Comprehensive models for antenna measurement utilizing compressive sensing in multi-probe systems

Measuring the radiation pattern of complex antennas can often be a time-consuming process. As a result, researchers are seeking techniques that can reduce measurement time while maintaining accuracy. Compressive sensing is a powerful method in signal processing that can be applied to various types of measurements. It enhances systems by reducing energy consumption, optimizing memory usage, increasing measurement speed, and ultimately shortening measurement time. Although compressive sensing has seen significant advancements in theoretical research, designing systems and application models based on this technique requires a thorough understanding of its strengths and limitations. In this study, we evaluate CS-based antenna measurement models using simulated datasets of antenna. Results show that measurement time can be reduced by up to 60% while maintaining reconstruction accuracy within 5% RMSE. These findings highlight the efficiency of CS in antenna characterization.