Research on communication signal waveform technology of aerospace telemetry track and command network based on polynomial regression

Abstract

In recent years, due to the development of communication measurement and control technology and the rise of artificial intelligence technology, the construction of intelligence and informatization has become the main direction of China's wireless communication application field in the future. However, due to the increasingly scarce spectrum resources, the interference in the communication environment is complex and changeable. With the development of technology, artificial intelligence uses a large number of structured data mining methods to fit nonlinear information systems. This paper considers the relationship between communication signal waveform parameters and environmental SNR and bit error rate in aerospace measurement and control scenarios, and proposes to use polynomial regression algorithm to build an adaptive parameter learning model, while using the grid search hyperparameter optimization method to find the optimal combination of hyperparameters.