An Interrupted Sampling Repeater Jamming Suppression Algorithm Based on Multi-Domain Joint Sparse Reconstruction

​ Conventional signal reconstruction-based algorithms for countering Interrupted Sampling Repeater Jamming (ISRJ) are highly dependent on the accuracy of parameter estimation and suffer from high computational complexity. And filter-based algorithms require high separability between the jamming and target signals, rendering them ineffective in complex scenarios where the target and jamming signals overlap. To address these issues, this paper proposes a novel ISRJ suppression algorithm based on multi-domain joint sparse reconstruction. The target signal is sparsely represented using a time-delay dictionary matrix constructed from the transmitted signal. Leveraging the amplitude difference between the ISRJ and the target in the time-frequency domain, the jamming signal is sparsely represented in this domain. To efficiently solve this optimization problem, a solver based on the Alternating Direction Method of Multipliers (ADMM) is employed for iterative solution. Simulation results demonstrate that the proposed algorithm achieves higher robustness and a superior Signal-to-Jamming Ratio Improvement Factor (SJRIF) compared to the traditional max-Time Frequency (max-TF) filter algorithm, particularly when the target and jamming signals overlap in the time-frequency domain.