MACHe - Model-based algorithm for classification of helicopters

Domenico Gaglione

doi:10.1109/MAES.2016.150246

MACHe - Model-based algorithm for classification of helicopters

Domenico Gaglione

Electronic And Electrical Engineering

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

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Abstract

Secondary motions of a target, such as rotating blades of a helicopter's main rotor, induce a Doppler modulation around the main Doppler shift. This represents a unique feature of the target itself, known as micro-Doppler signature, and can be used for classification purposes. In this student research highlight a model-based automatic helicopter classification algorithm is presented. It is a parametric classification approach based on a sparse signal recovery method and it is independent of both the initial position of the blades and the aspect angle. The algorithm is tested on simulated and real data.

Original language	English
Pages (from-to)	38-40
Number of pages	3
Journal	IEEE Aerospace and Electronic Systems Magazine
Volume	31
Issue number	8
DOIs	https://doi.org/10.1109/MAES.2016.150246
Publication status	Published - 29 Aug 2016

Keywords

Doppler modulation
micro-Doppler signature
helicopter classification algorithm

Access to Document

10.1109/MAES.2016.150246

Gaglione-AESM-2016-Model-based-algorithm-for-classification-of-helicoptersAccepted author manuscript, 1.71 MB

Signal Processing Solutions for the Networked Battlespace
Soraghan, J. & Weiss, S.
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research

Cite this

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title = "MACHe - Model-based algorithm for classification of helicopters",

abstract = "Secondary motions of a target, such as rotating blades of a helicopter's main rotor, induce a Doppler modulation around the main Doppler shift. This represents a unique feature of the target itself, known as micro-Doppler signature, and can be used for classification purposes. In this student research highlight a model-based automatic helicopter classification algorithm is presented. It is a parametric classification approach based on a sparse signal recovery method and it is independent of both the initial position of the blades and the aspect angle. The algorithm is tested on simulated and real data.",

keywords = "Doppler modulation, micro-Doppler signature, helicopter classification algorithm",

author = "Domenico Gaglione",

note = "{\textcopyright} 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, f or resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.",

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language = "English",

volume = "31",

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AU - Gaglione, Domenico

N1 - © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, f or resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2016/8/29

Y1 - 2016/8/29

N2 - Secondary motions of a target, such as rotating blades of a helicopter's main rotor, induce a Doppler modulation around the main Doppler shift. This represents a unique feature of the target itself, known as micro-Doppler signature, and can be used for classification purposes. In this student research highlight a model-based automatic helicopter classification algorithm is presented. It is a parametric classification approach based on a sparse signal recovery method and it is independent of both the initial position of the blades and the aspect angle. The algorithm is tested on simulated and real data.

AB - Secondary motions of a target, such as rotating blades of a helicopter's main rotor, induce a Doppler modulation around the main Doppler shift. This represents a unique feature of the target itself, known as micro-Doppler signature, and can be used for classification purposes. In this student research highlight a model-based automatic helicopter classification algorithm is presented. It is a parametric classification approach based on a sparse signal recovery method and it is independent of both the initial position of the blades and the aspect angle. The algorithm is tested on simulated and real data.

KW - Doppler modulation

KW - micro-Doppler signature

KW - helicopter classification algorithm

U2 - 10.1109/MAES.2016.150246

DO - 10.1109/MAES.2016.150246

M3 - Article

SN - 0885-8985

VL - 31

SP - 38

EP - 40

JO - IEEE Aerospace and Electronic Systems Magazine

JF - IEEE Aerospace and Electronic Systems Magazine

IS - 8

ER -

MACHe - Model-based algorithm for classification of helicopters

Abstract

Keywords

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Signal Processing Solutions for the Networked Battlespace

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