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The Journal of Supercomputing
Published in: The Journal of Supercomputing 5/2019

16-10-2018

OFDM waveform design based on mutual information for cognitive radar applications

Authors: Vahid Karimi, Reza Mohseni, Sadegh Samadi

Published in: The Journal of Supercomputing | Issue 5/2019

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Abstract

We propose a novel optimization method based on wideband orthogonal frequency division multiplexing (OFDM) signals to detect random extended targets with known covariance matrix in the presence of additive white Gaussian noise. Mutual information is used as our criterion for waveform design under transmitted power constraint. We utilize the advantage of OFDM signal to intelligently design the complex weights of the transmitted waveform. For making complete use of the transmission power, a novel iterative algorithm is introduced based on maximizing mutual information criterion between the target impulse response and the received echoes. We have derived the optimal Neyman–Pearson detector for the corresponding hypothesis testing problem and provided different numerical experiments to demonstrate the achieved performance improvement when the proposed method is applied.
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Appendix
Available only for authorised users
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Metadata
Title
OFDM waveform design based on mutual information for cognitive radar applications
Authors
Vahid Karimi
Reza Mohseni
Sadegh Samadi
Publication date
16-10-2018
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 5/2019
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2648-3

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