CFAR Detection Based on Adaptive Tight Frame and Weighted Group-Sparsity Regularization for OTHR

In high-frequency over-the-horizon radar (OTHR), it is a challenging work to detect targets in the nonhomogeneous range-Doppler (RD) map with multitarget interference and sharp/smooth clutter edges. The intensity transition of the clutter edge may be sharp or smooth due to the coexistence of atmosph...

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Bibliographic Details
Published inIEEE transactions on geoscience and remote sensing Vol. 59; no. 3; pp. 2058 - 2079
Main Authors Li, Yang, Wu, Longshan, Zhang, Ning, Zhang, Xinchao, Li, Yajun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive tight frame
Algorithms
Clutter
constant false alarm rate (CFAR) detection
Detection
Detectors
Doppler sonar
Image edge detection
Objective function
Over-the-horizon radar
over-the-horizon radar (OTHR)
Parameter estimation
Radar
Radar detection
Regularization
Robustness (mathematics)
Sea surface
Sparsity
spatial information
Statistical analysis
Statistical distributions
Surface clutter
Target detection
weighted group-sparsity regularization
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Summary:In high-frequency over-the-horizon radar (OTHR), it is a challenging work to detect targets in the nonhomogeneous range-Doppler (RD) map with multitarget interference and sharp/smooth clutter edges. The intensity transition of the clutter edge may be sharp or smooth due to the coexistence of atmospheric noise, sea clutter, and ionospheric clutter in OTHR. The analysis of the RD map shows the spatial correlation among neighboring cell-under-test (CUT) that varies from clutter to clutter. This article proposes an algorithm that uses the spatial relationship to estimate the statistical distribution parameters of every CUT by the adaptive tight frame and the weighted group-sparsity regularization. In the proposed algorithm, the spatial relationship is formulated mathematically by regularization terms and combined with the log-likelihood function of CUTs to construct the objective function. The proposed algorithm is verified by the simulated data and real RD maps collected from both trial sky-wave and surface-wave OTHRs in which it shows robust and improved detection.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2020.3004224