GSO frequency and orbit resource efficiency evaluation method based on demand constraints

Abstract

The present invention discloses a demand-constrained GSO frequency and orbit resource performance evaluation method, comprising: determining soft and hard evaluation modes; calculating commissioning time A1, satellite platform control consistency A2, operating frequency consistency A3, service area consistency A4, radiation envelope consistency A5, service type consistency A6; and demodulation threshold protection requirement consistency A7. For the hard evaluation mode, when A1 to A7 are all 1, the final performance evaluation value is 1, otherwise it is 0. For the soft evaluation mode, A1 to A7 are used as primary indicators, and a decision matrix for the primary indicators is given. Weights are calculated for each primary indicator to obtain a weight vector #imgabs0# for each primary indicator. The fuzzy satisfaction value of each primary indicator is calculated. The ambiguity vector is calculated for the obtained values to generate an evaluation matrix R. The matrix #imgabs1# selects the maximum value in the matrix C as the final performance evaluation value. The present invention can effectively evaluate the demand consistency of spatial frequency and orbit resources.

Description

Technical Field

[0001] The present invention relates to the technical field of space frequency orbit resources, and in particular to a GSO frequency orbit resource efficiency evaluation method based on demand constraints. Background Art

[0002] Satellite technology is developing rapidly in today's society. Countries attach great importance to space services and are competing fiercely for satellite frequency and orbital resources, resulting in a large number of frequency and orbit data applications. However, blindly pursuing resources without matching them with actual usage needs will have serious consequences in the future. Therefore, proposing a reasonable performance evaluation method from the perspective of demand constraints is an important part of seizing frequency and orbital resources.

[0003] Currently, the experts who declare resources are different from the actual users, and the time limit from declaration to the start of use of resources is long. There may be a mismatch between the used devices and the declared data, and the performance evaluation method for demand constraints is relatively weak. Summary of the Invention

[0004] The purpose of the present invention is to provide a GSO frequency-orbit resource efficiency evaluation method based on demand constraints, effectively evaluate the demand consistency of space frequency-orbit resources, and quantitatively calculate indicators at all levels under demand consistency.

[0005] The technical solution to achieve the purpose of the present invention is: a GSO frequency and orbit resource efficiency evaluation method based on demand constraints, comprising the following steps:

[0006] Step 1: Determine the evaluation mode, which is divided into soft evaluation mode and hard evaluation mode;

[0007] Step 2: Calculate the estimated value A1 of the time to be put into use;

[0008] Step 3: Calculate the evaluation value A2 of the satellite platform control consistency;

[0009] Step 4: Calculate the evaluation value A3 of the operating frequency consistency;

[0010] Step 5: Calculate the evaluation value A4 of the consistency of the service area;

[0011] Step 6: Calculate the evaluation value A5 of the radiation envelope consistency;

[0012] Step 7: Calculate the evaluation value A6 of the consistency of the service type;

[0013] Step 8: Calculate the demodulation threshold protection requirement consistency assessment value A7;

[0014] Step 9: For the hard evaluation mode, when A1 to A7 are all 1, the final performance evaluation value is 1, otherwise the final performance evaluation value is 0; for the soft evaluation mode, the final performance evaluation value is determined through steps 10 to 14;

[0015] Step 10: Take A1, A2, A3, A4, A5, A6, and A7 as first-level indicators, and give a decision matrix for the first-level indicators;

[0016] Step 11: Based on the decision matrix of the first-level indicators, calculate the weights respectively to obtain the weight vector of the first-level indicators

[0017] Step 12: Calculate the fuzzy satisfaction of each first-level indicator;

[0018] Step 13: Calculate the fuzzy vectors for the values obtained in steps 2 to 8 respectively, and generate an evaluation matrix R;

[0019] Step 14: Weight vector based on the first-level indicator Let the matrix The maximum value in matrix C is selected as the final performance evaluation value.

[0020] Compared with the existing technology, the present invention has the following significant advantages: (1) It analyzes the actual use requirements of the satellite system in detail and formulates a reasonable evaluation method from the perspective of meeting the use requirements; (2) It couples the satellite system and data, can effectively evaluate the demand consistency of space frequency orbit resources, and quantitatively calculates the indicators at all levels under the demand consistency, which has strong engineering feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of the GSO frequency and orbit resource efficiency evaluation method based on demand constraints of the present invention.

[0022] Figure 2 It is a schematic diagram of the indicator function in the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Combine Figure 1 The present invention provides a method for evaluating the efficiency of GSO frequency and orbit resources based on demand constraints, and the specific steps are as follows:

[0025] Step 1: Determine the evaluation mode, which is divided into soft evaluation mode and hard evaluation mode;

[0026] Step 2: Calculate the estimated value A1 of the time to be put into use;

[0027] Step 3: Calculate the evaluation value A2 of the satellite platform control consistency;

[0028] Step 4: Calculate the evaluation value A3 of the operating frequency consistency;

[0029] Step 5: Calculate the evaluation value A4 of the consistency of the service area;

[0030] Step 6: Calculate the evaluation value A5 of the radiation envelope consistency;

[0031] Step 7: Calculate the evaluation value A6 of the consistency of the service type;

[0032] Step 8: Calculate the demodulation threshold protection requirement consistency assessment value A7;

[0033] Step 9: For the hard evaluation mode, when A1 to A7 are all 1, the final performance evaluation value is 1, otherwise the final performance evaluation value is 0; for the soft evaluation mode, the final performance evaluation value is determined through steps 10 to 14;

[0034] Step 10: Take A1, A2, A3, A4, A5, A6, and A7 as first-level indicators, and give a decision matrix for the first-level indicators;

[0035] Step 11: Based on the decision matrix of the first-level indicators, calculate the weights respectively to obtain the weight vector of the first-level indicators

[0036] Step 12: Calculate the fuzzy satisfaction of each first-level indicator;

[0037] Step 13: Calculate the fuzzy vectors for the values obtained in steps 2 to 8 respectively, and generate an evaluation matrix R;

[0038] Step 14: Weight vector based on the first-level indicator Let the matrix The maximum value in matrix C is selected as the final performance evaluation value.

[0039] Furthermore, in step 1, the calculation methods for each indicator of the present invention include two modes: soft evaluation mode and hard evaluation mode. Only one of the soft evaluation mode and hard evaluation mode can be selected for each evaluation. Hard evaluation means that when all sub-indicators fully meet the threshold conditions, the satisfaction is 1, otherwise it is 0. Soft evaluation is more flexible, and the satisfaction is obtained through calculation methods. The specific calculation methods of the two modes are shown in steps 2 to 7.

[0040] Furthermore, the evaluation value A1 of the time to be put into use is calculated in step 2 as follows:

[0041] First, determine whether the information is N information. Substitute the ntc_id into the notice table to find the ntf_rsn value corresponding to the ntc_id. ntc_id represents the unique identifier of the notice. Notice is a general information table for notifications. There are three situations:

[0042] 1) When it is N, it means that N data has been enabled;

[0043] 2) If the value is C, substitute ntc_id into the com_el table, record the adm field and sat_name field of com_el and substitute the BIU URL, and search for the status value with the same adm and sat_name. If the status is C, it means that the N data has been enabled.

[0044] 3) If it is C, substitute ntc_id into the com_el table, record the adm field and sat_name field of com_el and substitute the BIU URL, and search for the status value with the same adm and sat_name. If status is N, it means that the N data is not enabled;

[0045] When N data is enabled, set A1 to 1; otherwise, further confirm the satellite network data reporting time; substitute ntc_id into the grp table, search for and record the corresponding d_st_cur value, recorded as time_1; substitute ntc_id into the com_el table, record the adm field and sat_name values of com_el, and substitute them into the BIU website address to search for the value of the Dateofbringingintouse field with the same adm and sat_name, recorded as time_2; calculate the time difference t between time_2 and time_1 in days; when hard decision mode is selected, if the time difference is greater than 1, set A1 to 1, otherwise it is 0; when soft decision mode is selected, set A1 = 1 - (2555 - t) / 2555.

[0046] Furthermore, the evaluation value A2 of the satellite platform control consistency is calculated in step 3 as follows:

[0047] Query the corresponding tol_east and tol_west values in the geo table according to ntc_id, and compare them with the threshold values tol_east_con and tol_west_con; when hard decision is selected, if tol_east ≤ tol_east_con and tol_west ≥ tol_west_con, then A2 = 1, otherwise A2 = 0; when soft decision is selected, let A2 = (tol_east_con - tol_east) + (tol_west_con - tol_west).

[0048] Furthermore, the evaluation value A3 of the operating frequency consistency is calculated in step 4 as follows:

[0049] Substitute ntc_id into the s_beam table and query all freq_min and freq_max groups under that ntc_id. Create a frequency band requirement table, as shown in Table 1. Take each frequency group in the frequency band requirement table and compare it with freq_min and freq_max. When hard decision is used, if freq_min ≤ freq_l and freq_max ≥ freq_m for each frequency group, set A3 = 1; otherwise, A3 = 0. When soft decision is used, set A3 = overlapping frequency band / required frequency band, where the required frequency band is the sum of all frequency bands in the frequency band requirement table.

[0050] Table 1 Frequency band requirements

[0051] id freq_l freq_m

[0052] Furthermore, the evaluation value A4 of the service area consistency is calculated in step 5 as follows:

[0053] Substitute the ntc_id into the grp table and use the area_no field to obtain the coverage area. Record the longitude and latitude sequence for each service area. Each longitude and latitude sequence represents a closed area. The user then marks the target coverage area on the map and calculates the overlap ratio between the two areas. When hard decision is selected, if the overlapping area equals the target area, set A4 = 1; otherwise, A4 = 0. When soft decision is selected, set A4 = overlapping area / target area.

[0054] Furthermore, the evaluation value A5 of the radiation envelope consistency is calculated in step 6 as follows:

[0055] Substitute ntc_id into the s_beam table, record all beams, i.e. beam_name and corresponding emi_rcp, and then make the following judgments for all beams in turn:

[0056] Substitute the ntc_id, emi_rcp, and beam_name into the grp table, find all corresponding grp_ids, and substitute each grp_id into the s_as_stn table. If a corresponding record is found, the beam is an intersatellite link; otherwise, it is a satellite-to-ground link. If it is a satellite-to-ground link, if the emi_rcp value for the beam is R, the beam is an uplink; if the emi_rcp value is E, the beam is a downlink. The user enters the threshold value psd_con for determining the consistency of the radiation envelope.

[0057] (1) Calculate the intersatellite radiation envelope consistency, using A 51For each intersatellite link beam, the following operations are performed:

[0058] 1.1) In the s_beam table, record the gain corresponding to beam_name;

[0059] 1.2) Substitute all grp_ids under the beam into the eject table and find the corresponding maximum pwr_ds_max;

[0060] 1.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd ≥ psd_con, A 51 =1, otherwise A 51 =0; when soft decision is selected, A 51 =1-psd_con / psd;

[0061] (2) Calculate the uplink radiation envelope consistency, using A 52 For each uplink beam, the following operations are performed:

[0062] 2.1) Substitute all grp_ids under the beam into the e_as_stn table, find the gain value under the grp_id, and record the grp_id with the largest gain value;

[0063] 2.2) In the eject table, find the pwr_ds_max value corresponding to the grp_id recorded in the previous step;

[0064] 2.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd ≥ psd_con, A 52 =1, otherwise A 52 =0; when soft decision is selected, A 52 =1-psd_con / psd;

[0065] (3) Calculate the downlink radiation envelope consistency, using A 53 For each downlink beam, the following operations are performed:

[0066] 3.1) Record the gain corresponding to beam_name;

[0067] 3.2) Substitute all grp_ids under the beam into the eject table and find the corresponding maximum pwr_ds_max;

[0068] 3.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd>=psd_con, A53 =1, otherwise A 53 =0; when soft decision is selected, A 53 =1-psd_con / psd;

[0069] When any type of beam does not exist, let A5 be 1; otherwise, let A5 = (A 51 +A 52 +A 53 ) / 3.

[0070] Furthermore, the evaluation value A6 of the service type consistency is calculated in step 7 as follows:

[0071] (1) Calculate the consistency of space station service types, using A 61 Indicates. Establish a space station business demand table, as shown in Table 2. Substitute the ntc_id value of the notice table into the grp table, record all grp_ids, and substitute the grp_ids into the srv_cls table in sequence to check the corresponding stn_cls. Let a represent the number of space station types in the data to be evaluated and the types in the space station business demand table, and b represent the number of space station types in the space station business demand table; when hard decision is selected, if a / b<1, A 61 =0, otherwise A 61 =1; when hard decision is selected, A 61 =a / b.

[0072] Table 2 Space Station Business Requirements

[0073] id Space station type

[0074] (2) Calculate the consistency of earth station service type, using A 62 Establish an earth station service requirement table, as shown in Table 3. Substitute the ntc_id value of the notice table into the grp table, record all grp_ids, and substitute the grp_ids into the e_srvcls table in sequence to check the corresponding stn_cls. Let p represent the number of earth station types in the data to be evaluated and the types in the earth station service requirement table, and q represent the number of earth station types in the earth station service requirement table. When hard decision is selected, if p / q < 1, A 62 =0, otherwise A 62 =1; when hard decision is selected, A 62 =p / q.

[0075] Table 3 Earth station service requirements

[0076] id Earth station type

[0077] Let A6 = (A 61 +A 62) / 2.

[0078] Furthermore, the calculation of the demodulation threshold protection requirement consistency evaluation value A7 in step 8 is as follows:

[0079] As shown in Table 4, a demodulation threshold table is established. Substitute ntc_id into the grp table, record all grp_ids, substitute the grp_id into the mod_char table, and look up the corresponding sequence number seq_emiss and modulation type i_mod_typ. Substitute the grp_id and seq_emiss into the emiss table, look up the corresponding threshold value c_to_n, substitute the set of i_mod_typ and c_to_n into the demodulation threshold table, look up the threshold value for the modulation type, compare the threshold value with c_to_n, and count the number of grp_ids that meet the threshold value. When hard decision is selected, if any of the threshold values are not met, set A7 = 0; otherwise, set A7 = 1. When soft decision is selected, set A7 = number of threshold values met / total.

[0080] Table 4 Demodulation Threshold Table

[0081] id Modulation type Threshold

[0082] Furthermore, for the hard evaluation calculation in step 9, when A i When (i=1,2,..,7) are all 1, the evaluation value is 1, otherwise the evaluation value is 0; for soft evaluation calculation, the calculation method is shown in steps 10 to 14.

[0083] Furthermore, in step 10, A1, A2, A3, A4, A5, A6, and A7 are used as first-level indicators, and the decision matrix of the first-level indicators is given. The form of the decision matrix is as follows:

[0084] <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[A4]]> <![CDATA[A5]]> <![CDATA[A6]]> <![CDATA[A7]]> <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[A4]]> <![CDATA[A5]]> <![CDATA[A6]]> <![CDATA[A7]]>

[0085] Furthermore, in step 11, based on the decision matrix of the first-level indicators, the weights are calculated respectively to obtain the weight vector of the first-level indicators.

[0086] First, the value b of each column of the decision matrix ij Normalized to ω ij , i, j are the row and column numbers of the matrix, n is the total number of rows; ij Sum by row to get ω i , and then ω i Normalized to get Get the weight vector of the indicator

[0087] The decision matrix of the first-level indicators is as follows:

[0088]

[0089] Furthermore, the fuzzy satisfaction of each first-level indicator is calculated as described in step 12, as follows:

[0090] For each first-level indicator, the boundary value of the indicator is given, the fuzzy satisfaction of the indicator is calculated and the evaluation matrix is generated. Five levels are set, namely A, B, C, D and E, and the boundary value of each level is given by experts, namely Figure 2 a1,b2,a2,b3,a3,b4,a4,b5 in.

[0091] Furthermore, in step 13, the ambiguity vectors are calculated for the values obtained in steps 2 to 8 respectively to generate the evaluation matrix R. The calculation steps are as follows:

[0092] For all first-level indicators A p , p=1,2,3,4,5,6,7, substitute into formula (1), formula (2) and formula (3) in turn, and get a matrix r with one row and five columns p =[r pi ,i=1,2,3,4,5], let the evaluation matrix be R=[r p ,p=1,2,3,4,5,6,7] T :

[0093]

[0094]

[0095]

[0096] Furthermore, the weight vector based on the first-level index in step 14 is Let the matrix The maximum value in matrix C is selected as the final performance evaluation value.

[0097] The soft decision method is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0098] Example

[0099] For example, the network ID of the frequency orbit resource to be evaluated is 90500037. Its satellite network name is PALAPA-B1. The performance evaluation value calculation for the C band is used as an example, as shown below.

[0100] Step 1: Select the indicator calculation mode. In this embodiment, both modes are used for calculation.

[0101] Step 2: Calculate the time to use. After searching, the network has N data, so A1 is 1 for both soft and hard evaluations.

[0102] Step 3: Calculate the satellite platform control consistency A2. The user enters to_east_con = 0.04 and tol_west_con = 0.05. After searching, the network's tol_east and tol_west values are both 0.05. In hard evaluation mode, A2 = 0; in soft evaluation mode, A2 = (0.05 - 0.04) + (0.05 - 0.05) = 0.01.

[0103] Step 4: Calculate the operating frequency consistency A3. Substitute the ntc_id into the s_beam table. The query shows that there are two beams under this ntc_id, with frequency ranges of 3700-4200 MHz and 5925-6425 MHz, respectively. Create a frequency band requirement table, as shown in Table 1.1, and determine the overlap between the satellite network to be evaluated and the required frequency band. Calculations show that in hard evaluation mode, A3 = 1, and in soft evaluation mode, A3 = 0.3.

[0104] Table 1.1 Frequency band requirements

[0105] id freq_l freq_m 1 2500 3500 2 4000 4600 3 6000 6400

[0106] Step 5: Calculate the service area consistency A4. Substitute ntc_id into the grp table and retrieve the covered service area based on the area_no field. The satellite network data contains 34 transponder groups, all belonging to a single service area. The longitude and latitude sequence of this service area is recorded. The user calibrates the target coverage area as China. Calculations show that in hard evaluation mode, A4 = 0, and in soft evaluation mode, A4 = 0.73.

[0107] Step 6: Calculate the radiation envelope consistency A5. Make the following judgments on the beams of the satellite network data:

[0108] Substitute the grp_id of the 34 transponder groups into the s_as_stn table in turn to determine if there is a corresponding record. After searching, the satellite network data does not have an intersatellite link, so it is only necessary to determine the consistency of the uplink and downlink radiation envelopes. Let the intersatellite radiation envelope consistency A 51 =1, user input threshold value psd_con = -10.1.

[0109] (1) The satellite network data has a total uplink beam. Calculate the uplink beam evaluation value A 52 :

[0110] 1) Substitute all grp_ids under the beam into the e_as_stn table and find the gain value of 50.5 under the grp_id. The grp_ids with the largest gain values are 81600004, 103606522, and 103606523.

[0111] 2) In the eject table, find the pwr_ds_max corresponding to the grp_id recorded in the previous step. The values are -57.5, -65.5, and -65.5 respectively.

[0112] 3) Let psd = gain + pwr_ds_max, take the maximum value as -7.5, and compare it with psd_con. When hard decision is selected, A 52 =1, when soft decision is selected, A 52 =1.

[0113] (2) The satellite network data has a total downlink beam. Calculate the downlink beam evaluation value A 53 :

[0114] 1) Record the gain corresponding to beam_name as 27.5;

[0115] 2) Substitute all grp_ids under the beam into the emiss table and find the corresponding maximum pwr_ds_max, which is -29;

[0116] 3) Let psd = gain + pwr_ds_max, then psd is -1.5, and is compared with psd_con. When hard decision is selected, A 53 =1, when soft decision is selected, A 53 =1.

[0117] Step 7: Calculate the business type consistency A6.

[0118] (1) Calculate the space station service type A 61 . Establish a space station service demand table, as shown in Table 1.2. Substitute all grp_ids into the srv_cls table in sequence and check the corresponding stn_cls. After searching, the satellite network data has three types of space services, namely EC, ER, and ED. Therefore, the network data to be evaluated and the demand table have one duplicate type. When hard decision is selected, A 61 =0, when soft decision is selected, A 61 =0.25.

[0119] Table 1.2 Space Station Business Requirements

[0120] id Space station type 1 EJ 2 EC 3 EM 4 ET

[0121] (2) Calculate the consistency of earth station service type A 62 . Create an earth station service demand table, as shown in Table 1.3. Substitute all grp_ids into the e_srvcls table in turn, and find that there are three types of earth stations, namely TC, TR, and TD. Therefore, the network data to be evaluated and the earth station demand table have one duplicate type. When hard decision is selected, A 62 =0, when soft decision is selected, A 62 =0.25.

[0122] Table 1.3 Earth station service requirements

[0123] id Earth station type 1 UO 2 TC 3 TM 4 UT

[0124] Step 8. Calculate the demodulation threshold protection requirement consistency A7. As shown in Table 1.4, establish a demodulation threshold table. Substitute ntc_id into the grp table, record all grp_ids, substitute the grp_id into the mod_char table, and look up the corresponding sequence number seq_emiss and modulation type i_mod_typ. Substitute the grp_id and seq_emiss into the emiss table to find the corresponding threshold value c_to_n. Substitute the set of i_mod_typ and c_to_n into the demodulation threshold table, look up the threshold value for the modulation type, and compare the threshold value with c_to_n. Statistics show that the total number of cases is 62, and the number of cases that meet the threshold is 45. When hard decision is selected, A7 = 0; when soft decision is selected, A7 = 0.726.

[0125] Table 1.4 Demodulation Threshold Table

[0126] id Modulation type rate Threshold 1 PSK 0.36 0.8 2 QPSK 0.36 0.3 3 QPSK 0.43 1.1 4 QPSK 0.51 2.4 5 QPSK 0.60 3.6 6 APSK 0.64 0.9 7 BPSK 0.64 1.1 8 8PSK 0.47 4.7 9 8PSK 0.54 6.0 10 8PSK 0.62 7.2 11 8PSK 0.70 8.7 12 8PSK 0.79 10.2 13 16PSK 0.64 0.5 14 2APSK 0.70 0.5 15 4APSK 0.40 0.7 16 8APSK 0.34 0.8 17 16APSK 2.64 11.3 18 16APSK 2.92 12.5 19 16APSK 3.20 14.0 20 16APSK 3.52 15.7 21 32APSK 0.76 17.2

[0127] Step 9: For hard evaluation calculation, when A i When (i=1,2,..,7) are all 1, the evaluation value is 1, otherwise the evaluation value is 0; for soft evaluation calculation, the calculation method is as shown in steps 10 to 14.

[0128] Step 10: Classify the indicators to be evaluated, give the first-level indicators and the decision matrix of each second-level indicator, and record them in the database;

[0129] The decision matrix of the first-level indicator:

[0130] <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[A4]]> <![CDATA[A5]]> <![CDATA[A6]]> <![CDATA[A7]]> <![CDATA[A1]]> 1 1 / 2 1 / 3 1 / 2 1 / 3 1 / 2 1 <![CDATA[A2]]> 2 1 2 / 3 1 2 / 3 1 2 <![CDATA[A3]]> 3 3 / 2 1 3 / 2 1 3 / 2 3 <![CDATA[A4]]> 2 1 2 / 3 1 2 / 3 1 2 <![CDATA[A5]]> 3 3 / 2 1 3 / 2 1 2 / 3 3 <![CDATA[A6]]> 2 1 2 / 3 1 2 / 3 1 2 <![CDATA[A7]]> 1 1 / 2 1 / 3 1 / 2 1 / 3 1 / 2 1

[0131] Step 11: Calculate the weights of the decision matrix of the first-level indicators. Normalize the decision matrix by column, then sum it by row, and normalize the sum of each row again to obtain the weight vector of the first-level indicator. As follows: The decision matrix of the first-level indicator:

[0132]

[0133] Step 12: For each first-level indicator, give the boundary value of the indicator, calculate the fuzzy satisfaction of the indicator and generate an evaluation matrix. Set 5 levels, namely A, B, C, D and E, and let the experts give the boundary value of each level, namely Figure 2 The specific values are as follows: the boundary values of A1 are [0.05, 0.1, 0.3, 0.4, 0.6, 0.8, 0.9, 1], the boundary values of A2 are [0.01, 0.1, 0.3, 0.4, 0.6, 0.8, 0.9, 1], the boundary values of A3 are [0, 0.1, 0.2, 0.3, 0.4, 0.6, 0.8, 1], and the boundary values of A4 are [0, 0. The boundary values of A5 are [0, 0.2, 0.4, 0.5, 0.7, 0.8, 0.9, 1], the boundary values of A6 are [0, 0.1, 0.2, 0.4, 0.6, 0.8, 0.9, 1], and the boundary values of A7 are [0, 0.2, 0.3, 0.4, 0.6, 0.7, 0.8, 1].

[0134] Step 13: Calculate the ambiguity vectors for the values obtained in steps 1 to 6 respectively to generate an evaluation matrix. The calculation steps are as follows:

[0135] For A1, A2, A3, A4, A5, A6 and A7, let i be 1, 2, 3, 4, 5 respectively, and substitute them into formula (1), formula (2) and formula (3) in turn. After calculation, the results are as follows: r1 = [0, 0, 0, 0, 0], r2 = [1, 0, 0, 0, 0], r3 = [0, 0, 1, 0, 0], r4 = [0, 0, 0, 1, 0], r5 = [0, 0, 0, 0, 0], r6 = [0, 0.75, 0.25, 0, 0], r7 = [0, 0, 0, 1, 0];

[0136] Let the evaluation matrix B = [r1, r2, r3, r4, r5, r6, r7].

[0137] Step 14: Let the matrix After calculation, the matrix C = [0.143, 0.107, 0.25, 0.214, 0]. The maximum value in the matrix C is selected as the performance evaluation value, so the final performance evaluation value of the matrix is 0.25.

[0138] The present invention analyzes in detail the actual usage requirements of the satellite system and develops a reasonable evaluation method from the perspective of meeting usage requirements. By coupling the satellite system and data, it can effectively evaluate the consistency of space-frequency orbital resource requirements and quantitatively calculate indicators at all levels under the consistency of requirements, which has strong engineering feasibility.

Claims

1. A GSO frequency and orbit resource efficiency evaluation method based on demand constraints, characterized by: The following steps are involved: Step 1: Determine the evaluation mode, which is divided into soft evaluation mode and hard evaluation mode; Step 2: Calculate the estimated value A1 of the time to be put into use; Step 3: Calculate the evaluation value A2 of the satellite platform control consistency; Step 4: Calculate the evaluation value A3 of the operating frequency consistency; Step 5: Calculate the evaluation value A4 of the consistency of the service area; Step 6: Calculate the evaluation value A5 of the radiation envelope consistency; Step 7: Calculate the evaluation value A6 of the consistency of the service type; Step 8: Calculate the demodulation threshold protection requirement consistency assessment value A7; Step 9: For the hard evaluation mode, when A1 to A7 are all 1, the final performance evaluation value is 1, otherwise the final performance evaluation value is 0; for the soft evaluation mode, the final performance evaluation value is determined through steps 10 to 14; Step 10: Take A1, A2, A3, A4, A5, A6, and A7 as first-level indicators, and give a decision matrix for the first-level indicators; Step 11: Based on the decision matrix of the first-level indicators, calculate the weights respectively to obtain the weight vector of the first-level indicators Step 12: Calculate the fuzzy satisfaction of each first-level indicator; Step 13: Calculate the fuzzy vectors for the values obtained in steps 2 to 8 respectively, and generate an evaluation matrix R; Step 14: Weight vector based on the first-level indicator Let the matrix Select the maximum value in matrix C as the final performance evaluation value; In step 1, each evaluation can only select one of the soft evaluation mode and the hard evaluation mode. The hard evaluation means that the final performance evaluation value is 1 when all sub-indicators fully meet the threshold conditions, otherwise it is 0. The final performance evaluation value is obtained by calculation method; The evaluation value A1 of the time to be put into use is calculated in step 2 as follows: First, determine whether the data is N data. Substitute the ntc_id into the notice table to find the ntf_rsn value corresponding to the ntc_id. ntc_id represents the unique identifier of the notice. Notice is a general data table for notifications. There are three situations: 1) When it is N data, it means that N data has been enabled; 2) If it is C profile, substitute ntc_id into com_el table, record the adm field and sat_name field of com_el and substitute the BIU URL, and search for the status value with the same adm and sat_name. If status is C profile, it means N profile has been enabled. 3) If it is C profile, substitute ntc_id into com_el table, record the adm field and sat_name field of com_el and substitute the BIU URL, and search for the status value with the same adm and sat_name. If the status is N profile, it means that N profile is not enabled; When N data is enabled, set A1 to 1; otherwise, further confirm the satellite network data reporting time; substitute ntc_id into the grp table, find and record the corresponding d_st_cur value, and record it as time_1; substitute ntc_id into the com_el table, record the adm field and sat_name values of com_el, and substitute them into the BIU website, find the value of the Date of bringing into use field under the same adm and sat_name, and record it as time_2; calculate the time difference t between time_2 and time_1 in days; when hard decision mode is selected, if the time difference is greater than 1, set A1 to 1, otherwise it is 0; when soft decision mode is selected, set A1 = 1-(2555-t) / 2555; The calculation of the satellite platform control consistency evaluation value A2 in step 3 is as follows: Query the corresponding tol_east and tol_west values in the geo table based on ntc_id, and compare them with the thresholds tol_east_con and tol_west_con. When hard decision is selected, if tol_east ≤ tol_east_con and tol_west ≥ tol_west_con, then A2 = 1; otherwise, A2 = 0. When soft decision is selected, set A2 = (tol_east_con - tol_east) + (tol_west_con - tol_west). The evaluation value A3 of the operating frequency consistency is calculated in step 4 as follows: Substitute ntc_id into the s_beam table and query all freq_min and freq_max groups under that ntc_id. Create a frequency band requirement table and compare each frequency group in the frequency band requirement table with freq_min and freq_max. When hard decision is selected, if freq_min ≤ freq_l and freq_max ≥ freq_m for each frequency group, set A3 = 1; otherwise, set A3 = 0. When soft decision is selected, set A3 = overlapping frequency band / required frequency band, where the required frequency band is the sum of all frequency bands in the frequency band requirement table. The evaluation value A4 of the service area consistency is calculated in step 5 as follows: Substitute ntc_id into the grp table, obtain the coverage area based on the area_no field, and record the longitude and latitude sequence of each service area. Each longitude and latitude sequence is a closed area. The user then marks the target coverage area on the map and calculates the overlap ratio of the two areas. When hard decision is selected, if the overlapping area is equal to the target area, set A4 = 1, otherwise A4 = 0. When soft decision is selected, set A4 = overlapping area / target area. The evaluation value A5 of the radiation envelope consistency is calculated as described in step 6 as follows: Substitute ntc_id into the s_beam table, record all beams, i.e. beam_name and corresponding emi_rcp, and then make the following judgments for all beams in turn: Substitute ntc_id, emi_rcp, and beam_name into the grp table, find all corresponding grp_ids, and substitute each grp_id into the s_as_stn table. If a corresponding record is found, the beam is an intersatellite link; otherwise, it is a satellite-to-ground link. If it is a satellite-to-ground link, if the emi_rcp of the beam is R, the beam is an uplink; if the emi_rcp is E, the beam is a downlink. The user inputs the threshold value psd_con, which is used to judge the consistency of the radiation envelope; (1) Calculate the intersatellite radiation envelope consistency, using A 51 For each intersatellite link beam, the following operations are performed: 1.1) In the s_beam table, record the gain corresponding to beam_name; 1.2) Substitute all grp_ids under the beam into the eject table and find the corresponding maximum pwr_ds_max; 1.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd ≥ psd_con, A 51 =1, otherwise A 51 =0; when soft decision is selected, A 51 =1-psd_con / psd; (2) Calculate the uplink radiation envelope consistency, using A 52 For each uplink beam, the following operations are performed: 2.1) Substitute all grp_ids under the beam into the e_as_stn table, find the gain value under the grp_id, and record the grp_id with the largest gain value; 2.2) In the eject table, find the pwr_ds_max value corresponding to the grp_id recorded in the previous step; 2.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd ≥ psd_con, A 52 =1, otherwise A 52 =0; when soft decision is selected, A 52 =1-psd_con / psd; (3) Calculate the downlink radiation envelope consistency, using A 53 For each downlink beam, the following operations are performed: 3.1) Record the gain corresponding to beam_name; 3.2) Substitute all grp_ids under the beam into the eject table and find the corresponding maximum pwr_ds_max; 3.3) Let psd = gain + pwr_ds_max, and compare with psd_con; when hard decision is selected, if psd>=psd_con, A 53 =1, otherwise A 53 =0; when soft decision is selected, A 53 =1-psd_con / psd; When any type of beam does not exist, let A5 be 1; otherwise, let A5 = (A 51 +A 52 +A 53 ) / 3; The evaluation value A6 of the service type consistency is calculated in step 7 as follows: (1) Calculate the consistency of space station service types, using A 61 Indicates; establish a space station business demand table, substitute the ntc_id value of the notice table into the grp table, record all grp_ids, substitute the grp_ids into the srv_cls table in turn, check the corresponding stn_cls, let a represent the number of space station types in the space station business demand table that are repeated in the data to be evaluated, and b represents the number of space station types in the space station business demand table; when hard decision is selected, if a / b<1, A 61 =0, otherwise A 61 =1; when hard decision is selected, A 61 =a / b; (2) Calculate the consistency of earth station service type, using A 62 =Representation; establish an earth station service demand table, substitute the ntc_id value of the notice table into the grp table, record all grp_ids, substitute the grp_ids into the e_srvcls table in sequence, check the corresponding stn_cls, let p represent the number of earth station types in the data to be evaluated and the types in the earth station service demand table, q represents the number of earth station types in the earth station service demand table; when hard decision is selected, if p / q<1, A 62 =0, otherwise A 62 =1; when hard decision is selected, A 62 =p / q; Order A6=(A 61 +A 62 ) / 2; The calculation of the demodulation threshold protection requirement consistency assessment value A7 in step 8 is as follows: Establish a demodulation threshold table; substitute ntc_id into the grp table, record all grp_ids, substitute grp_id into the mod_char table, check the corresponding sequence number seq_emiss and modulation type i_mod_typ; substitute grp_id and seq_emiss into the emiss table, check the corresponding threshold value c_to_n, substitute a set of i_mod_typ and c_to_n into the demodulation threshold table, find the threshold value of the modulation type, compare the threshold value with c_to_n, and count the number of all grp_ids that meet the threshold value; when hard decision is selected, if there is a situation where the threshold value is not met, then A7 = 0, otherwise A7 = 1; when soft decision is selected, let A7 = number of threshold values met / total number.

2. The method for evaluating GSO frequency and orbit resource efficiency based on demand constraints according to claim 1, characterized in that: The specific process of steps 11 to 13 is as follows: First, the value b of each column of the decision matrix ij Normalized to ω ij , i, j are the row and column numbers of the matrix, n is the total number of rows; ij Sum by row to get ω i , and then ω i Normalized to get Get the weight vector of the indicator Set 5 levels, namely A, B, C, D and E, and let experts give the boundary values of each level, which are represented by a1, b2, a2, b3, a3, b4, a4, b5 in order; For all first-level indicators A p , p=1,2,3,4,5,6,7, substitute into formula (1), formula (2) and formula (3) in turn, and get a matrix r with one row and five columns p =[r pi ,i=1,2,3,4,5], let the evaluation matrix be R=[r p ,p=1,2,3,4,5,6,7] T :

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