One-dimension range profile identification of radar targets based on a linear interpolation neural network

Guangmin Sun; Xinming Zhang; Peng Wang; Weixian Liu; Jeffrey S. Fu

doi:10.1016/S0165-1684(01)00083-4

One-dimension range profile identification of radar targets based on a linear interpolation neural network

Guangmin Sun^*, Xinming Zhang, Peng Wang, Weixian Liu, Jeffrey S. Fu

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

5 Scopus citations

Abstract

One-dimension range profile can reflect the precise geometric structure features of radar targets. The approach is comprehensively used for radar target identification (RTI), however it varies with target posture. This paper presents a novel neural network model - linear interpolation neural network (LINN) to solve the problem. LINN combines the variation information of one-dimension range profile with its invariant feature information. Simulation results show that this method greatly improves the target identification performance of radar systems.

Original language	English
Pages (from-to)	2033-2040
Number of pages	8
Journal	Signal Processing
Volume	81
Issue number	10
DOIs	https://doi.org/10.1016/S0165-1684(01)00083-4
State	Published - 10 2001
Externally published	Yes

Keywords

Linear interpolation
Neural network
One-dimension range profile
Radar target identification

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10.1016/S0165-1684(01)00083-4

Cite this

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title = "One-dimension range profile identification of radar targets based on a linear interpolation neural network",

abstract = "One-dimension range profile can reflect the precise geometric structure features of radar targets. The approach is comprehensively used for radar target identification (RTI), however it varies with target posture. This paper presents a novel neural network model - linear interpolation neural network (LINN) to solve the problem. LINN combines the variation information of one-dimension range profile with its invariant feature information. Simulation results show that this method greatly improves the target identification performance of radar systems.",

keywords = "Linear interpolation, Neural network, One-dimension range profile, Radar target identification",

author = "Guangmin Sun and Xinming Zhang and Peng Wang and Weixian Liu and Fu, {Jeffrey S.}",

year = "2001",

month = oct,

doi = "10.1016/S0165-1684(01)00083-4",

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AU - Sun, Guangmin

AU - Zhang, Xinming

AU - Wang, Peng

AU - Liu, Weixian

AU - Fu, Jeffrey S.

PY - 2001/10

Y1 - 2001/10

N2 - One-dimension range profile can reflect the precise geometric structure features of radar targets. The approach is comprehensively used for radar target identification (RTI), however it varies with target posture. This paper presents a novel neural network model - linear interpolation neural network (LINN) to solve the problem. LINN combines the variation information of one-dimension range profile with its invariant feature information. Simulation results show that this method greatly improves the target identification performance of radar systems.

AB - One-dimension range profile can reflect the precise geometric structure features of radar targets. The approach is comprehensively used for radar target identification (RTI), however it varies with target posture. This paper presents a novel neural network model - linear interpolation neural network (LINN) to solve the problem. LINN combines the variation information of one-dimension range profile with its invariant feature information. Simulation results show that this method greatly improves the target identification performance of radar systems.

KW - Linear interpolation

KW - Neural network

KW - One-dimension range profile

KW - Radar target identification

UR - http://www.scopus.com/inward/record.url?scp=0035479396&partnerID=8YFLogxK

U2 - 10.1016/S0165-1684(01)00083-4

DO - 10.1016/S0165-1684(01)00083-4

M3 - 文章

AN - SCOPUS:0035479396

SN - 0165-1684

VL - 81

SP - 2033

EP - 2040

JO - Signal Processing

JF - Signal Processing

IS - 10

ER -

One-dimension range profile identification of radar targets based on a linear interpolation neural network

Abstract

Keywords

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