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A Novel Feature Vector Using Complex HRRP for Radar Target Recognition.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Derong Liu
Shumin Fei
Zeng-Guang Hou
Huaguang Zhang
Changyin Sun
Source :
Advances in Neural Networks: ISNN 2007 (9783540723820); 2007, p1303-1309, 7p
Publication Year :
2007

Abstract

Radar high-resolution range profile (HRRP) has received intensive attention from the radar automatic recognition (RATR) community. Since the initial phase of a complex HRRP is strongly sensitive to target position variation, which is referred to as the initial phase sensitivity, only the amplitude information in the complex HRRP, what is called the real HRRP, is used for RATR. This paper proposes a novel feature extraction method for the complex HRRP. The extracted complex feature vector contains the difference phase information between range cells but no initial phase information in the complex HRRP. The recognition algorithms, frame-template-database establishment methods and preprocessing methods used in the real HRRP-based RATR can also be applied to the proposed complex feature vector-based RATR. The recognition experiments based on measured data show that the proposed complex feature vector can obtain better recognition performance than the real HRRP if only the cell interval parameters are proper. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540723820
Database :
Complementary Index
Journal :
Advances in Neural Networks: ISNN 2007 (9783540723820)
Publication Type :
Book
Accession number :
33176543
Full Text :
https://doi.org/10.1007/978-3-540-72383-7_152