Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter

Hongyan WANG; Guisheng LIAO; Jun LI; Liangbing HU; Wangmei GUO

doi:10.1587/transcom.E95.B.2087

Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter

Hongyan WANG, Guisheng LIAO, Jun LI, Liangbing HU, Wangmei GUO

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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.

Publication: IEICE TRANSACTIONS on Communications Vol.E95-B No.6 pp.2087-2094

Publication Date: 2012/06/01

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Online ISSN: 1745-1345

DOI: 10.1587/transcom.E95.B.2087

Type of Manuscript: PAPER

Category: Sensing

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Hongyan WANG, Guisheng LIAO, Jun LI, Liangbing HU, Wangmei GUO, "Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter" in IEICE TRANSACTIONS on Communications, vol. E95-B, no. 6, pp. 2087-2094, June 2012, doi: 10.1587/transcom.E95.B.2087.
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.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E95.B.2087/_p

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@ARTICLE{e95-b_6_2087,
author={Hongyan WANG, Guisheng LIAO, Jun LI, Liangbing HU, Wangmei GUO, },
journal={IEICE TRANSACTIONS on Communications},
title={Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter},
year={2012},
volume={E95-B},
number={6},
pages={2087-2094},
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.},
keywords={},
doi={10.1587/transcom.E95.B.2087},
ISSN={1745-1345},
month={June},}

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TY - JOUR
TI - Waveform Optimization for MIMO Radar Based on Cramer-Rao Bound in the Presence of Clutter
T2 - IEICE TRANSACTIONS on Communications
SP - 2087
EP - 2094
AU - Hongyan WANG
AU - Guisheng LIAO
AU - Jun LI
AU - Liangbing HU
AU - Wangmei GUO
PY - 2012
DO - 10.1587/transcom.E95.B.2087
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E95-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2012
AB - 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.
ER -