Enhanced Meta-Heuristic Approach for Echo Suppression in Synthetic Aperture Radar Using Non-Periodic Interrupted Sampling

Echo cancellation is a deception jamming technique designed to nullify the target's echo and prevent its detection by enemy radar. Traditional methods rely on time-domain synchronization, but they struggle to fully suppress echoes when there is an amplitude mismatch. This limitation often leaves the target partially visible in synthetic aperture radar (SAR) images, reducing the effectiveness of the jamming technique. Non-periodic interrupted sampling modulation (NP-ISM) is applied as it produces a continuous jamming strip instead of discrete false targets whereas in Periodic sampling multiple false targets emerge even the real target echo is canceled which makes it easy to be countered by enemy radar. The improved henry gas solubility optimization algorithm (IHGSOA) is applied in the echo cancellation model to optimize the random rectangular envelope pulse train in the NP-ISM which enhances signal cancellation. This significantly reduces the Peak to Average Ratio (PAR), enabling more effective target echo suppression. A polynomial non-linear frequency modulation (PNLFM) is employed to reduce the PAR leading to significant improvement in signal-to-noise ratio (SNR), enabling more effective target echo cancellation. The proposed IHGSOA-based echo cancellation model effectively aligns the cancellation and echo signals through time-delay synchronization, minimizing errors even in the presence of a mismatch. The simulation results show that using the above cancelling system the desired target echo amplitude drops to 50% and 40% of its original target echo, hence the system has a very high cancellation effect. Thus, the effectiveness of the IHGSOA is evaluated by comparing its performance with other conventional algorithms.