Minimax Robust MIMO Radar Waveform Design
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...
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| Published in | IEEE journal of selected topics in signal processing Vol. 1; no. 1; pp. 147 - 155 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.06.2007
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-4553 1941-0484 |
| DOI | 10.1109/JSTSP.2007.897056 |
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| Abstract | 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 |
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| AbstractList | 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 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. |
| Author | Blum, R.S. Yang Yang |
| Author_xml | – sequence: 1 surname: Yang Yang fullname: Yang Yang organization: Dept. of Electr. & Comput. Eng., Lehigh Univ., Bethlehem, PA – sequence: 2 givenname: R.S. surname: Blum fullname: Blum, R.S. organization: Dept. of Electr. & Comput. Eng., Lehigh Univ., Bethlehem, PA |
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| SubjectTerms | 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 |
| Title | Minimax Robust MIMO Radar Waveform Design |
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