Hopping instants detection and frequency tracking of frequency hopping signals with single or multiple channels

Abstract

Most of previous blind parameter estimation methods of frequency hopping (FH) signals with a single channel do not adapt to overlapped signals, whereas the multi-channel-based ones are computationally much too expensive. Moreover, all the single- and multiple-channel-based methods use batch processing techniques, and they are not able to give real-time estimates of the hopping frequencies. This study establishes a temporal autoregressive moving average (ARMA) model of the temporally overlapped FH signals, which is then used to detect the frequency hops once they happen, and track the hopping frequencies online. Numerical examples are carried out to demonstrate the effectiveness of the proposed method.