CN116050053A - Interference effect evaluation method for communication satellite - Google Patents
Interference effect evaluation method for communication satellite Download PDFInfo
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Abstract
The invention discloses a method for evaluating interference effect on a communication satellite, which comprises the following steps: step S1: establishing a multi-level index system meeting the evaluation requirement; step S2: and establishing an evaluation model for evaluating the interference effectiveness. Step S3: a satellite communication interference assessment algorithm is performed. The invention has the advantages of simple principle, easy operation, good evaluation effect, wide application range and the like.
Description
Technical Field
The invention mainly relates to the technical field of electronic countermeasure of communication satellites, in particular to a method for evaluating interference effects on communication satellites.
Background
With the rapid development and wide application of digital information system technology, the status of information communication in civil field and military task is more and more prominent, and mastering the information right plays a vital role in national life and competition.
The electronic countermeasure for satellite communication is a main field of interest in the satellite field, and a typical electronic countermeasure system for satellite communication comprises three systems of satellite signal reconnaissance, interference and command decision. The anti-command decision system determines the adjustment of the interference strategy, and adjusts the interference method according to the detected communication signal and the interference effect so as to achieve the optimal interference effect. Therefore, the research of satellite communication interference effect evaluation technology is developed to have important application value.
The interference effect evaluation refers to a process of qualitatively or quantitatively evaluating damage or destruction generated by an interfered device after electronic interference is implemented.
At present, the evaluation of the interference effect of the communication satellite in the conventional technology is classified into a suppression interference model evaluation and a deception interference model evaluation according to the type of the implemented interference signal. The interference suppression mode mainly suppresses communication signals in the modes of single-tone interference, multi-tone interference, single-tone frequency sweep interference, multi-tone frequency sweep interference and the like, the deception interference mode mainly forwards interference signals, and the aim of disturbing communication of the other party is achieved by forwarding signals of the other party to a satellite.
The research of the interference effect evaluation method in the electronic anti-interference field is mainly focused on radar electronic anti-interference effect evaluation, and the research of the communication anti-interference effect evaluation scheme is less and simpler.
The existing communication anti-interference effect evaluation criteria are mainly based on the error rate and the call clearing probability. The error rate and the probability of being cleared are two indexes which can reflect the communication quality most directly, but for a communication non-partner, the two indexes are difficult to obtain an accurate estimation. In addition, the anti-interference modes of satellite communication are various, such as spread spectrum anti-interference technology, self-adaptive zeroing antenna anti-interference technology, frequency hopping/variable frequency anti-interference technology and the like, and the application of the anti-interference technology ensures the smooth proceeding of the communication process. For the interfering party, the interference effect is only estimated by the error rate of the communication of the non-cooperative party and the estimated value of the call clearing probability, so that objective and effective estimation is difficult to achieve.
Obviously, the above existing evaluation method cannot adapt to complex and variable interference and anti-interference modes. Therefore, the search and research of the communication satellite interference effect evaluation method is urgent.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems existing in the prior art, the invention provides the interference effect evaluation method for the communication satellite, which has the advantages of simple principle, easy operation, good evaluation effect and wide application range.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method for evaluating interference effect on communication satellite includes the steps:
step S1: establishing a multi-level index system meeting the evaluation requirement;
step S2: and establishing an evaluation model for evaluating the interference effectiveness.
Step S3: a satellite communication interference assessment algorithm is performed.
As a further improvement of the process of the invention: in the step S2, an evaluation model is built by using a hierarchical analysis method, and elements included in the problem are divided into three layers:
the highest layer is the target layer, namely the evaluation result of the interference effectiveness;
the middle layer is a criterion layer, which takes different types of index sets as evaluation middle results of a class of criteria;
the lowest layer is the index layer, and the indexes are directly related to the interference effect to a certain extent.
As a further improvement of the process of the invention: the highest layer has only 1 element, which is the intended target or ideal result of the problem to be analyzed.
As a further improvement of the process of the invention: the intermediate layer comprises intermediate links involved for achieving the aim and consists of a plurality of layers.
As a further improvement of the process of the invention: the intermediate layer comprises one or more of qualitative indexes, interference detection results, spectrum characteristics and demodulation results.
As a further improvement of the process of the invention: the bottom layer contains various indexes, measures and schemes which can be selected to achieve the aim.
As a further improvement of the process of the invention: the bottom layer comprises one or more of interference signal type, whether a communication object changes frequency, whether a symbol rate is reduced, interference signal power, interference signal bandwidth, interference signal number, interference signal ratio, interference sweep speed, interference sweep bandwidth, constellation diagram clustering index, eye pattern characteristic index, error rate and frame error rate.
As a further improvement of the process of the invention: the step S3 includes:
step S301: sorting importance among indexes;
after establishing a hierarchical structure model for efficiency evaluation, subjectively ordering the mutual importance relations of each index to the index of the upper layer, namely L vectors;
step S302: establishing a judgment matrix;
automatically obtaining a judgment matrix M according to the L vector obtained in the step S301, wherein the judgment matrix M is obtained by comparing the importance degrees of the indexes to the elements of the upper layer in pairs, and is marked as M_ (n multiplied by n) = [ m_ij ], wherein n is the number of the selected indexes; the element m_ij in the matrix M is called a scale and is obtained by comparing the ith index and the jth index, and is divided into 9 levels which are respectively represented by 1-9 and the inverse thereof, wherein 1 index i has the same importance as index j, and 9 represents that the index i is extremely important than the index j;
step S303: generating a weight vector;
performing eigenvalue decomposition on the judgment matrix M to obtain an eigenvector V matrix and an eigenvalue D matrix:
[V,D]＝eig(M)
obtaining the maximum characteristic value: λ_max=d (1, 1);
calculating normalized feature vectors: w_i=v_i/sum (v_i (: 1));
then obtaining a weight vector from the matrix, and finally carrying out merging by using a weighted sum method to obtain the final weight of the total target, so that a final evaluation result can be obtained;
step S304: and (5) comprehensively scoring and evaluating.
As a further improvement of the process of the invention: in the step S304, according to the different relationships between the indexes and the criterion layer elements, the indexes are classified into the following 3 classes:
(1) Benefit index: i.e. "larger the better" the data;
the normalization formula is as follows:
x i ＝0,when X i ≤min{X i }
x i ＝1,when X i ≥max{X i }
(2) Cost index: i.e. "smaller the better" the data;
the normalization formula is as follows:
x i ＝1,when X i ≤min{X i }
x i ＝0,when X i ≥max{X i }
(3) The interval index: i.e. the index data falls within the range X i ∈[σ,ε]Preferably;
the normalization formula is as follows:
x i ＝1,whenσ≤X i ≤ε。
as a further improvement of the process of the invention: further comprising step S5: and adjusting the satellite communication interference model.
Compared with the prior art, the invention has the advantages that:
the interference effect evaluation method for the communication satellite is simple in principle, easy to operate, good in evaluation effect and wide in application range, combines the working principle and the functional characteristics of satellite communication, builds an index system for evaluating the interference efficiency of satellite communication by applying a fuzzy mathematical theory, and builds a second-level fuzzy evaluation model. The invention adopts a uniform distribution form to construct the membership function, and utilizes an Analytic Hierarchy Process (AHP) of an index scale to determine the weight of each factor, so that the consistency index of a judgment matrix is improved, and the interference quantification evaluation of the communication satellite is realized. According to the invention, a plurality of interference signals are selected as examples for fuzzy comprehensive judgment, and the example analysis results show that the communication satellite interference effectiveness fuzzy judgment model has practicability, and the evaluation results can provide references for the selection of interference measures.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of a satellite communication interference assessment model in a specific application example of the present invention.
Fig. 3 is a flowchart of a satellite communication interference assessment algorithm in a specific application example of the present invention.
Fig. 4 is a control adjustment plan view of the satellite communication interference assessment model in a specific application example of the present invention.
Fig. 5 is a spectrum diagram of an undisturbed satellite communication signal in a specific application example of the present invention.
Fig. 6 is a schematic diagram of interference score curves of interference-free satellite communication signals in a specific application example of the invention.
Fig. 7 is a spectrum diagram of a single tone interfering satellite communication signal in a specific application example of the present invention.
Fig. 8 is a schematic diagram of a signal interference score curve of a single tone interfering satellite communication in a specific application example of the present invention.
Fig. 9 is a spectrum diagram of a multi-tone interfering satellite communication signal in a specific application example of the present invention.
Fig. 10 is a schematic diagram of a multi-tone interference satellite communication signal interference score curve in a specific application example of the present invention.
Fig. 11 is a spectrum diagram of a single-tone swept-frequency interfering satellite communication signal in an example of an application of the invention.
Fig. 12 is a schematic diagram of a single-tone swept-frequency interfering satellite communication signal interference score curve in an embodiment of the invention.
Fig. 13 is a spectrum diagram of a multi-tone swept-frequency interfering satellite communication signal in an example of an application of the invention.
Fig. 14 is a schematic diagram of a multi-tone swept-frequency interfering satellite communication signal interference score curve in a specific application example of the invention.
Fig. 15 is a spectrum diagram of a retransmission interference satellite communication signal in a specific application example of the present invention.
Fig. 16 is a graph of the signal-to-interference score of a retransmission interference satellite communication signal in a specific application example of the present invention.
Detailed Description
The invention will be described in further detail with reference to the drawings and the specific examples.
Based on the principle, the interference effect evaluation method for the communication satellite comprises the following steps:
step S1: establishing a multi-level index system meeting the evaluation requirement;
in the process of interference effectiveness evaluation, firstly, a multi-level index system meeting the evaluation requirement is established, index data of target objects participating in evaluation are collected, and the index data are quantized by applying various quantization models; and then, further combining the weights given to the indexes of each level by an expert system, performing coupling operation on the quantized results and the weight data by using a model matrix according to different evaluation modes to obtain target evaluation scores of each level and total evaluation results of each target, and performing performance evaluation on the target objects according to the target evaluation scores.
Step S2: and establishing an evaluation model for evaluating the interference effectiveness.
Step S3: a satellite communication interference assessment algorithm is performed.
In a specific application example, in step S2 of the present invention, an evaluation model is built by using a hierarchical analysis method, and the present invention divides elements included in a problem into 3 layers:
(1) The highest layer (target layer), which has only 1 element, is the intended target or ideal result of the problem to be analyzed.
(2) The middle layer (criterion layer), which includes the intermediate links involved to achieve the goal, may consist of several layers.
(3) A bottom layer (index layer) containing various indexes, measures, schemes, and the like, which are selectable to achieve the objective.
Wherein the highest layer is a target layer, namely an evaluation result of interference effectiveness; the middle layer is a criterion layer, and takes different types of index sets as evaluation middle results of a class of criteria; the lowest layer is the index layer, and the indexes are directly related to the interference effect to a certain extent.
FIG. 2 shows a model of a satellite communication interference estimation method in a specific application example, wherein the highest layer is the satellite communication interference estimation result; the middle layer comprises one or more of qualitative indexes, interference detection results, map features and demodulation results; the bottom layer comprises one or more of interference signal type, whether a communication object changes frequency, whether a symbol rate is reduced, interference signal power, interference signal bandwidth, number of interference signals, interference signal ratio, interference sweep speed, interference sweep bandwidth, constellation diagram clustering index, eye pattern characteristic index, bit error rate and frame error rate.
Further, in a specific application example, the indexes selected by the above-mentioned index layer respectively represent different meanings:
In a specific application example, referring to fig. 3, step S3 of the present invention includes:
step S301: sorting importance among indexes;
after the hierarchical structure model of efficiency evaluation is established, subjective ordering is carried out on the mutual importance relations among the indexes of the upper layer, namely L vectors, through experts.
Step S302: establishing a judgment matrix;
the judgment matrix M is automatically obtained according to the L vector obtained in step S301, and is obtained by comparing the importance degrees of the indexes to the elements of the previous layer, and is denoted as m_ (n×n) = [ m_ij ], wherein n is the number of the selected indexes. The element m_ij in the matrix M is called a scale and is obtained by comparing the ith index with the jth index, and is divided into 9 levels, which are respectively represented by 1-9 and the inverse thereof, wherein 1 index i has the same importance as index j, and 9 represents that the index i is extremely important than the index j.
For example: if the 4 th index is slightly more important than the 1 st index, the elements m_41 and m_14 in the matrix M are 3 and 1/3, respectively. In this way, the judgment matrix can be obtained by comparing the importance of each index in the index layer and filling the scale value in the corresponding position of the matrix M.
Step S303: generating a weight vector;
performing eigenvalue decomposition on the judgment matrix M to obtain an eigenvector V matrix and an eigenvalue D matrix:
[V,D]＝eig(M)
obtaining the maximum characteristic value: λ_max=d (1, 1);
calculating normalized feature vectors: w_i=v_i/sum (v_i (: 1));
and obtaining a weight vector from the matrix, and finally, carrying out merging by using a weighted sum method to obtain the final weight of the total target, so that the final evaluation result can be obtained.
Step S304: comprehensively scoring and evaluating;
in actual evaluation, the magnitude and dimension of each evaluation index are different, and the attributes are also different, so that the smaller and better the index requirements (cost type index) are, the larger and better the index requirements (benefit type index) are, and the stability of certain determined ideal values (fixed index) is required for the indexes.
In order to eliminate the incoordination among the indexes, the trend requirements of the indexes are unified, and the evaluation indexes are subjected to normalization processing before evaluation. The data of these indices are normalized to serve as the basis for subsequent evaluation calculations.
Further, in the specific application example, in step S304, X is i For normalizing the pre-sampleElements in the set, maximum value is max { X i Minimum value is min { X } i }，x i Is the corresponding data after normalization. According to different relationships of each index to the criterion layer elements, the indexes can be classified into the following 3 classes:
1. benefit index: i.e. "the larger the data the better".
The normalization formula is as follows:
x i ＝0,when X i ≤min{X i }
x i ＝1,when X i ≥max{X i }
2. cost index: i.e. "smaller the better" the data.
The normalization formula is as follows:
x i ＝1,when X i ≤min{X i }
x i ＝0,when X i ≥max{X i }
3. the interval index: i.e. the index data falls within the range X i ∈[σ,ε]Preferably, the method comprises the steps of.
The normalization formula is as follows:
x i ＝1,whenσ≤X i ≤ε
if the performance of a certain communication interference system is evaluated independently, selecting a judgment grade corresponding to the maximum value in the judgment vector as a system performance evaluation result according to the maximum membership principle; when comparing the performance of more than two communication interference systems, a weighted average method can be adopted to digitize the evaluation results and then sort the evaluation results. Which is a kind of
The final scoring result may be expressed as:
wherein v is a score result, x is an index data normalization vector, and w is a weight vector.
As a preferred embodiment, the present invention further includes step S5: and adjusting the satellite communication interference model. The mutual importance degree (influence judgment matrix) among indexes, the membership function (influence scoring result) of the indexes, and the influence of the indexes on the interference effect is not necessarily linear due to the membership function correction, so the membership function correction is added.
y＝smf(x,[ab])
S-type membership function
Wherein [ a b ] is a data range.
y＝linmf(x,[ab])
Linear membership function
Number of digits
Wherein [ a b ] is a data range.
y＝expmf(x,[abc])
Index membership function
Wherein c is the bottom, [ a b ] is the data range.
y＝logmf(x,[abc])
Logarithmic membership function
Wherein c is the bottom, [ a b ] is the data range.
The invention will be described with respect to a specific application as an example. And establishing a multi-level index system meeting the evaluation requirement according to the satellite communication interference evaluation model. A control adjustment plan for the satellite communication interference assessment model is shown in fig. 4.
The value of the weight in the graph can be adjusted (the weight range is 0-9); the function type (the function type is S-type membership function, linear membership function, exponential membership function and logarithmic membership function) can be selected; the maximum value and the minimum value of the interference parameters can be adjusted according to different interference detection situations.
When the satellite communication interference evaluation model is determined, the magnitude of the current interference effect can be evaluated by inputting various parameters of the current measured satellite signals into the model.
The satellite communication interference evaluation method takes single-tone interference, multi-tone interference, single-tone frequency sweep interference, multi-tone frequency sweep interference and forwarding interference as examples, and verifies the interference evaluation effect of the satellite communication interference evaluation method.
As shown in fig. 5 and fig. 6, the signal spectrum diagram of the satellite communication signal under the normal communication condition without interference and the interference score curve obtained after the interference evaluation model are respectively shown.
As shown in fig. 7 and fig. 8, the signal spectrum diagram of the satellite communication signal under the condition of single-tone interference normal communication and the interference score value curve obtained after the interference evaluation model are respectively shown.
As shown in fig. 9 and fig. 10, the signal spectrum diagram of the satellite communication signal under the condition of multi-tone interference normal communication and the interference score value curve obtained after the interference evaluation model are respectively shown.
As shown in fig. 11 and 12, the signal spectrum diagram of the satellite communication signal under the condition of single-tone frequency sweep interference normal communication and the interference score value curve obtained after the interference evaluation model are respectively shown.
As shown in fig. 13 and fig. 14, the signal spectrogram of the satellite communication signal under the condition of multi-tone frequency sweep interference normal communication and the interference score value curve obtained after the interference evaluation model are respectively shown.
As shown in fig. 15 and fig. 16, the signal spectrum diagram of the satellite communication signal under the condition of forwarding interference normal communication and the interference score value curve obtained after the interference evaluation model are respectively shown.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.
Claims (10)
1. The interference effect evaluation method for the communication satellite is characterized by comprising the following steps:
step S1: establishing a multi-level index system meeting the evaluation requirement;
step S2: establishing an evaluation model for evaluating the interference effectiveness;
step S3: a satellite communication interference assessment algorithm is performed.
2. The method for evaluating the interference effect on a communication satellite according to claim 1, wherein in the step S2, an evaluation model is built by using a hierarchical analysis method, and elements included in the problem are divided into three layers:
the highest layer is the target layer, namely the evaluation result of the interference effectiveness;
the middle layer is a criterion layer, which takes different types of index sets as evaluation middle results of a class of criteria;
the lowest layer is the index layer, and the indexes are directly related to the interference effect to a certain extent.
3. The method of claim 2, wherein the highest layer has only 1 element, which is a predetermined target or ideal result of a problem to be analyzed.
4. The method for evaluating the interference effect on a communication satellite according to claim 2, wherein the intermediate layer comprises an intermediate link involved in achieving the objective and is composed of a plurality of layers.
5. The method of claim 4, wherein the intermediate layer comprises one or more of a qualitative indicator, an interference detection result, a profile feature, and a demodulation result.
6. The method of claim 2, wherein the bottom layer contains various metrics, measures and schemes that are selectable to achieve the goal.
7. The method of claim 6, wherein the bottom layer includes one or more of an interference signal type, whether a communication object is frequency-shifted, whether a symbol rate is reduced, an interference signal power, an interference signal bandwidth, a number of interference signals, an interference signal ratio, an interference sweep speed, an interference sweep bandwidth, a constellation clustering index, an eye pattern feature index, an error rate, and a frame error rate.
8. The method for evaluating the interference effect on a communication satellite according to any one of claims 1 to 7, wherein the step S3 includes:
step S301: sorting importance among indexes;
after establishing a hierarchical structure model for efficiency evaluation, subjectively ordering the mutual importance relations of each index to the index of the upper layer, namely L vectors;
step S302: establishing a judgment matrix;
automatically obtaining a judgment matrix M according to the L vector obtained in the step S301, wherein the judgment matrix M is obtained by comparing the importance degrees of the indexes to the elements of the upper layer in pairs, and is marked as M_ (n multiplied by n) = [ m_ij ], wherein n is the number of the selected indexes; the element m_ij in the matrix M is called a scale and is obtained by comparing the ith index and the jth index, and is divided into 9 levels which are respectively represented by 1-9 and the inverse thereof, wherein 1 index i has the same importance as index j, and 9 represents that the index i is extremely important than the index j;
step S303: generating a weight vector;
performing eigenvalue decomposition on the judgment matrix M to obtain an eigenvector V matrix and an eigenvalue D matrix:
[V,D]＝eig(M)
obtaining the maximum characteristic value: λ_max=d (1, 1);
calculating normalized feature vectors: w_i=v_i/sum (v_i (: 1));
then obtaining a weight vector from the matrix, and finally carrying out merging by using a weighted sum method to obtain the final weight of the total target, so that a final evaluation result can be obtained;
step S304: and (5) comprehensively scoring and evaluating.
9. The method for evaluating the interference effect on a communication satellite according to claim 8, wherein in the step S304, the indexes are classified into the following 3 types according to different relationships of the indexes to the criterion layer elements:
(1) Benefit index: i.e. "larger the better" the data;
the normalization formula is as follows:
x i ＝0,when X i ≤min{X i }
x i ＝1,when X i ≥max{X i }
(2) Cost index: i.e. "smaller the better" the data;
the normalization formula is as follows:
x i ＝1,when X i ≤min{X i }
x i ＝0,when X i ≥max{X i }
(3) The interval index: i.e. the index data falls within the range X i ∈[σ,ε]Preferably;
the normalization formula is as follows:
x i ＝1,whenσ≤X i ≤ε。
10. the interference effect evaluation method for a communication satellite according to any one of claims 1 to 7, further comprising step S5: and adjusting the satellite communication interference model.
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| CN116886174A (en) * | 2023-08-21 | 2023-10-13 | 中国人民解放军战略支援部队航天工程大学 | Anti-interference efficiency evaluation method for satellite communication system |
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| CN116886174B (en) * | 2023-08-21 | 2024-02-09 | 中国人民解放军战略支援部队航天工程大学 | Anti-interference efficiency evaluation method for satellite communication system |
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