[1]LI Rui,WANG Xiaodan,LEI Lei,et al.HRRP fusion recognition by RVM and DS evidence theory[J].CAAI Transactions on Intelligent Systems,2016,11(4):554-560.[doi:10.11992/tis.201511021]
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HRRP fusion recognition by RVM and DS evidence theory

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 4 Page number: 554-560 Column: 学术论文—机器感知与模式识别 Public date: 2016-07-25
Title:
HRRP fusion recognition by RVM and DS evidence theory
Author(s):
LI Rui;  WANG Xiaodan;  LEI Lei;  ZHAO Zhengchong
Institute of Air Defense and Anti-Missile, Air Force Engineering University, Xi’an 710051, China
Keywords:
target recognition; HRRP; RVM; DS
CLC:
TP181
DOI:
10.11992/tis.201511021
Abstract:
Aimed at improving target fusion recognition performance, an efficient approach to radar high resolution range profile (HRRP) fusion recognition is investigated. Three translation-invariant features were extracted from the HRRPs. Meanwhile, a high performance RVM (relevance vector machine) classifier was constructed and DS evidence theory used to fuse the recognition result. A HRRP classification approach, combining RVM and DS evidence theory, is then presented. The method makes full use of RVM output probability information, which solved the difficulty of getting BPA in DS evidence theory. The experimental results based on the simulated data show the effectiveness of the proposed approach.
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