Range and velocity estimation using kernel maximum correntropy based nonlinear estimators in non-Gaussian clutter

Uday Kumar Singh; Rangeet Mitra; Vimal Bhatia; Amit Kumar Mishra

doi:10.1109/TAES.2019.2948518

Range and velocity estimation using kernel maximum correntropy based nonlinear estimators in non-Gaussian clutter

Uday Kumar Singh^*, Rangeet Mitra, Vimal Bhatia, Amit Kumar Mishra

^*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

10 Dyfyniadau (Scopus)

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In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer-Rao lower bound using a modified Fisher information matrix.

Iaith wreiddiol	Saesneg
Rhif yr erthygl	8880529
Tudalennau (o-i)	1992-2004
Nifer y tudalennau	13
Cyfnodolyn	IEEE Transactions on Aerospace and Electronic Systems
Cyfrol	56
Rhif cyhoeddi	3
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/TAES.2019.2948518
Statws	Cyhoeddwyd - 23 Hyd 2019
Cyhoeddwyd yn allanol	Ie

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10.1109/TAES.2019.2948518

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@article{501b9e5d20694398bf3d460979eef170,

title = "Range and velocity estimation using kernel maximum correntropy based nonlinear estimators in non-Gaussian clutter",

abstract = "In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer-Rao lower bound using a modified Fisher information matrix.",

keywords = "Delay, Doppler shift, kernel maximum correntropy (KMC), linear frequency modulated (LFM), stepped frequency (SF)",

author = "Singh, {Uday Kumar} and Rangeet Mitra and Vimal Bhatia and Mishra, {Amit Kumar}",

note = "Publisher Copyright: {\textcopyright} 1965-2011 IEEE.",

year = "2019",

month = oct,

day = "23",

doi = "10.1109/TAES.2019.2948518",

language = "English",

volume = "56",

pages = "1992--2004",

journal = "IEEE Transactions on Aerospace and Electronic Systems",

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TY - JOUR

T1 - Range and velocity estimation using kernel maximum correntropy based nonlinear estimators in non-Gaussian clutter

AU - Singh, Uday Kumar

AU - Mitra, Rangeet

AU - Bhatia, Vimal

AU - Mishra, Amit Kumar

PY - 2019/10/23

Y1 - 2019/10/23

N2 - In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer-Rao lower bound using a modified Fisher information matrix.

AB - In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer-Rao lower bound using a modified Fisher information matrix.

KW - Delay

KW - Doppler shift

KW - kernel maximum correntropy (KMC)

KW - linear frequency modulated (LFM)

KW - stepped frequency (SF)

UR - http://www.scopus.com/inward/record.url?scp=85079665425&partnerID=8YFLogxK

U2 - 10.1109/TAES.2019.2948518

DO - 10.1109/TAES.2019.2948518

M3 - Article

AN - SCOPUS:85079665425

SN - 0018-9251

VL - 56

SP - 1992

EP - 2004

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

IS - 3

M1 - 8880529

ER -

Range and velocity estimation using kernel maximum correntropy based nonlinear estimators in non-Gaussian clutter

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