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

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
• Public URL: https://durham-repository.worktribe.com/output/1341569