Optimal and robust waveform design for MIMO radars in the presence of clutter

Naghibi, Tofigh; Namvar, Mehrzad; Behnia, Fereidoon

doi:10.1016/j.sigpro.2009.07.033

Cited by 38 publications

(60 citation statements)

References 26 publications

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“…which has the same form as Equation 3 shown in [19]. Therefore, according to Theorem 4 in [19], if R H t and R H c can be joint diagonalized, we can obtain…”

Section: Appendix Bmentioning

confidence: 89%

“…Multi-input multi-output (MIMO) radar has attracted more and more attention recently [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Unlike the traditional phased-array radar which can only transmit scaled versions of a single waveform, MIMO radar can use multiple transmitting elements to transmit arbitrary waveforms.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, MIMO radar with colocated antennas, the elements of which in transmitting and receiving arrays are close enough such that the target radar cross sections (RCS) observed by MIMO radar are identical, can be used to increase the spatial resolution. Accordingly, it has several advantages over its phased array counterpart, including improved parameter identifiability [4,5], and more flexibility for transmit beampattern design [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. In this article, we focus on MIMO radar with colocated antennas.…”

Section: Introductionmentioning

confidence: 99%

“…One of the most interesting research topics on both types of MIMO radar is the waveform optimization, which has been studied in [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. According to the target model used in the problem of waveform design, the current design methods can be divided into two categories: (1) point target-based design [6][7][8][9][10][11][12], and (2) extended target-based design [13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

“…According to the target model used in the problem of waveform design, the current design methods can be divided into two categories: (1) point target-based design [6][7][8][9][10][11][12], and (2) extended target-based design [13][14][15][16][17][18][19]. In the case of point targets, the corresponding methods optimize the waveform covariance matrix (WCM) [6][7][8] or the radar ambiguity function [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Wang

Liao

Liu

et al. 2011

EURASIP J. Adv. Signal Process.

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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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“…which has the same form as Equation 3 shown in [19]. Therefore, according to Theorem 4 in [19], if R H t and R H c can be joint diagonalized, we can obtain…”

Section: Appendix Bmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Wang

Liao

Liu

et al. 2011

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

show abstract

References

2012

Cognitive Radio Communications and Networking

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Robust Waveform Design for MIMO Radar with Imperfect Prior Knowledge

Wang

Pei

2015

Circuits Syst Signal Process

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Waveform optimization for multi-input multi-output radar usually depends on the initial parameter estimates (i.e., some prior information on the target of interest and scenario). However, it is sensitive to estimate errors and uncertainty in the parameters. Robust waveform design attempts to systematically alleviate the sensitivity by explicitly incorporating a parameter uncertainty model into the optimization problem. In this paper, we consider the robust waveform optimization to improve the worstcase performance of parameter estimation over a convex uncertainty model, which is based on the Cramer-Rao bound. An iterative algorithm is proposed to optimize the waveform covariance matrix such that the worst-case performance can be improved. Each iteration step in the proposed algorithm is solved by resorting to convex relaxation that belongs to the semidefinite programming class. Numerical results show that the worst-case performance can be improved considerably by the proposed method compared to that of uncorrelated waveforms and the non-robust method.

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Optimal and robust waveform design for MIMO radars in the presence of clutter

Cited by 38 publications

References 26 publications

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

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

References

Robust Waveform Design for MIMO Radar with Imperfect Prior Knowledge

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