The frequency selection and size of the models are due to the limitations of the computer's performance. The specifications of the computer used in the simulation are: CPU: E3-1231 v3, RAM: 8 GB, GPU: R9-280x, and the simulation program is CST2016 and the simulation type is monostatic.
| C ONCL US I ONIn this paper, we apply the Cauchy method to low-frequency RCS data in order to predict high-frequency RCS data and illustrate the error.Similarities in the graphs were checked based on the case where the error between the original RCS value and the predicted RCS value using the Cauchy method is 0 dB in the prediction frequency band of >6 GHz, and then it was judged whether prediction is possible.As a result, it has been shown that RCS data at high frequencies can be predicted using low-frequency RCS data.However, an angle close to 0 dB can be confirmed. Future work will be performed to study methods to increase the number of data, change the reference frequency of the LPF, and reduce error using techniques not used in this paper, in order to improve the accuracy of RCS data prediction with more complex changes.
ACKNOWLEDGMENTS AbstractIn the recently published article, Ramya et al. (Microw Opt Technol Lett. 2017;59:1837-1845. https://doi.org/10. 1002/mop.30636) proposed asymmetrical metamaterial absorber structure for wideband applications. It was shown that, the reported structure has wideband absorptivity