Estimation of signal to noise ratio value based on Autoregressive Integrated Moving Average model in Intelligent Satellite System

For intelligent satellite system (ISS) to accomplish its missions, it has to adjust dynamically its operation according to future signal to noise ratio (SNR) value which can be estimated by using autoregressive integrated moving average (ARIMA) models. The ARIMA module takes the forecasted signal attenuation and real-time SNR values as the inputs and estimates the SNR values as the output. The ARIMA module will be updating the database with future SNR values in real-time for every one minute. This database will then be used by the ISS to achieve the most efficient operation mechanism.