A closed-loop strategy for cognitive radar based on the estimation of clutter power spectrum

To address the limitations of traditional radar in time-varying and complex environments, a novel closed-loop structure for cognitive radar is introduced in this paper. The proposed system begins by estimating the power spectrum density of clutter using a clutter inversion algorithm. Next it predicts the upcoming clutter information using an autoregression model and a clutter prior information matrix as input. Finally, it employs a water-filling method and a time-synthesis algorithm to design an optimal spectrum and a constant modulus transmit sequence utilizing the prediction clutter priori information. Moreover, experimental results using real-measured data under varying parameters demonstrate that the proposed strategy outperforms traditional radar process.