A Scheme to Improve the Accuracy of Antenna Impedance Detection

The detection of antenna impedance is the core component of the Ultra-short-wave modulation System. The main scheme of current engineering application environment is vector impedance detection. This scheme is widely used because it has the advantages of high accuracy and wide range of measurable frequencies based on vector network and transmission line theory. However, the original vector impedance detection scheme has extremely high requirements on the performance of the circuit, and the system error in the high-frequency environment is difficult to restrain by calibration. In order to solve the above problems, this paper proposes a scheme based on Integrated Learning. The program builds a supervised machine learning model to suppress system errors through the data acquisition of standard devices thus improve the accuracy of impedance inspection The test results show that the impedance detection scheme based on Integrated Learning improves the accuracy significantly compared to the original vector impedance detection method.