Research On Evaluation Technology Of Uncertain Multi-attribute Jamming Effect

In radar countermeasure,jamming effect is an important information that both radar and jammer pay close attention to.With the emergence of cognitive electronic warfare technology and the intelligent development of radar countermeasure equipment,the role of jamming effect evaluation in radar countermeasure becomes more and more important.In order to evaluate the interference effect reasonably and effectively,many evaluation criteria,evaluation indexes and evaluation methods is put forward by researchers.In the interference evaluation,the multiple evaluation indexes is used in the evaluation often,so it is necessary to integrate multiple index information for evaluation processing.In the actual situation,there is uncertainty in the evaluation of interference effect.For example,some interference indexes are fuzzy,which need to be described by fuzzy language according to expert evaluation.Some evaluation indexes have incomplete information and some parameters are missing.Therefore,jamming effect evaluation can also be regarded as an uncertain multiattribute problem.In this thesis,the problem of uncertain multi-attribute interference effect evaluation is studied,and the theory of uncertain multi-attribute decision-making is combined with interference effect evaluation to explore a feasible and effective interference effect evaluation method.The main research work of this thesis is as follows:Firstly,the theory of radar jamming effect evaluation is studied,and the classification of radar jamming effect evaluation is introduced combined with the application scenarios of jamming effect evaluation.The jamming effect evaluation technology is analyzed in detail from three aspects of jamming effect evaluation criteria,evaluation indexes and evaluation methods.The common evaluation criteria is discussed in the thesis,the common evaluation indexes of jamming effect is studied in detail,and the uncertainty in the evaluation indexes of jamming effect is analyzed,the uncertainty in the evaluation indexes of jamming effect is studied from two aspects of linguistic variables and incomplete information.The common jamming effect evaluation methods and their advantages and disadvantages are analyzed.The evaluation of interference effect based on multi-attribute decision-making is studied in the thesis,focuses on TOPSIS,the calculation method of attribute weight based on entropy weight method is discussed,and the evaluation model of interference effect based on multiattribute decision-making is established,The feasibility of applying multi-attribute decisionmaking to jamming effect evaluation and the effectiveness of TOPSIS in multi-attribute decision-making to jamming effect evaluation are verified.The problem of jamming effect evaluation with fuzzy information as evaluation index is studied,the jamming effect evaluation based on fuzzy multi-attribute decision-making is studied.The jamming effect evaluation index data qualitatively described by fuzzy semantic variables is transformed into intuitionistic trapezoidal fuzzy number,and the relative entropy is introduced as the distance measure of Topsis to improve the traditional Topsis,and the jamming effect evaluation model based on fuzzy multi-attribute decision-making is established.The evaluation results calculated by relative entropy distance and traditional distance are compared with simulation examples.The fuzzy multi-attribute decision-making method based on relative entropy is proved that it is feasible and effective in this kind of interference effect evaluation.Finally,the evaluation method of jamming effect under incomplete information is given,and the method of intuitionistic fuzzy set to measure missing information is studied.The weight of evaluation index under incomplete information is calculated by intuitionistic fuzzy entropy.Combined with multi-attribute decision-making based on evidential reasoning,the evaluation method of jamming effect under incomplete information is proposed,and the method is verified by simulation with a example.