Minimax Robust MIMO Radar Waveform Design

• Published in: IEEE journal of selected topics in signal processing Vol. 1; no. 1; pp. 147 - 155
• Main Authors: Yang Yang, Blum, R.S.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2007; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Character recognition; Criteria; Density; Extended radar targets; Information theory; MIMO; Minimax technique; Minimax techniques; minimum mean-square error (MMSE); multiple-input multiple-output (MIMO) radar; Mutual information; mutual information (MI); Radar; Radar signal processing; Radar theory; Radar tracking; radar waveform design; robust signal processing; Robustness; Signal design; Spectra; target classification and identification; Uncertainty; Waveforms
• ISSN: 1932-4553; 1941-0484
• DOI: 10.1109/JSTSP.2007.897056

We consider the problem of minimax robust waveform design for multiple-input multiple-output (MIMO) radar based on mutual information (MI) and minimum mean-square error (MMSE) estimation for target identification and classification. Recognizing that a single, precise characterization of target power spectral density (PSD) is rare in practice, we assume the PSD lies in an uncertainty class of spectra bounded by known upper and lower bounds, which markedly relaxes the required target a priori knowledge. Based on this band model, we develop minimax robust waveforms for MIMO radar under both MMSE and MI criteria. These robust waveforms bound the worst-case performance at an acceptable limit, and also could insure performance will be sufficiently good for any PSD in the uncertainty class. Our findings also indicate that the MI and MMSE criteria lead to different minimax robust waveform solutions, which is in contrast to the case of the perfectly known target PSD