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

^*Corresponding author for this work

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

20 Citations (Scopus)

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.

Original language	English
Article number	8603824
Pages (from-to)	2501-2515
Number of pages	15
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	55
Issue number	5
DOIs	https://doi.org/10.1109/TAES.2019.2891148
Publication status	Published - 07 Jan 2019
Externally published	Yes

Keywords

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

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10.1109/TAES.2019.2891148

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KW - Delay

KW - doppler shift

KW - kernel least mean square (KLMS)

KW - orthogonal frequency division multiplexed (OFDM) radar

KW - reproducing kernel Hilbert space (RKHS)

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Kernel LMS-Based Estimation Techniques for Radar Systems

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Keywords

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