High-resolution Inverse Synthetic Aperture Radar Imaging of Maneuvering Targets Joint with Parameter Estimation

For inverse synthetic aperture radar (ISAR) imaging, the high maneuverability of target will introduce additional Doppler modulation, which increases the difficulty of imaging and scaling in low signal-to-noise ratio (SNR). To resolve this, this paper proposes a novel algorithm of joint high-resolution imaging and parameter estimation, which can realize well-focused imaging and accurate image scaling. The signal model of target maneuverability is constructed by considering the rotational jerk. To deal with the unknown rotational rate and rotational center, the approach using minimum entropy is presented to realize these parameter estimation. Meanwhile, the estimate the rotational parameters are used for azimuth scaling by extracting the 2-D target geometry. In comparison with the conventional imaging algorithms, such as time-frequency approach, the proposed algorithm in this paper can achieve higher resolution with full aperture data, and can realize acceptable imaging performance even in low SNR. Finally, the experimental analysis is performed to confirm the effectiveness of the proposed algorithm.