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Entropy 2018, 20(4), 256; https://doi.org/10.3390/e20040256

Information Geometry for Radar Target Detection with Total Jensen–Bregman Divergence

1
School of Electronic Science, National University of Defence Technology, Changsha 410073, China
2
Space Engineering University, Beijing 101400, China
*
Authors to whom correspondence should be addressed.
Received: 16 February 2018 / Revised: 27 March 2018 / Accepted: 6 April 2018 / Published: 6 April 2018
(This article belongs to the Section Information Theory)
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Abstract

This paper proposes a radar target detection algorithm based on information geometry. In particular, the correlation of sample data is modeled as a Hermitian positive-definite (HPD) matrix. Moreover, a class of total Jensen–Bregman divergences, including the total Jensen square loss, the total Jensen log-determinant divergence, and the total Jensen von Neumann divergence, are proposed to be used as the distance-like function on the space of HPD matrices. On basis of these divergences, definitions of their corresponding median matrices are given. Finally, a decision rule of target detection is made by comparing the total Jensen-Bregman divergence between the median of reference cells and the matrix of cell under test with a given threshold. The performance analysis on both simulated and real radar data confirm the superiority of the proposed detection method over its conventional counterparts and existing ones. View Full-Text
Keywords: information geometry; Hemitian positive-definite matrix; total Jensen–Bregman divergence; median matrix; radar target detection information geometry; Hemitian positive-definite matrix; total Jensen–Bregman divergence; median matrix; radar target detection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Hua, X.; Fan, H.; Cheng, Y.; Wang, H.; Qin, Y. Information Geometry for Radar Target Detection with Total Jensen–Bregman Divergence. Entropy 2018, 20, 256.

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