MIMO Radar Accurate Imaging and Motion Estimation for 3-D Maneuvering Ship Target

Image deterioration problem occurs in radar imaging for ship target, which results from the complex time-varying motions of ship, the noise in channels, and the clutter on sea surface. It is hard to be solved effectively due to coherent accumulation sampling time and high-dimensional parametric model. Hence, an accurate imaging and motion estimation method based on multiple-input-multiple-out (MIMO) radar is presented. First, the multidimensional signal model is built to characterize target features accurately. To reduce the interference from sea clutters, a preprocessing strategy is exerted based on the space-time adaptive processing (STAP) theory, clutter signals can be suppressed effectually with constructing a Doppler spectrum model. Then, for accurate imaging and motion estimation, a combined trace norm minimization problem is deduced based on the relaxation of tensor rank, where the noise in sea environments is also considered. Meanwhile, generalized tensor total variation constraint is developed to ensure stable estimation and smooth imaging results when separating the noise term. Accordingly, an effective decomposition criterion is formulated based on alternating direction multiplier method (ADMM) strategy, and motion parameters can be precisely calculated based on the least square (LS) method. Finally, theoretical analysis and simulation results present the accurate performance of the proposed method.

Automated summary

In this study, an accurate imaging and motion estimation method based on multiple-input-multiple-out (MIMO) radar is proposed to tackle the image deterioration problem in radar imaging for ship target. By establishing a multidimensional signal model and employing a preprocessing strategy based on the space-time adaptive processing (STAP) theory, sea clutter interference can be effectively reduced.