Estimating Signal Parameters in Strong Clutter Using SVM-Based Chaos Synchronization

In this paper, a novel approach for estimating signal parameters in strong clutter using chaos synchronization based on Support vector machine (SVM) is proposed. Assuming that the clutter process is chaotic, chaos synchronization is found to be able to extract the weak signal even when the signal is totally embedded inside the clutter spectrum. When the dynamics of the chaotic system is unknown, an SVM-based chaos synchronization is proposed to estimate the signal parameters. The unbiasedness and efficiency of the proposed approach are evaluated theoretically. Computer simulations on estimating sinusoidal frequencies confirm that the weak target frequencies can be estimated accurately. The proposed method is shown to have a better Mean square error (MSE) performance than the conventional techniques. Apply the proposed method to the narrowband interference cancellation problem in a Spread spectrum (SS) communication system and it is demonstrated that the proposed method can effectively suppress the narrowband interference.