Imaging method for space precession targets with intermittent observation

Narrowband radar can accurately image Precession targets through micro Doppler imaging. However, in the actual spinning process of targets, the radar signal may periodically obstruct the target or be interfered. When the complex back projection algorithm is used to image the rotating target in space, higher sidelobes may appear, which affects the imaging quality. A spinning target imaging algorithm based on Bayesian Compressive Sensing (BCS) is proposed. This algorithm uses the characteristics of rotating target echo signal and compressive sensing theory to obtain enough information with intermittent observation data to reconstruct the target space. The simulation results show that under intermittent observation conditions, compared with the complex back projection algorithm, it has lower sidelobe and its imaging effect is better.