Adaptive Parameter Estimation for Compound Interrupted Sampling and Repeating Jamming
Liyi Liu, Qinzhe Lv, Junliang Liu, Yaojun Wu, Yinghui Quan
Abstract
With the increasing complexity of the electromagnetic environment and a growing number of jamming sources, radar systems are facing an unprecedented threat of compound jamming. Precision in estimating the key parameters of compound jamming is of paramount significance for developing effective anti-jamming strategies. In response to the current lack of effective solutions for estimating parameters of compound interrupted sampling and repeating jamming (ISRJ), a dualcompound ISRJ parameter estimation method is proposed, which employs Gaussian multi-peak fitting for adaptively decoupling jamming signals and leverages the inherent temporal periodicity characteristics of ISRJ for parameter matching. The proposed method fully exploits the latent information in the received signals and conducts efficient processing, while being able to adapt to various jamming scenarios. The simulation results demonstrate the effectiveness and robustness of the proposed method