Physics

Clutter

Pattern recognition (psychology)

Mathematics

Continuous-wave radar

Radar imaging

Algorithm

Speckle pattern

Statistics

Gaussian

Artificial intelligence

Covariance matrix

Computer science

Quantum mechanics

Likelihood-ratio test

Stationary target indication

Radar

Telecommunications

Constant false alarm rate

Detector

IEEE Transactions on Geoscience and Remote Sensing

This article addresses the detection problem of radar targets embedded in nonhomogeneous and non-Gaussian sea clutter. Nonhomogeneity leads to insufficiency of secondary data for estimating the clutter speckle covariance matrix, and non-Gaussianity causes sea clutter to become spiky. In this article, the persymmetry of the clutter covariance matrix is adopted to alleviate the requirement of secondary data, and the prior distribution of clutter texture is exploited to tackle the clutter non-Gaussianity. Based on such clutter knowledge, three adaptive detectors are proposed according to the principles of the generalized likelihood ratio test, the Wald test, and the Rao test. It is proven that three detectors ensure constant false alarm rate (CFAR) properties with respect to both the clutter speckle covariance matrix and the clutter power mean. Simulation experiments show that three detectors outperform their competitors.

Persymmetric Detection of Radar Targets in Nonhomogeneous and Non-Gaussian Sea Clutter