Name
Title | ||
|---|---|---|
Information Geometry for Radar Target Detection with Total Jensen-Bregman Divergence. |
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/e20040256 | ENTROPY |
Keywords | Field | DocType |
information geometry,Hemitian positive-definite matrix,total Jensen-Bregman divergence,median matrix,radar target detection | Radar,Decision rule,Applied mathematics,Information geometry,Mathematical optimization,Divergence,Matrix (mathematics),Bregman divergence,Hermitian matrix,Mathematics,Von Neumann architecture | Journal |
Volume | Issue | ISSN |
20 | 4 | 1099-4300 |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoqiang Hua | 1 | 8 | 1.88 |
| Haiyan Fan | 2 | 126 | 8.13 |
| Yongqiang Cheng | 3 | 133 | 29.99 |
| Hongqiang Wang | 4 | 69 | 9.96 |
| Yuliang Qin | 5 | 142 | 27.06 |