TY - JOUR
T1 - Range compression and waveform optimization for MIMO radar
T2 - A Cramér-Rao bound based study
AU - Li, Jian
AU - Xu, Luzhou
AU - Stoica, Petre
AU - Forsythe, Keith W.
AU - Bliss, Daniel W.
N1 - Funding Information:
Manuscript received August 25, 2006; revised April 24, 2007. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Steven M. Kay. This work was supported in part by the Defense Advanced Research Projects Agency under Air Force Contract FA8721-05-C-0002 and under Grant HR0011-06-1-0031 and in part by the Office of Naval Research under Grant N000140710293. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government. J. Li performed part of this work while a Visiting Scientist at the MIT Lincoln Laboratory, Lexington, MA.
PY - 2008/1
Y1 - 2008/1
N2 - A multi-input multi-output (MIMO) radar system, unlike standard phased-array radar, can transmit via its antennas multiple probing signals that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar enables superior capabilities compared with a standard phased-array radar. One of the common practices in radar has been range compression. We first address the question of "to compress or not to compress" by considering both the Cramér-Rao bound (CRB) and the sufficient statistic for parameter estimation. Next, we consider MIMO radar waveform optimization for parameter estimation for the general case of multiple targets in the presence of spatially colored interference and noise. We optimize the probing signal vector of a MIMO radar system by considering several design criteria, including minimizing the trace, determinant, and the largest eigenvalue of the CRB matrix. We also consider waveform optimization by minimizing the CRB of one of the target angles only or one of the target amplitudes only. Numerical examples are provided to demonstrate the effectiveness of the approaches we consider herein.
AB - A multi-input multi-output (MIMO) radar system, unlike standard phased-array radar, can transmit via its antennas multiple probing signals that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar enables superior capabilities compared with a standard phased-array radar. One of the common practices in radar has been range compression. We first address the question of "to compress or not to compress" by considering both the Cramér-Rao bound (CRB) and the sufficient statistic for parameter estimation. Next, we consider MIMO radar waveform optimization for parameter estimation for the general case of multiple targets in the presence of spatially colored interference and noise. We optimize the probing signal vector of a MIMO radar system by considering several design criteria, including minimizing the trace, determinant, and the largest eigenvalue of the CRB matrix. We also consider waveform optimization by minimizing the CRB of one of the target angles only or one of the target amplitudes only. Numerical examples are provided to demonstrate the effectiveness of the approaches we consider herein.
KW - Cramér &-Rao bound (CRB)
KW - Cramér-Rao bound (CRB)
KW - MIMO radar
KW - Space-time adaptive processing (STAP)
KW - Waveform optimization
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U2 - 10.1109/TSP.2007.901653
DO - 10.1109/TSP.2007.901653
M3 - Article
AN - SCOPUS:37749028007
SN - 1053-587X
VL - 56
SP - 218
EP - 232
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 1
ER -