Design and Performance Analysis of Sparse TOPS SAR Mode - Hui Bi; Guoxu Li; Yufan Song; Jingjing Zhang; Daiyin Zhu; Wen Hong; Yirong Wu (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022)
Terrain observation by progressive scans (TOPS) is a novel and promising wide-swath synthetic aperture radar (SAR) imaging mode, which overcomes the scalloping effect existing in ScanSAR. Traditional imaging algorithms are computationally efficient in raw data processing of TOPS, but the problems from clutter and sidelobes suppression have not been effectively solved. Sparse SAR imaging not only effectively solves these problems, but also has great potential in improving system performance, e.g., lower requirement of pulse repetition frequency (PRF), higher swath coverage, less data amount, and lower system complexity. Therefore, this article proposes a novel sparse TOPS SAR imaging mode. The proposed mode combines advantages of sparse imaging system and TOPS mode to achieve high-quality and wide-swath SAR imaging. In this mode, we first design the beam position by timing diagram. Then, the basic parameters of the mode are calculated according to the radar equation, and the properties, such as grating lobes are analyzed. Finally, an $L_{2,1}$ -norm regularization based sparse TOPS SAR imaging algorithm is introduced to achieve the high-quality sparse scene recovery. Experimental results show that compared with conventional TOPS imaging mode, the proposed mode can obtain wide swath with lower PRF and effectively solve the effect on distributed target ambiguity ratio. Compared with matched filtering-based TOPS imaging algorithm, the sparse method can achieve unambiguous reconstruction of the considered scene from down-sampled data, and obtain the image with less artifacts.