ISAR Imaging for Non-cooperative Targets based on Sharpness Criterion under Low SNR

Inverse synthetic aperture radar (ISAR) imaging for non-cooperatives targets with complex translational motion (TM) and 3D rotational (RM) face the problem of spatial-variant (SV) high-order phase modulation. Existing ISAR technique cannot compensate modulation completely, especially under low signal-to-noise-ratio (SNR). In this work, an efficient approach is proposed non-cooperative SNR. First, signal model TM RM are established, where 2-D error deduced by utilizing a nonstationary image projection plane (IPP) model. Second, to mitigate influence noise, adaptive de-noising filter generated exploring similarity between profiles echoes. addition, inspired characteristic that all scatterers share same TM, compensating factors extracted from prominent scatterers, which can absolutely avoid accumulation residual errors. Meanwhile, coherence fully utilized SV errors caused RM. Finally, both simulated electromagnetic data experiments validate effectiveness robustness method.