| ELECTRONIC ENGINEERING |
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Man-made target detection in polarimetric SAR images using the Riemannian kernel Fisher criterion |
| GAO Wei1, YIN Junjun2, YANG Jian1 |
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;
2. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China |
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Abstract Detection of man-made targets is essential for automatic interpretation of polarimetric synthetic aperture radar (SAR) images. This paper describes a man-made target detection method that utilizes the Riemannian kernel Fisher criterion. The kernel function is constructed by means of a Riemannian metric defined on the manifold of Hermitian positive definite matrices. The polarimetric covariance matrices are mapped into the high-dimensional feature space induced by the kernel function and then discriminated by the Fisher criterion. This method takes into account the special matrix structure of the polarimetric SAR data and does not assume any statistical models; therefore, it is particularly suitable for detecting man-made targets in polarimetric SAR images. The effectiveness of this method is verified in the context of ship detection. Tests show that this method outperforms other detectors, especially for low target-to-clutter ratio.
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| Keywords
polarimetric SAR
man-made target detection
Riemannian manifold
kernel Fisher criterion
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Issue Date: 15 September 2016
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2016,
Vol. 56
