Kernel LMS-Based Estimation Techniques for Radar Systems

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

doi:10.1109/TAES.2019.2891148

Kernel LMS-Based Estimation Techniques for Radar Systems

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

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Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer-Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems.

Iaith wreiddiol	Saesneg
Rhif yr erthygl	8603824
Tudalennau (o-i)	2501-2515
Nifer y tudalennau	15
Cyfnodolyn	IEEE Transactions on Aerospace and Electronic Systems
Cyfrol	55
Rhif cyhoeddi	5
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/TAES.2019.2891148
Statws	Cyhoeddwyd - 07 Ion 2019
Cyhoeddwyd yn allanol	Ie

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10.1109/TAES.2019.2891148

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@article{5a2b728efbd94e15a5015114d1257c02,

title = "Kernel LMS-Based Estimation Techniques for Radar Systems",

abstract = "Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer-Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems.",

keywords = "Delay, doppler shift, kernel least mean square (KLMS), orthogonal frequency division multiplexed (OFDM) radar, reproducing kernel Hilbert space (RKHS)",

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

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

year = "2019",

month = jan,

day = "7",

doi = "10.1109/TAES.2019.2891148",

language = "English",

volume = "55",

pages = "2501--2515",

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

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T1 - Kernel LMS-Based Estimation Techniques for Radar Systems

AU - Singh, Uday Kumar

AU - Mitra, Rangeet

AU - Bhatia, Vimal

AU - Mishra, Amit Kumar

PY - 2019/1/7

Y1 - 2019/1/7

N2 - Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer-Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems.

AB - Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer-Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems.

KW - Delay

KW - doppler shift

KW - kernel least mean square (KLMS)

KW - orthogonal frequency division multiplexed (OFDM) radar

KW - reproducing kernel Hilbert space (RKHS)

UR - http://www.scopus.com/inward/record.url?scp=85059607238&partnerID=8YFLogxK

U2 - 10.1109/TAES.2019.2891148

DO - 10.1109/TAES.2019.2891148

M3 - Article

AN - SCOPUS:85059607238

SN - 0018-9251

VL - 55

SP - 2501

EP - 2515

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

IS - 5

M1 - 8603824

ER -

Kernel LMS-Based Estimation Techniques for Radar Systems

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