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Joint optimization of MIMO radar waveform and biased estimator with prior information in the presence of clutter

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Author(s): Wang Hongyan | Liao Guisheng | Liu Hongwei | Li Jun | Lv Hui

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2011;
Issue: 1;
Start page: 15;
Date: 2011;
Original page

Keywords: Multi-input multi-output (MIMO) radar | waveform optimization | clutter | constrained biased Cramer-Rao bound (CRB) | Semidefinite programming (SDP)

ABSTRACT
Abstract In this article, we consider the problem of joint optimization of multi-input multi-output (MIMO) radar waveform and biased estimator with prior information on targets of interest in the presence of signal-dependent noise. A novel constrained biased Cramer-Rao bound (CRB) based method is proposed to optimize the waveform covariance matrix (WCM) and biased estimator such that the performance of parameter estimation can be improved. Under a simplifying assumption, the resultant nonlinear optimization problem is solved resorting to a convex relaxation that belongs to the semidefinite programming (SDP) class. An optimal solution of 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.
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