Raw Data-Based Motion Compensation for High-Resolution Sliding Spotlight Synthetic Aperture Radar

Abstract

For accurate motion compensation (MOCO) in airborne synthetic aperture radar (SAR) imaging, a high-precision inertial navigation system (INS) is required. However, an INS is not always precise enough or is sometimes not even included in airborne SAR systems. In this paper, a new, raw, data-based range-invariant motion compensation approach, which can effectively extract the displacements in the line-of-sight (LOS) direction, is proposed for high-resolution sliding spotlight SAR mode. In this approach, the sub-aperture radial accelerations of the airborne platform are estimated via a well-developed weighted total least square (WTLS) method considering the time-varying beam direction. The effectiveness of the proposed approach is validated by two airborne sliding spotlight C band SAR raw datasets containing different types of terrain, with a high spatial resolution of about 0.15 m in azimuth.

Airborne SAR Autofocus Based on Blurry Imagery Classification

“…Therefore, combining motion compensation (MoCo)/autofocus processing for airborne SAR imaging [11][12][13][14] is necessary. In many cases, the motion compensation technique combined with the inertial navigation system (INS) and/or global position system (GPS) data cannot meet the expected accuracy requirements because the aircraft may not be able to carry enough high-precision INS/GPS equipment [15][16][17]. Consequently, the autofocus technique based on radar raw data needs to be implemented in airborne SAR imaging.…”

Novel sparse apertures ISAR imaging algorithm via the TLS‐ESPRIT technique

“…Normally, in the ISAR system, high range resolution is gained by adopting wide‐band signals. The large relative Doppler shift between targets and radar is a guarantee for high cross‐range resolution [1–6]. Exploiting long coherence processing interval (CPI) is an effective way to enhance azimuth resolution [7, 8].…”

Multi-Instance Inertial Navigation System for Radar Terrain Imaging

“…The second group of MOCO methods, called autofocus, consists in the analysis of the echo signals received by the radar sensor [14,[23][24][25][26][27][28][29][30][31][32][33]. A great variety of autofocus methods exists due to their individual limitations, e.g., the Phase Gradient Autofocus (PGA) needs the presence of highly reflective objects in the imaged area [24], while in the Map-Drift method the area should be diversified (presence of edges, shadows, etc.)…”