, and other data for all shortwave channels within one cycle, denoted as . , , and .

[0059] S105. Determine the frequency quality analysis results based on the time delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel.

[0060] It should be noted that the final result of the frequency quality analysis is obtained by taking into account the time delay, signal-to-noise ratio, and monitoring occupancy together.

[0061] Compared with existing technologies, the frequency quality analysis method provided in this embodiment acquires periodic chirp probe data from shortwave communication links, and then calculates the signal strength, delay-to-noise ratio, and monitoring occupancy data corresponding to the target station, thereby comprehensively evaluating frequency quality. Using chirp probe data combined with monitoring data for frequency quality assessment more directly reflects the ionospheric channel state, improves the accuracy of shortwave frequency prediction, and provides important data support for frequency prediction planning.

[0062] Based on the above embodiments, a specific scenario implementation method for the frequency quality analysis method of this application is proposed.

[0063] Step 1: Obtain periodic Chirp probe data from the shortwave communication link, perform binary data conversion processing, and generate the data required for frequency quality calculation.

[0064] In the specific implementation process, the binary data stream of Chirp detection can be obtained by importing or connecting to a Chirp detection receiver, so as to achieve daily changes according to the time cycle.

[0065] Step 2: Based on the Chirp probe data generated in Step 1, extract the signal strength data E for each probe frequency and calculate the time delay data D for each probe frequency.

[0066] Step 3: Construct the signal data matrix and delay data matrix in the time and frequency domains. Through time-domain weighting and frequency-domain smoothing, calculate the stationary signal strength data and delay data at the detection frequency. The signal strength data and time delay data of the detected frequency within the generated cycle are saved to an electronic file or database for iterative retrieval in the next cycle, facilitating data calculation.

[0067] Step 4: Obtain the monitoring data from the station, and extract the average noise intensity data and monitoring occupancy data of the shortwave channel; Step 5: Combine the signal strength data from Step 3 and the monitoring occupancy data from Step 4 to generate the signal-to-noise ratio data for the shortwave channel; Step 6, as follows Figure 2 As shown, this is a frequency energy data distribution map calculated based on shortwave detection data. Finally, based on the time delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel calculated in steps 3 to 5, time delay quality score, signal-to-noise ratio quality score, and occupancy quality score are generated according to the frequency quality standard. Different weights for the quality scores are designed according to different application scenarios to generate a weighted comprehensive quality score.

[0068] During implementation, a quality score lookup table can be set for delay values, signal strength values, signal-to-noise ratio values, and occupancy values. During frequency quality calculation, evaluation can be quickly performed by looking up the table. It also facilitates adjustments between different business years and different systems, increasing the adaptability of this method.

[0069] Please refer to Figure 3 , Figure 3This is a flowchart illustrating the steps of one embodiment of the frequency quality analysis method of this application. Depending on different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted. This frequency quality analysis method can be applied to the aforementioned frequency quality analysis apparatus, but is not limited thereto, and the embodiments of this application do not limit it in this regard.

[0070] This embodiment is a further improvement on the aforementioned embodiment. The main improvement is that: in this embodiment, multi-dimensional performance characteristic analysis of the shortwave communication link is performed, including signal strength, time delay, electromagnetic background monitoring intensity, channel occupancy, etc., to evaluate the quality information of the shortwave channel frequency.

[0071] The specific process of this embodiment is as follows: Figure 3 As shown, it includes the following steps: S301. Based on the delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel, generate delay quality analysis results, signal-to-noise ratio quality analysis results, and occupancy quality analysis results according to the frequency quality standard.

[0072] It should be noted that, firstly, based on the calculated delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel, delay quality scores, signal-to-noise ratio quality scores, and occupancy quality scores are generated according to frequency quality standards, thereby determining the quality information of the shortwave channel frequency under different dimensions for evaluation.

[0073] S302. Determine the frequency quality analysis result based on the delay quality analysis result, the signal-to-noise ratio quality analysis result, and the occupancy quality analysis result.

[0074] It should be noted that after obtaining the quality analysis results from multiple dimensions, a weighted calculation is performed to obtain the comprehensive analysis result.

[0075] In some embodiments, step S302 includes: acquiring application scenario information of the target station; determining quality weight allocation information based on the application scenario information; and performing weighted calculations on the delay quality analysis result, the signal-to-noise ratio quality analysis result, and the occupancy quality analysis result based on the quality weight allocation information to obtain the frequency quality analysis result.

[0076] It should be understood that different quality score weights are designed according to different application scenarios, then the current weight allocation strategy is determined based on the application scenario corresponding to the current target station, and finally the weighted comprehensive quality score is generated based on the weight allocation strategy.

[0077] Compared with existing technologies, the frequency quality analysis method provided in this embodiment performs multi-dimensional performance characteristic analysis on shortwave communication links, including signal strength, time delay, electromagnetic background monitoring intensity, channel occupancy, etc., to evaluate the quality information of shortwave channel frequencies.

[0078] Based on the same concept as the frequency quality analysis method in the above embodiments, this application also provides a frequency quality analysis device, which can be used to perform the above-described frequency quality analysis method. For ease of explanation, the structural schematic diagram of the frequency quality analysis device embodiment only shows the parts related to the embodiments of this application. Those skilled in the art will understand that the illustrated structure does not constitute a limitation on the device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0079] like Figure 4 As shown, the frequency quality analysis device 400 includes an acquisition module 401, a processing module 402, an extraction module 403, a calculation module 404, and an analysis module 405. In some embodiments, the above modules can be programmable software instructions stored in memory and executable by a processor. It is understood that in other embodiments, the above modules can also be program instructions or firmware embedded in the processor.

[0080] The acquisition module 401 is used to acquire Chirp probe data of periodic shortwave communication links; The processing module 402 is used to calculate the stable signal strength data and time delay data of the detection frequency based on the Chirp detection data; The extraction module 403 is used to extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station. The calculation module 404 is used to generate signal-to-noise ratio data for the shortwave channel based on the stable signal strength data, the average noise strength data, and the monitoring occupancy data. The analysis module 405 is used to determine the frequency quality analysis results based on the time delay data, the signal-to-noise ratio data, and the monitoring occupancy data of each shortwave channel.

[0081] The frequency quality analysis device 400 provided in the above embodiments can realize the technical solutions described in the above frequency quality analysis method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above frequency quality analysis method embodiments, and will not be repeated here.

[0082] Please refer to Figure 5 , Figure 5This is a schematic diagram of an embodiment of the electronic device of this application. In this embodiment of the invention, the electronic device 500 includes a processor 501, a memory 502, and a display 503. Figure 5 Only some components of the electronic device 500 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0083] In some embodiments, processor 501 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 502 or process data, such as the frequency quality analysis method of the present invention.

[0084] In some embodiments, processor 501 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 501 may be local or remote. In some embodiments, processor 501 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, intranet, multi-cloud, etc., or any combination thereof.

[0085] In some embodiments, memory 502 may be an internal storage unit of electronic device 500, such as a hard disk or memory of electronic device 500. In other embodiments, memory 502 may also be an external storage device of electronic device 500, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 500.

[0086] Furthermore, the memory 502 may include both internal storage units of the electronic device 500 and external storage devices. The memory 502 is used to store application software and various types of data installed on the electronic device 500.

[0087] In some embodiments, display 503 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 503 is used to display information from electronic device 500 and to display visual user applications. Components 501-503 of electronic device 500 communicate with each other via a system bus.

[0088] In one embodiment, when processor 501 executes the frequency quality analysis program in memory 502, the following steps can be implemented: Acquire Chirp probe data for periodic shortwave communication links; Based on the Chirp detection data, calculate the stable signal strength data and time delay data of the detection frequency; Extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station; Based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, the signal-to-noise ratio data of the shortwave channel is generated; The frequency quality analysis results are determined based on the time delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel.

[0089] It should be understood that when the processor 501 executes the frequency quality analysis program in the memory 502, in addition to the functions mentioned above, it can also perform other functions, as can be found in the description of the corresponding method embodiments above.

[0090] Furthermore, the embodiments of the present invention do not specifically limit the type of electronic device 500 mentioned, and the electronic device 500 can be any type of auxiliary electronic device.

[0091] Accordingly, this application also provides a frequency quality analysis system, which includes an electronic device 500 and a computer-readable storage medium. The computer-readable storage medium is used to store computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the frequency quality analysis methods provided in the above-described method embodiments.

[0092] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0093] The frequency quality analysis method, apparatus, electronic device, and system provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A frequency quality analysis method, characterized in that, include: Acquire Chirp probe data for periodic shortwave communication links; Based on the Chirp detection data, calculate the stable signal strength data and time delay data of the detection frequency; Extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station; Based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, the signal-to-noise ratio data of the shortwave channel is generated; The frequency quality analysis results are determined based on the time delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel.

2. The frequency quality analysis method according to claim 1, characterized in that, The calculation of stationary signal strength data and time delay data at the detection frequency based on the Chirp detection data includes: The Chirp probe data is converted into binary data to generate the binary data required for frequency quality calculation. Based on the binary data, extract the signal strength data and time delay distribution data for each detection frequency; Construct a signal data matrix and a time delay data matrix in the time domain and frequency domain based on the signal strength data and the time delay distribution data; Based on the signal data matrix and the time delay data matrix, calculate the stable signal strength data and time delay data for each detection frequency.

3. The frequency quality analysis method according to claim 2, characterized in that, The calculation of stationary signal strength data and time delay data for each detection frequency based on the signal data matrix and the time delay data matrix includes: Calculate the time-domain weighting coefficients; The stationary data within the period of each detection frequency are calculated based on the time-domain weighting coefficients, the signal data matrix, and the time delay data matrix. The stable data within the period is smoothed to obtain stable signal strength data and time delay data.

4. The frequency quality analysis method according to claim 1, characterized in that, The extraction of average noise intensity data and channel monitoring occupancy data from the monitoring data of the target station includes: Acquire monitoring data from the target station; Based on the frequency range of the shortwave channel, the shortwave frequency in the monitoring data is offline into multiple channel frequencies; Average noise intensity data and channel occupancy monitoring data of the shortwave channel are extracted from each channel frequency.

5. The frequency quality analysis method according to claim 1, characterized in that, Based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data, signal-to-noise ratio (SNR) data for the shortwave channel is generated, including: Obtain the preset linear interpolation formula; The signal-to-noise ratio (SNR) of the shortwave channel is obtained by calculating the signal strength data, the average noise intensity data, and the monitoring occupancy data using the linear interpolation formula.

6. The frequency quality analysis method according to claim 1, characterized in that, The determination of frequency quality analysis results based on the delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel includes: Based on the delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel, delay quality analysis results, signal-to-noise ratio quality analysis results, and occupancy quality analysis results are generated according to frequency quality standards. The frequency quality analysis results are determined based on the delay quality analysis results, the signal-to-noise ratio quality analysis results, and the occupancy quality analysis results.

7. The frequency quality analysis method according to claim 6, characterized in that, The determination of frequency quality analysis results based on the delay quality analysis results, the signal-to-noise ratio quality analysis results, and the occupancy quality analysis results includes: Obtain the application scenario information of the target station; The quality weight allocation information is determined based on the application scenario information. The frequency quality analysis results are obtained by weighting the delay quality analysis results, the signal-to-noise ratio quality analysis results, and the occupancy quality analysis results based on the quality weight allocation information.

8. A frequency quality analysis device, characterized in that, include: The module includes an acquisition module, a processing module, an extraction module, a calculation module, and an analysis module. The acquisition module is used to acquire Chirp probe data of periodic shortwave communication links; The processing module is used to calculate the stable signal strength data and time delay data of the detection frequency based on the Chirp detection data; The extraction module is used to extract the average noise intensity data and monitoring occupancy data of the shortwave channel from the monitoring data of the target station; The calculation module is used to generate signal-to-noise ratio data for the shortwave channel based on the stable signal strength data, the average noise intensity data, and the monitoring occupancy data. The analysis module is used to determine the frequency quality analysis results based on the delay data, signal-to-noise ratio data, and monitoring occupancy data of each shortwave channel.

9. An electronic device, the electronic device comprising a processor and a memory, characterized in that, The memory is used to store instructions, and the processor is used to call the instructions in the memory to cause the electronic device to execute the frequency quality analysis method as described in any one of claims 1 to 7.

10. A frequency quality analysis system, characterized in that, The intelligent frequency quality analysis system includes an electronic device, a data acquisition device, and an output device as described in claim 9. The electronic device is connected to the data acquisition device and the output device, respectively. The data acquisition device is used to acquire Chirp probe data of periodic shortwave communication links, and the output device is used to generate and output frequency quality analysis results.

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