JOURNAL ARTICLE

A modified matrix CFAR detector based on maximum eigenvalue for target detection in the sea clutter

Abstract

Riemannian distance based matrix constant false alarm rate (CFAR) detector under small number of pulses provides a novel mechanism for detecting radar targets against the background of sea clutter. However, the computational complexity of this detector is heavy. In this paper, using the maximum eigenvalue, we propose two blind algorithms for rank one signal. The proposed methods achieve high detection rates with low computational complexity in which the maximum eigenvalue is employed as the test statistic to modify the Riemannian method. Furthermore, the CFAR property is derived by the group invariant theory. The computational complexity is also analyzed and simulation results verify the effectiveness of the proposed detection methods.

Keywords:
Constant false alarm rate Clutter Computational complexity theory Detector Algorithm Computer science Eigendecomposition of a matrix Eigenvalues and eigenvectors Radar Detection theory Likelihood-ratio test Matrix (chemical analysis) Test statistic Artificial intelligence Mathematics Statistical hypothesis testing Statistics Physics Telecommunications

Metrics

7
Cited By
1.87
FWCI (Field Weighted Citation Impact)
21
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Radar Systems and Signal Processing
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced SAR Imaging Techniques
Physical Sciences →  Engineering →  Aerospace Engineering
Direction-of-Arrival Estimation Techniques
Physical Sciences →  Computer Science →  Signal Processing

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