An adaptive filtering approach to chirp estimation and ISAR imaging of maneuvering targets

In inverse synthetic aperture radar (ISAR) imaging, due to the noncooperative motion of maneuvering targats the Doppler shifts of the scatterers are usually time-varying, and the radar return signals are usually chirps. The chirp estimation plays an important role in the performance of the ISAR imaging. Li and Stoica recently presented an adaptive FIR filtering approach to estimate the amplitudes and phases of sinusoidal signals and applied this method to the synthetic aperture radar (SAR) imaging with the sinusoidal signal model. In this paper, we extend the Li and Stoica's algorithm to estimate the chirps and then apply it to the ISAR imaging of maneuvering targets. The extended algorithm is verified by simulated data.