Abstract

As a result of technology advancements in the signal processing industry, radar performance has improved during the previous few decades. The RCS of an object is a measurement of how much energy it reflects back to a radar. The radar cross section (RCS) of simple and sophisticated objects is investigated because it is critical for identifying targets and improving or decreasing their radar visibility over a wide range of frequency ranges. To determine the RCS of any object, first learn how the RCS parameters change as the aspect angle changes. Simulate the RCS to represent the required objectives under various situations such as angle of view and frequency range in this project. This method is developed to assess radar overall performance. After then, the radar target's data is simulated. Swerling models were used in this project. First, create and test the simulation's ideology. In order to potentially, successfully implement these models on a radar system, they are simulated in MATLAB and Xilinx. In MATLAB, Radar Cross Section signatures are detected for further improvement in order to find accurate RCS. The objective of this research is to provide an overview of the conceptual foundation and technical approach to RCS prognosis for readers.

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