Effective Barrage Noise Jamming for Spotlight SAR Using Extended Kalman Filter-Based Kinematic Parameter Estimation

A barrage noise jamming method for spotlight synthetic aperture radar (SAR) with kinematic parameter estimation using extended Kalman filter (EKF) is newly proposed. The main objective of the proposed method is real-time generation of the jamming signals to create noise-like blankets with arbitrary locations and shapes in SAR images. Achieving the objective allows concentrating all jamming power within the noise patches with specific desired shapes, which enables more effective jamming compared to existing barrage jamming methods. We derived the jamming model to produce the noise-like blankets with desired shapes and locations in the SAR image. We also specified the kinematic parameters required to compute the jamming model, and derived the model to estimate them using EKF. Finally, we designed the algorithm with the derived models to generate the jamming signals. The feasibility for real-time implementation of the algorithm is verified through the complexity analysis. Since the proposed method does not require the prior knowledge about the platform motion, it is applicable to not only spaceborne SAR but also airborne SAR. The simulation results demonstrate that the proposed method shows robust parameter estimation performance, and outperforms the conventional barrage noise jamming due to the relatively high processing gain.