## 3 The Objective Electromagnetic Environmental Effects Assessment
### Entropy Theory  
Entropy is a measurement of how chaotic a system is. The messier a system, the greater its entropy. Conversely, the cleaner a system, the lower the entropy. Hence, we can use entropy theory in the electromagnetic environment's complexity evaluation. The greater the entropy, the more complex the electromagnetic environment, which means that the target object suffers from serious interference from the electromagnetic environment. This method does not need the electromagnetic environment threshold definition in the four-domain models. Some studies [35] show that the entropy theory can also be applied to the assessment-level divisions of the electromagnetic environment. Therefore, it can solve the subjectivity problem in the assessment. Figure 4 illustrates the application of electromagnetic environmental effect research based on entropy theory. In the exploration research of entropy theory, [PERSON] et al. [36] proposed an analysis method for building a complex space for the electromagnetic environment through Shannon's entropy (probability) due to the uncertain characteristics of electromagnetic behavior in that complex environment. It suggests using the entropy method to analyze the complexity of the electromagnetic environment. The entropy theory is also used in the radiation source signal identification [37; 38]. These entropy-based methods are preliminary attempts at an objective quantitative analysis of the complexity of the electromagnetic environment. \begin{table}
\begin{tabular}{c c c c} \hline
**Electromagnetic Environment** & **The Hierarchy of the Evaluation System** & **Complexity Classification and the Quantitative Value** & **Reliability of Index Weighting (CC)** \\ \hline Environment 1 [30] & & & Simply: 0–0.2 \\ Environment 1 [30] & & & Mildly: 0.2–0.4 \\  & & & Moderately: 0.4–0.7 \\  & & & Severely: 0.7–1 \\  & & & \\ \hline Environment 2 [31] & & & Simply: 0–(10 + 10K)\% \\ Environment 2 [31] & & & Middly: (10 + 10K)\%–(30 + 5K)\% \\  & & & Moderately: (30 + 5K)\%–(60 + 2K)\% \\  & & Severely: (60 + 2K)\% \\  & & & Severely: 0–(60 + 2K)\% \\  & & & K is the adaptability coefficient of a \\  & & & specific equipment in the \\  & & & electromagnetic environment \\ \hline Environment 3 [33] & & Simply: 3 \\  & & Mildly: 5 \\  & & Moderately: 7 \\  & & Severely: 9 \\ \hline \end{tabular}
\end{table} 
Table 2: The typical hierarchy of the evaluation system and quantitative representation in grey theory and the AHP method. Figure 4: The application of entropy theory in an electromagnetic environmental effects study. In their application, [PERSON] et al. [39] proposed a method using compound information entropy to evaluate the electromagnetic environment's complexity. The probability models of type entropy, density entropy, and distribution entropy are established, respectively. The evaluation indexes in the four domains are involved. Then, the composite information for the entropy model is constructed through the weighting method, which can reasonably illustrate the complexity of the electromagnetic environment. However, each weighting is defined customarily, which leads to subjective models. [PERSON] et al. [40] first calculated the number of quantified gray pixel values at a certain range based on gray image data. Then, the probability of gray pixel values could be obtained. Subsequently, they obtained the image gray distribution entropy based on Shannon's entropy. The qualitative and quantitative research on both of the two kinds of suppressing interferences, radio and modulated frequency noises, was carried out on ISAR (Inverse Synthesis Aperture Radar) to evaluate the electromagnetic interference. In the initial attempt, the image entropy in the electromagnetic environmental effects evaluation is not refined enough to measure the complexity of the electromagnetic environment. [PERSON] et al. [41] constructed the grayscale image of the electromagnetic environment based on the data in the four domains.