Abstract
The study is dedicated to the statistical optimization of radar imaging of surfaces with the synthetic aperture radar (SAR) technique, assuming a static surface area and applying the ability to move a sensor along a nonlinear trajectory via developing a new method and validating its operability for remote sensing and non-destructive testing. The developed models address the sensing geometry for signals reflected from a surface along with the observation signal–noise equation, including correlation properties. Moreover, the optimal procedures for coherent radar imaging of surfaces with the static SAR technology are synthesized according to the maximum likelihood estimation (MLE). The features of the synthesized algorithm are the decoherence of the received oscillations, the matched filtering of the received signals, and the possibility of using continuous signal coherence. Furthermore, the developed optimal and quasi-optimal algorithms derived from the proposed MLE have been investigated. The novel framework for radio imaging has demonstrated good overall operability and efficiency during simulation modeling (using the MATLAB environment) for real sensing scenes. The developed algorithms of spatio–temporal signal processing in systems with a synthesized antenna with nonlinear carrier trajectories open a promising direction for creating new methods of high-precision radio imaging from UAVs and helicopters.
Published Version
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