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• W2080774883 endingPage "2094" @default.
• W2080774883 startingPage "2087" @default.
• W2080774883 abstract "In this paper, we consider the problem of waveform optimization for multi-input multi-output (MIMO) radar in the presence of signal-dependent noise. A novel diagonal loading (DL) based method is proposed to optimize the waveform covariance matrix (WCM) for minimizing the Cramer-Rao bound (CRB) which improves the performance of parameter estimation. The resulting nonlinear optimization problem is solved by resorting to a convex relaxation that belongs to the semidefinite programming (SDP) class. An optimal solution to the initial problem is then constructed through a suitable approximation to an optimal solution of the relaxed one (in a least squares (LS) sense). Numerical results show that the performance of parameter estimation can be improved considerably by the proposed method compared to uncorrelated waveforms." @default.
• W2080774883 created "2016-06-24" @default.
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• W2080774883 date "2012-01-01" @default.
• W2080774883 modified "2023-10-18" @default.
• W2080774883 title "Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter" @default.
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• W2080774883 doi "https://doi.org/10.1587/transcom.e95.b.2087" @default.
• W2080774883 hasPublicationYear "2012" @default.
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