Abstract
In general, conventional error correction for inverse synthetic aperture radarimaging consists of range alignment and phase adjustment, which compensate range shift and phase error, respectively. Minimum entropy-based methods have been proposed to realize range alignment and phase adjustment. However, it becomes challenging to align high-resolution profiles when strong noise presents, even using entropy minimization. Consequently, the subsequent phase adjustment fails to correct phase errors. In this article, we propose a novel method for translational motion correction, where entropy minimization is utilized to achieve range alignment and phase adjustment jointly. And, a coordinate descent algorithm is proposed to solve the optimization implemented by quasi-Newton algorithm. Moreover, a method for coarse motion estimation is also proposed for initialization in solving the optimization. Both simulated and real-measured datasets are used to confirm the effectiveness of the joint motion correction in low signal-to-noise ratio situations.
Highlights
Inverse synthetic aperture radar (ISAR) imaging has been a widely addressed topic in last few decades [1,2,3]
It is widely accepted that global optimization methods are more robust to reflectivity scintillation and additive noise than maximum correlation method, in which the problem of ISAR range alignment is formulated by using some global metrics
Based on the fact that both range shift and phase error are directly related to the quality of the focused image, in this article, we present a novel entropy-based approach to joint range alignment and phase adjustment
Summary
Inverse synthetic aperture radar (ISAR) imaging has been a widely addressed topic in last few decades [1,2,3]. Successful phase adjustment can only be ensured when perfect range alignment is obtained, while if the profiles are misaligned in some cases, such as strong noise situation, even the image metric-based methods fail to correct phase errors. To overcome this problem, in [14], a joint correction scheme for simultaneous range alignment and phase adjustment was proposed based on a two-order polynomial model of the translational range history, and a novel coarse estimation of both velocity and acceleration was developed to accelerate the motion estimation. Some conclusions are drawn and some future works are viewed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
