Abstract
The nonhomogeneous clutter is a major challenge for ship detection in high-frequency mixed-mode surface wave radar. In this paper, a geometric barycenter-based reduced-dimension space-time adaptive processing method is proposed to suppress the clutter. Given the measured dataset, the range correlation of sea clutter is first investigated. Then, joint domain localized processing is applied to solve the training samples starve scenario in a practical system. The geometric barycenter-based training data selector is presented to select valid training samples and improve the accuracy of the clutter covariance matrix estimation. Finally, the validity of the proposed method is verified using the experimental data and the results show that it outperforms the conventional method in the nonhomogeneous environment of a practical system.
Highlights
High-frequency (HF) over-the-horizon radar (OTHR) has been successfully developed for target monitoring and ocean remote sensing by transmitting HF vertical polarization electromagnetic wave working at 3–30 MHz [1,2,3,4]
The advantages of the mixed propagation mode compared with the conventional high-frequency surface wave radar (HFSWR), are that more target information can be obtained due to additional propagation paths and the detection range can be extended for HFSWR owing to the ionosphere propagation path
The first-order sea clutter is contaminated by ionosphere clutter, so the IID training samples with cell under test (CUT) are limited and some highly contaminated samples need to be eliminated from the training data
Summary
High-frequency (HF) over-the-horizon radar (OTHR) has been successfully developed for target monitoring and ocean remote sensing by transmitting HF vertical polarization electromagnetic wave working at 3–30 MHz [1,2,3,4]. The advantages of the mixed propagation mode compared with the conventional HFSWR, are that more target information can be obtained due to additional propagation paths and the detection range can be extended for HFSWR owing to the ionosphere propagation path These features have drawn increasing attention to the new HF MMSWR. The first-order sea clutter is contaminated by ionosphere clutter, so the IID training samples with CUT are limited and some highly contaminated samples need to be eliminated from the training data How to select these samples is a valuable research issue for the clutter suppression processing in HF MMSWR. We combine the geometric barycenter-based covariance estimation algorithm with the reduced-dimension STAP method to overcome the heterogeneous clutter in HF MMSWR.
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
