A novel clutter cancellation method based on sparse representation for passive radar

Utilizing the sparsity of the clutter time delay, a novel clutter cancellation method based on sparse representation is proposed to improve the cancellation performance when fractional time delay exists in the clutter of the surveillance signals. The proposed method performs the cancellation by transforming the clutter cancellation problem to the sparse signal reconstruction problem, in which the spectrum division technique is introduced to establish the signal model of the clutter time delay measurement. Taking advantage of the sparse representation theory, high estimation accuracy and resolution of the time delay are achieved in the proposed method. The simulation results prove that compared with the traditional methods, the proposed method improves the clutter cancellation and weak target detection performance when there exists clutter with fractional time delay at low signal-to-noise ratio.