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Updated: Dec 15, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
Published on: February 12, 2014
A Single-Dataset-Based Pre-Processing Joint Domain Localized Algorithm for Clutter-Suppression in Shipborne
Liang Guo1, Xin Zhang1,2, Di Yao2,3
1School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China.
Abstract:
Due to the motion of the platform, the spectrum of first-order sea clutter will widen and mask low-velocity targets such as ships in shipborne high-frequency surface-wave radar (HFSWR). Limited by the quantity of qualified training samples, the performance of the generally used clutter-suppression method, space-time adaptive processing (STAP) degrades in shipborne HFSWR. To deal with this problem, an innovative training sample acquisition method is proposed, in the area of joint domain localized (JDL) reduced-rank STAP. In this clutter-suppression method, based on a single range of cell data, the unscented transformation is introduced as a preprocessing step to obtain adequate homogeneous secondary data and roughly estimated clutter covariance matrix (CCM). The accurate CCM is calculated by integrating the approximate CCM of different range of cells. Compared with existing clutter-suppression algorithms for shipborne HFSWR, the proposed approach has a better signal-to-clutter-plus-noise ratio (SCNR) improvement tested by real data.
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