A method, system and storage medium for GEO satellite frequency orbital resource availability assessment

Abstract

The application discloses a GEO satellite frequency orbit resource availability evaluation method and system and a storage medium, relates to the technical field of space frequency orbit resource management, and aims at solving the problem that there is no comprehensive and effective GEO satellite frequency orbit resource availability evaluation method in the prior art. By comprehensively considering the satellite orbit, the declared frequency, the occupied bandwidth, the link direction, the polarization type, the coverage area and other influencing factors, the availability of the use scheme is evaluated and ranked, and a backup scheme is given in the case that the availability is low, so that the use efficiency of the GEO satellite frequency orbit resource can be greatly improved, and the current situation of the GEO satellite frequency orbit resource shortage can be effectively relieved. By using the effectiveness evaluation result of the GEO satellite frequency orbit resource, on the one hand, the frequency orbit resource use scheme can be quickly formed, and the labor cost and the time cost can be saved; on the other hand, the current use situation of the GEO satellite frequency orbit resource can be comprehensively reflected, and auxiliary decision support can be provided for satellite network data declaration and utilization.

Description

Technical Field

[0001] This invention relates to the field of space frequency orbit resource management technology, and more specifically, to a method, system, and storage medium for assessing the availability of GEO satellite frequency orbit resources. Background Technology

[0002] Satellite frequency and orbital slots, especially those for GEO satellites, are finite resources. GEO satellite orbital slots primarily refer to the 360° orbital plane at an altitude of 36,000 kilometers above the equator, where satellites are relatively stationary relative to the Earth. Given these limited slots, the more GEO satellites launched, the more strained the slots become, increasing the difficulty of slot application, coordination, and utilization. GEO satellite frequency resources mainly refer to the frequency bands used by various GEO satellite services, including UHF / VHF, L, S, C, X, Ku, Ka, and EHF bands. As the number of GEO satellites increases, frequency interference and coordination become increasingly difficult. Currently, there is no clear standard for assessing the availability of GEO satellite frequency and orbital resources. Assessments rely solely on manual database searches and subjective judgments based on existing data from on-orbit satellites and satellite networks. This leads to numerous review issues when submitting satellite network data and easily overlooks valuable resources, reducing resource utilization. Therefore, assessing the rationality of GEO satellite frequency and orbital resource utilization can better guide the effective use of GEO satellites. Summary of the Invention

[0003] The technical problem to be solved by this invention is:

[0004] There is a lack of comprehensive and effective methods for assessing the availability of GEO satellite frequency orbit resources in existing technologies.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0006] This invention provides a method for assessing the availability of GEO satellite frequency orbit resources, comprising the following steps:

[0007] Step 1: Evaluate task interaction

[0008] Determine the evaluation requirements indicators, including: initial track location, permissible arc range, frequency band type, permissible frequency band range, occupied bandwidth, link direction, polarization type, and coverage area;

[0009] Step 2: Assigning values ​​to evaluation indicators

[0010] Determine the evaluation indicators, assign values ​​to the evaluation indicators, and perform quantitative calculations on the evaluation indicators;

[0011] Step 3: Assigning weights to evaluation indicators

[0012] Step 4: Input the initial frequency track selection scheme

[0013] The initial frequency track selection scheme was evaluated based on the task interaction input;

[0014] Step 5: Frequency overlap detection

[0015] Compare the allowable frequency band range of the input initial selected frequency orbit with the satellite frequency bands in the basic database. If there is a frequency overlap area, proceed to the next step of orbital spacing calculation; if there is no frequency overlap area, determine whether "all satellites in the basic database have been traversed".

[0016] Step 6: Track Spacing Calculation

[0017] For different frequency bands, a high-risk interval vector with radii is designed; based on the initial orbit position of the input initial selected frequency orbit and the satellite orbit position read from the database, the orbit position interval between satellites is calculated. If the orbit position is within the high-risk interval, the coverage area overlap assessment is performed; if the orbit position is not within the high-risk interval, the judgment of "whether all satellites in the basic database have been traversed" is performed.

[0018] Step 7: Coverage Area Overlap Analysis

[0019] The coverage area of ​​the input initial frequency track is compared with the coverage area of ​​the satellites in the database. If the coverage areas overlap, an interference assessment is performed; if the coverage areas do not overlap, a judgment is made on whether all satellites in the basic database have been traversed.

[0020] Step 8: Evaluate data and output results.

[0021] Furthermore, in step 2, trapezoidal fuzzy numbers are used to quantify the evaluation indicators, specifically as follows:

[0022]

[0023] Among them, A i (x) represents the membership function, and α and b represent the parameters of the satisfaction membership function.

[0024] Furthermore, step 3 determines the weights of the evaluation indicators based on the second-order coefficient of variation, namely:

[0025]

[0026] Where v represents the coefficient of variation.

[0027] Furthermore, it also includes generating alternative schemes, which differ from the initially selected frequency track scheme in track position, while all other parameters remain unchanged; the generation of the alternative schemes is based on the following method:

[0028] a) Select a frequency track whose orbital parameters do not conflict with the initial frequency track selection scheme;

[0029] b) Choose the frequency track with the least difficulty in coordinating conflicting options.

[0030] This invention provides a GEO satellite frequency orbit resource availability assessment system. The system has program modules corresponding to the steps of any of the above-described technical solutions, and executes the steps in the above-described GEO satellite frequency orbit resource availability assessment method when running.

[0031] The present invention provides a computer-readable storage medium storing a computer program configured to, when invoked by a processor, implement the steps in the GEO satellite frequency orbit resource availability assessment method described in any of the above technical solutions.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] This invention provides a method, system, and storage medium for assessing the availability of GEO satellite frequency and orbit resources. Based on global GEO satellite network application data and global GEO satellite data in orbit, it comprehensively considers factors such as satellite orbit, applied frequency, occupied bandwidth, link direction, polarization type, and coverage area to evaluate and rank the availability of various GEO satellite frequency and orbit usage plans. In cases of low availability, it provides alternative plans, significantly improving the efficiency of GEO satellite frequency and orbit resource utilization and effectively alleviating the current shortage of GEO satellite frequency and orbit resources. Specifically, it manifests in:

[0034] I. The evaluation indicator system is more comprehensive, taking into account the data submitted by global on-orbit satellites and satellite networks, as well as the advantageous orbital resources held by traditional satellite operators. The indicator system is more complete and the evaluation results are more accurate.

[0035] Second, the evaluation indicators are calculated using a variety of methods, which can be adapted to the evaluation of different frequency track schemes;

[0036] Third, it can quickly formulate frequency track resource utilization plans, saving manpower and time costs;

[0037] Fourth, it can comprehensively reflect the current status of GEO satellite frequency and orbit resource utilization, providing auxiliary decision-making support for satellite network data application and utilization. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the evaluation task interaction content in an embodiment of the present invention;

[0039] Figure 2 This is a diagram illustrating the data screening and alternative scheme generation in an embodiment of the present invention.

[0040] Figure 3 This is a flowchart illustrating the evaluation process in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the evaluation index system in an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram illustrating the on-orbit satellite interference risk level in an embodiment of the present invention;

[0043] Figure 6 This is a schematic diagram illustrating the risks caused by resources already in use in an embodiment of the present invention;

[0044] Figure 7 This is a schematic diagram illustrating the risks arising from coordinated data in an embodiment of the present invention. Detailed Implementation

[0045] To enable those skilled in the art to better understand the present invention, exemplary embodiments or examples of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments or examples are merely some, not all, of the embodiments or examples of the present invention. All other embodiments or examples obtained by those skilled in the art based on the embodiments or examples of the present invention without inventive effort should fall within the scope of protection of the present invention.

[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0047] This invention provides a method for assessing the availability of GEO satellite frequency orbit resources, such as... Figure 3 As shown, it includes the following steps:

[0048] Step 1: Evaluate task interaction

[0049] like Figure 1 As shown, based on the evaluation party's requirements, relevant demand indicators are determined: frequency band type, occupied bandwidth, link direction, polarization type, and coverage area serve as input parameters for the initial frequency track selection scheme. Simultaneously, the arc segments required to cover the coverage area are calculated, i.e., the allowable arc segment range. Based on the allowable arc segment range and track position data in the basic database, available track positions are calculated, further selecting the initial track positions. The allowable frequency band range of this frequency track scheme is further determined based on link direction, occupied bandwidth, and frequency band type. Finally, based on link direction, occupied bandwidth, frequency band type, polarization, and in conjunction with the "Radio Regulations," the interference limits for this system are further determined.

[0050] Step 2: Assigning and customizing evaluation metrics

[0051] like Figure 4As shown, the evaluation indicators include: the actual number of satellites in the vicinity, the minimum spacing of actual satellites, the worst link interference of nearby satellites, the worst beam interference of nearby satellites, the worst link interference of satellites with the minimum spacing, the worst beam interference of satellites with the minimum spacing, the worst link interference of satellites, the worst beam interference of satellites, the number of occupied satellite networks in the vicinity, the minimum spacing of occupied satellite networks, the worst link interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the worst link interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the number of coordination data of nearby position-priority satellite networks, the minimum spacing of coordination data of position-priority satellite networks, the worst link interference of coordination data of nearby position-priority satellite networks, the worst beam interference of coordination data of nearby position-priority satellite networks, the worst link interference of priority coordination data of minimum spacing, the worst beam interference of priority coordination data of minimum spacing, the worst link interference of coordination data of position-priority satellite networks, and the worst beam interference of coordination data of position-priority satellite networks. Non-Boolean indicators are quantified using fuzzy vector calculations. Fuzzy vectors, through precise numerical methods, process fuzzy evaluation indicators, enabling a more scientific, reasonable, and realistic quantitative evaluation of these indicators. The evaluation result is a vector, not a single point value, containing richer information and accurately characterizing the evaluated object. Further processing yields reference information. The specific method is as follows:

[0052] Let N be the fuzzy satisfaction level, and let X1, X2, ..., X N X i = (i-1) / (N-1), where i = 1, 2, ..., N represent satisfaction levels from low to high, and X1 = 0 represents the lowest satisfaction level. N =1 indicates the highest satisfaction level. Domain experts provide fuzzy membership functions corresponding to each level of satisfaction based on the data variation range of individual indicators. For example, the satellite revisit cycle is a "the shorter the better" attribute indicator, which is quantified using trapezoidal fuzzy numbers. The membership function is shown in the following formula:

[0053]

[0054] Among them, A i (x) represents the membership function, and a and b represent the parameters of the satisfaction membership function, with specific values ​​provided by experts.

[0055] Similarly, for the "the bigger the better" type and the moderate index type, the same method is used to give the satisfaction level and its membership function.

[0056] For each indicator, after determining the satisfaction level and its membership function, the indicator data is substituted into the above formula to calculate the fuzzy vector of that indicator. The parameter values ​​of the membership function are provided by experts.

[0057] Taking the worst-case link interference of nearby satellites as an example, let the satisfaction level be N=5, namely (0, 0.25, 0.5, 0.75, 1), and the parameters of its satisfaction membership function are given by experts, namely a1=10, a2=21, a3=40, a4=80, b2=15, b3=36, b4=60, b5=100. The current worst-case link interference of nearby satellites is 25dB. Substituting into the formula, the fuzzy satisfaction membership degree of the revisit period is calculated, and its fuzzy vector is {0, 0.2, 0.8, 0, 0}, and its satisfaction is [10.75 0.5 0.25 0][0 0.2 0.8 0 0]=0.55.

[0058] Step 3: Customize and configure indicator weights

[0059] The Delphi subjective weighting method is used to subjectively assign parameter weights, while the coefficient of variation objective weighting method is used to objectively assign parameter weights. Furthermore, the indicator weights can be customized or learned values ​​can be selected based on the needs of the evaluator.

[0060] To eliminate the influence of different dimensions among the evaluation indicators, the coefficient of variation of each indicator is used to measure the degree of difference between the indicators. The objective weighting method based on the coefficient of variation has unique advantages, enabling the determination of weighting factors for multiple indicators with different dimensions.

[0061] The standard method for determining the coefficient of variation is as follows: the coefficient of variation for each indicator is determined by the following formula.

[0062]

[0063] In the formula,

[0064] v i — Represents the coefficient of variation of the i-th indicator.

[0065] σ i - represents the standard deviation of the i-th indicator.

[0066] — This represents the arithmetic mean of the i-th indicator.

[0067] Weights of each indicator w i Defined as:

[0068]

[0069] The steps for solving frequency track verification problems using the coefficient of variation objective weighting method are relatively simple. The most important part of the solution process is the calculation of the statistical data of the evaluation indicators. Specifically, the calculation of indicator weights using the coefficient of variation method consists of three steps:

[0070] 1) Extract indicator data from the input frequency track scheme and basic database, and perform statistical analysis on the evaluation indicators. Based on the information contained in each indicator, calculate the arithmetic mean and standard deviation of the indicator.

[0071] 2) According to the definition of the coefficient of variation, the coefficient of variation of each level of indicators can be directly calculated using the arithmetic mean and standard deviation. The process of solving the coefficient of variation is a dimensionless process. Therefore, the coefficient of variation of the evaluation indicators does not contain the dimensional factors of the original indicator data.

[0072] 3) Sum the coefficients of variation of the indicators within each level of the indicator layer, and calculate the proportion of the coefficients of variation of different indicators within their respective subsystems, thereby obtaining the proportion of each indicator within its corresponding evaluation system.

[0073] The above calculation process describes the determination of each index using the conventional coefficient of variation weighting method. However, the traditional coefficient of variation method has several problems. For example, its accuracy is limited by the range of the mean (especially when the mean is very small and approaches zero, the denominator of the formula approaches zero, making the formula inaccurate), and the method itself lacks a reasonable physical interpretation and meaning. Based on the above method, the second-order coefficient of variation method is used to solve the above problems, as detailed in the following formula:

[0074]

[0075] The above formula gives the second-order coefficient of variation for the j-th indicator. The second-order coefficient of variation takes into account the difference between the average of the squares of each indicator and the square of its average. The second-order coefficient of variation has lower requirements on the range of the mean value compared to the conventional weighted method for variation parameters, resulting in higher accuracy.

[0076] Based on this, the weights determined by the second-order coefficient of variation are expressed by the following formula:

[0077]

[0078] The second-order coefficient of variation method determines the weight of indicators by averaging the second-order coefficients of variation for each indicator, thus determining the weight of each indicator's second-order coefficient of variation relative to the total second-order coefficients of variation of all indicators.

[0079] Step 4: Input the initial frequency track selection scheme

[0080] The evaluator inputs the initial frequency track scheme through the evaluation task interaction. The input frequency track scheme parameters mainly include: initial track position, allowable arc range, frequency band type, allowable frequency band range, occupied bandwidth, link direction, polarization type, and coverage area.

[0081] Step 5: Frequency overlap detection

[0082] If the allowed frequency band range input by the evaluator is compared with the satellite frequency bands in the basic database, and there is a frequency overlap area, the next step of orbital spacing calculation is performed; if there is no frequency overlap area, a judgment is made on "whether all satellites in the basic database have been traversed".

[0083] Step 6: Track Spacing Calculation

[0084] For different frequency bands, high-risk radian spacing vectors are designed. For example, the tentative orbital spacing configuration is 2 degrees for Ka band, 3 degrees for Ku band, 2 degrees for X band, and 4 degrees for C band. This spacing will be further improved using spectrum compatibility data and optimization methods.

[0085] Based on the initial selected orbital positions input by the evaluator, the satellite orbital positions are read from the database, and the orbital position intervals between satellites are calculated. If the orbital position is within a high-risk interval, coverage overlap analysis is performed; if the orbital position is not within a high-risk interval, a judgment is made on whether all satellites in the basic database have been traversed.

[0086] Step 7: Coverage Area Overlap Analysis

[0087] The coverage areas in the initial frequency and orbit scheme selected by the evaluation method are compared with the coverage areas of satellites in the database. If the coverage areas overlap, interference analysis is performed; if the coverage areas do not overlap, a judgment is made on whether all satellites in the basic database have been traversed.

[0088] Step 8: Generation of alternative solutions

[0089] like Figure 2 As shown, in addition to the frequency and orbit scheme input by the evaluator, other orbital positions are selected as alternative schemes within the arc segment that meets the evaluator's requirements, according to a certain step position. During the selection of other orbital positions, the system provides a default step position and supports customization by the evaluator. The default step position is 0.2 degrees, corresponding to 1800 selectable orbital positions for a 360-degree geostationary orbital arc segment in the equatorial plane. The alternative schemes differ from the scheme input by the evaluator only in the orbital position; all other parameters remain unchanged. Two main types of recommended orbital positions are included:

[0090] a) Select a trajectory whose parameters do not conflict with ours at all;

[0091] b) Choose the path with the least difficulty in coordinating conflicting options.

[0092] Step 9: Evaluation Data and Result Output

[0093] like Figures 5 to 7 As shown, this invention records relevant weights and input values ​​during the evaluation process using an evaluation index system, and can display the relevant parameter values ​​in the form of a mind map. For all frequency track schemes recommended in the evaluation, the scoring details of the scheme can be viewed, risk tracing can be performed, and the specific index items and basic data that caused the evaluation value to be too low can be located, helping the evaluator to understand the current satellite or satellite network environment.

[0094] The evaluation data and results output by this invention can fulfill the requirement of the evaluator to have full visibility into the evaluation process and final results. It displays the satellite data and basic satellite network data currently participating in the evaluation in a list format; and the evaluation data can be exported as needed by the evaluator.

[0095] The GEO satellite frequency orbit resource availability assessment method (algorithm) proposed in this invention is the underlying technical core of this invention, and various products can be derived based on the algorithm.

[0096] Based on the method proposed in this invention, a GEO satellite frequency orbit resource availability assessment system is developed using a programming language. This system has program modules corresponding to the steps of the above-mentioned technical solution, and executes the steps in the above-mentioned GEO satellite frequency orbit resource availability assessment method when running.

[0097] The developed system (software) computer program is stored on a computer-readable storage medium, and the computer program is configured to implement the steps of the GEO satellite frequency orbit resource availability assessment method described above when called by a processor. In other words, the invention is materialized on a carrier, becoming a computer program product.

[0098] Various implementations of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, application-specific integrated circuits (ASICs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] The computational programs (also referred to as programs, software, software applications, or code) of this invention include machine instructions of a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device PLD) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0100] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for assessing the availability of GEO satellite frequency orbit resources, characterized in that, Includes the following steps: Step 1: Evaluate task interaction; Determine the evaluation requirements indicators, including: initial track location, permissible arc range, frequency band type, permissible frequency band range, occupied bandwidth, link direction, polarization type, and coverage area; Step 2: Assign values ​​to evaluation indicators; Determine the evaluation indicators, assign values ​​to the evaluation indicators, and perform quantitative calculations on the evaluation indicators; Step 3: Quantify the weights of the evaluation indicators by assigning them using fuzzy vectors; Step 4: Input the initial frequency track selection scheme; The initial frequency track selection scheme was evaluated based on the task interaction input; Step 5: Frequency overlap detection; Compare the allowed frequency band range of the input initial selected frequency orbit with the satellite frequency bands in the basic database. If there is a frequency overlap area, proceed to the next step of orbital spacing calculation; if there is no frequency overlap area, determine whether "all satellites in the basic database have been traversed". Step 6: Track spacing calculation; For different frequency bands, a high-risk interval vector with radii is designed; based on the initial orbit position of the input initial selected frequency orbit and the satellite orbit position read from the database, the orbit position interval between satellites is calculated. If the orbit position is within the high-risk interval, the coverage area overlap assessment is performed; if the orbit position is not within the high-risk interval, the judgment of "whether all satellites in the basic database have been traversed" is performed. Step 7: Coverage overlap analysis; The coverage area of ​​the input initial frequency track is compared with the coverage area of ​​the satellites in the database. If the coverage areas overlap, an interference assessment is performed; if the coverage areas do not overlap, a judgment is made on whether all satellites in the basic database have been traversed. Step 8: Evaluate data and output results; The evaluation metrics in Step 2 include: the actual number of satellites in the vicinity, the minimum spacing of actual satellites, the worst link interference of nearby satellites, the worst beam interference of nearby satellites, the worst link interference of satellites with the minimum spacing, the worst beam interference of satellites with the minimum spacing, the worst link interference of satellites, the worst beam interference of satellites, the number of occupied satellite networks in the vicinity, the minimum spacing of occupied satellite networks, the worst link interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the worst link interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the worst link interference of occupied satellite networks, the worst beam interference of occupied satellite networks, the number of coordination data of nearby position-priority satellite networks, the minimum spacing of coordination data of position-priority satellite networks, the worst link interference of coordination data of nearby position-priority satellite networks, the worst beam interference of coordination data of nearby position-priority satellite networks, the worst link interference of coordination data of priority coordination data of minimum spacing, the worst beam interference of priority coordination data of minimum spacing, the worst link interference of coordination data of position-priority satellite networks, and the worst beam interference of coordination data of position-priority satellite networks. Quantization is performed using fuzzy vector calculations; the evaluation result is a vector. Let the fuzzy satisfaction level be ,use , These represent satisfaction levels from low to high. This indicates the lowest level of satisfaction. The highest level of satisfaction is indicated by the data range of each individual indicator, which is then used by domain experts to provide fuzzy membership functions corresponding to each level of satisfaction. For the satellite revisit cycle, a shorter cycle is considered better; trapezoidal fuzzy numbers are used to quantify the evaluation indicators, and the membership function is shown in the following formula: Among them, A i (x) represents the membership function, and a and b represent the parameters of the satisfaction membership function; For each indicator, after determining the satisfaction level and its membership function, the indicator data is substituted into the above formula to calculate the fuzzy vector of the indicator. In step 3, the Delphi subjective weighting method is used to subjectively assign parameter weight values, and the coefficient of variation objective weighting method is used to objectively assign parameter weight values. In step 3, the weights of the evaluation indicators are determined based on the second-order coefficient of variation, i.e.: Among them, v j Let be the second-order coefficient of variation of the j-th index, expressed as: For the j-th indicator, Let be the arithmetic mean of the j-th indicator; The method further includes generating alternative schemes, which differ from the initially selected frequency track scheme in track position, while all other parameters remain unchanged; the generation of the alternative schemes is based on the following method: a) Select a frequency track whose track parameters do not conflict with the initially selected frequency track scheme; b) Choose the frequency track with the least difficulty in coordinating conflicting options.

2. A GEO satellite frequency orbit resource availability assessment system, characterized in that, The system has program modules corresponding to the steps of the method described in claim 1 above, and executes the steps in the GEO satellite frequency orbit resource availability assessment method described above when running.

3. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program configured to, when invoked by a processor, implement the steps in the GEO satellite frequency orbit resource availability assessment method of claim 1.

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