Range compression and waveform optimization for MIMO radar: a Cramer-Rao bound based study

被引：254

作者：

Li, Jian ^{[1
]}

Xu, Luzhou ^{[1
]}

Stoica, Petre ^{[2
]}

Forsythe, Keith W. ^{[3
]}

Bliss, Daniel W. ^{[3
]}

机构：

[1] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA

[2] Uppsala Univ, Dept Informat Technol, SE-75105 Uppsala, Sweden

[3] MIT, Lincoln Lab, Lexington, MA 02420 USA

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2008年 / 56卷 / 01期

关键词：

Cramer-Rao bound (CRB); MIMO radar; space-time adaptive processing (STAP); waveform optimization;

D O I：

10.1109/TSP.2007.901653

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 Cramer-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.

引用

页码：218 / 232

页数：15

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