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Power Minimization Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Shi, Chenguang; Wang, Fei; Sellathurai, Mathini; Zhou, Jianjiang; Salous, Sana

Power Minimization Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence Thumbnail


Authors

Chenguang Shi

Fei Wang

Mathini Sellathurai

Jianjiang Zhou



Abstract

This paper considers the problem of power minimization based robust orthogonal frequency division multiplexing (OFDM) radar waveform design, in which the radar coexists with a communication system in the same frequency band. Recognizing that the precise characteristics of target spectra are impossible to capture in practice, it is assumed that the target spectra lie in uncertainty sets bounded by known upper and lower bounds. Based on this uncertainty model, three different power minimization based robust radar waveform design criteria are proposed to minimize the worst-case radar transmitted power by optimizing the OFDM radar waveform, which are constrained by a specified mutual information (MI) requirement for target characterization and a minimum capacity threshold for communication system. These criteria differ in the way the communication signals scattered off the target are considered: (i) as useful energy, (ii) as interference or (iii) ignored altogether at the radar receiver. Numerical simulations demonstrate that the radar transmitted power can be efficiently reduced by exploiting the communication signals scattered off the target at the radar receiver. It is also shown that the robust waveforms bound the worst-case power-saving performance of radar system for any target spectra in the uncertainty sets.

Citation

Shi, C., Wang, F., Sellathurai, M., Zhou, J., & Salous, S. (2018). Power Minimization Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence. IEEE Transactions on Signal Processing, 66(5), 1316-1330. https://doi.org/10.1109/tsp.2017.2770086

Journal Article Type Article
Acceptance Date Oct 27, 2017
Online Publication Date Nov 3, 2017
Publication Date Mar 1, 2018
Deposit Date Oct 30, 2017
Publicly Available Date Oct 30, 2017
Journal IEEE Transactions on Signal Processing
Print ISSN 1053-587X
Electronic ISSN 1941-0476
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 66
Issue 5
Pages 1316-1330
DOI https://doi.org/10.1109/tsp.2017.2770086

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