Abstract
The effectiveness evaluation of the Electronic Information (ELINT) system, which plays an important role in guiding the theoretical research, equipment development, and practical application, is the key technology of the ELINT system. In practical applications, the effectiveness evaluation of ELINT system is mainly aimed at evaluation methods. However, the establishment of evaluation criteria and the construction of the index system are still two main challenges in this field, especially the optimization of the evaluation index system. In this paper, we aim at establishing the ELINT system index evaluation criteria and optimizing the ELINT system evaluation index system. Based on the principle structure of the ELINT system, we directly construct the original efficiency index system, establish specific evaluation criteria for each index, and quantify the indexes using the criteria. To optimize the proposed index system, we introduce the idea of rough set reduction and develop an index system reduction model based on the mutual information heuristic knowledge reduction (MIBARK) algorithm. Simulation analysis shows that the proposed evaluation criteria quantify each index scientifically, and the established indicator reduction model can eliminate the redundancy of the ELINT efficiency indicator system, making the indicator system more streamlined and reasonable.
Highlights
IntroductionWith the increasing complexity of modern electronic warfare, the role of electronic intelligence has become more and more obvious. e Electronic Information (ELINT) system is an important combat equipment for acquiring electronic intelligence on the battlefield, and the evaluation of its overall combat effectiveness is one of the important issues currently faced [1].ELINT system effectiveness evaluation is a process of multi-index comprehensive evaluation, which mainly involves the construction of the index system, the establishment of evaluation criteria, and the selection of evaluation algorithms [2,3,4,5,6]. e current algorithm research for multiindex system evaluation is relatively extensive, from basic ADC method [7], analytic hierarchy process [8], SEA method [9], and grey relational analysis method [10] to widely used neural network algorithm [11, 12], which has a relatively mature theoretical system
Electronic Information (ELINT) system effectiveness evaluation is a process of multi-index comprehensive evaluation, which mainly involves the construction of the index system, the establishment of evaluation criteria, and the selection of evaluation algorithms [2,3,4,5,6]. e current algorithm research for multiindex system evaluation is relatively extensive, from basic ADC method [7], analytic hierarchy process [8], SEA method [9], and grey relational analysis method [10] to widely used neural network algorithm [11, 12], which has a relatively mature theoretical system
A decision system with zero conditional entropy H (D/C) is a consistent decision system. e larger the average mutual information of the condition attribute set in the consistent decision-making system, the greater the amount of information provided by the condition attribute set to the decision attribute set, and the more obvious the role it plays in decision-making
Summary
With the increasing complexity of modern electronic warfare, the role of electronic intelligence has become more and more obvious. e ELINT system is an important combat equipment for acquiring electronic intelligence on the battlefield, and the evaluation of its overall combat effectiveness is one of the important issues currently faced [1].ELINT system effectiveness evaluation is a process of multi-index comprehensive evaluation, which mainly involves the construction of the index system, the establishment of evaluation criteria, and the selection of evaluation algorithms [2,3,4,5,6]. e current algorithm research for multiindex system evaluation is relatively extensive, from basic ADC method [7], analytic hierarchy process [8], SEA method [9], and grey relational analysis method [10] to widely used neural network algorithm [11, 12], which has a relatively mature theoretical system. E ELINT system is an important combat equipment for acquiring electronic intelligence on the battlefield, and the evaluation of its overall combat effectiveness is one of the important issues currently faced [1]. ELINT system effectiveness evaluation is a process of multi-index comprehensive evaluation, which mainly involves the construction of the index system, the establishment of evaluation criteria, and the selection of evaluation algorithms [2,3,4,5,6]. E electronic equipment efficiency index system, which is constructed in the traditional method, lacks objectivity and comprehensiveness [15, 16]. It is only constructed based on expert experience, without the reasonable analysis of complexity and redundancy of the index system. In terms of algorithm optimization, [17,18,19] proposed an optimal solution based on the ant colony optimization (MSICEAO) algorithm and an improved quantum evolutionary algorithm; these algorithms can find the optimal solution but the computational complexity is relatively high
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