Abstract
Conventional compressive sensing (CS)-based imaging methods allow images to be reconstructed from a small amount of data, while they suffer from high computational burden even for a moderate scene. To address this problem, this paper presents a novel two-dimensional (2D) CS imaging algorithm for strip-map synthetic aperture radars (SARs) with zero squint angle. By introducing a 2D separable formulation to model the physical procedure of the SAR imaging, we separate the large measurement matrix into two small ones, and then the induced algorithm can deal with 2D signal directly instead of converting it into 1D vector. As a result, the computational load can be reduced significantly. Furthermore, thanks to its superior performance in maintaining contour information, the gradient space of the SAR image is exploited and the total variation (TV) constraint is incorporated to improve resolution performance. Due to the non-differentiable property of the TV regularizer, it is difficult to directly solve the induced TV regularization problem. To overcome this problem, an improved split Bregman method is presented by formulating the TV minimization problem into a sequence of unconstrained optimization problem and Bregman updates. It yields an accurate and simple solution. Finally, the synthesis and real experiment results demonstrate that the proposed algorithm remains competitive in terms of high resolution and high computational efficiency.
Highlights
IntroductionSynthetic aperture radar (SAR) represents a powerful active remote-sensing tool [1,2]
Synthetic aperture radar (SAR) represents a powerful active remote-sensing tool [1,2]as it allows to produce high resolution image from the region of interest (ROI)
SAR with zero squint angle based on the modified alternating split Bregman method
Summary
Synthetic aperture radar (SAR) represents a powerful active remote-sensing tool [1,2]. As it allows to produce high resolution image from the region of interest (ROI). Such a useful tool is capable of operating in adverse weather and illumination conditions, and plays a significant role in various applications such as terrain mapping, environmental monitoring, and resources exploration. During the coherent processing interval (CPI), the radar emits radio waves towards the ROI under a fixed squint angle, and achieves a two-dimensional (2D) wide swath image from the received echoes using an image formation algorithm. The length limitations of synthetic aperture and linear array lead to a poor azimuth resolution, which eventually degrades the image quality
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have