Open AccessImproved phase curvature autofocus for stripmap synthetic aperture radar imaging
Author(s) -
Saeedi Jamal
Publication year - 2020
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2020.0334
Subject(s) - autofocus , synthetic aperture radar , computer science , computer vision , artificial intelligence , phase (matter) , radar imaging , range (aeronautics) , radar , algorithm , focus (optics) , optics , telecommunications , engineering , physics , aerospace engineering , chemistry , organic chemistry
Based on the theory of phase curvature autofocus (PCA) on stripmap synthetic aperture radar (SAR), an improved algorithm for increasing the accuracy of phase error compensation is presented in this study. PCA method was proposed to extend the phase gradient autofocus method for SAR systems in stripmap mode. The main problems concerned with the traditional PCA algorithm are related to selecting candidates in the image for phase error estimation, windowing, estimation procedure, and range shift due to the phase error. In this study, the modification of traditional PCA algorithm has been performed in different steps including the following: improving range‐compressed data, prominent points extraction, adaptive windowing, weighted maximum likelihood for phase error estimation, improving phase error result, range shift compensation, and determining the condition to end the iterations. Real data experiments demonstrate the success of the proposed autofocus method, which is applied to the stretched‐based pulsed mode SAR data set in the absence of highly accurate inertial navigation units.