ISAR Imaging for Fluctuating Ships Based on a Fast Bilinear Parameter Estimation Algorithm

For inverse synthetic aperture radar (ISAR) imaging of ships fluctuating with oceanic waves, azimuth echoes of a range cell have to be modeled as cubic phase signals (CPSs) after the range alignment and the phase adjustment. In ISAR imaging based on the CPS model, the chirp rate and the quadratic chirp rate are identified as causes of the target image defocus and need to be estimated with an effective algorithm. In this paper, a fast bilinear parameter estimation algorithm is proposed and applied in ISAR imaging for fluctuating ships by employing the cubic phase bilinear function, the nonuniform fast Fourier transform (NUFFT), and the parameter space switching method. Compared to two existing representative parameter estimation algorithms for the CPS, the advantages of this proposed estimation algorithm are: 1) the computational cost is lower due to the NUFFT and the parameter space switching method and 2) the bilinearity and the energy accumulation operation guarantee a higher anti-noise performance and a better suppression on cross-terms. Through simulations on synthetic models and the real radar data, we verify the effectiveness of this fast bilinear parameter estimation algorithm and the corresponding ISAR imaging algorithm.