复合高斯杂波中MIMO雷达DOA估计的克拉美-罗下限

王鞠庭; 江胜利; 刘中

doi:10.3724/SP.J.1146.2007.01984

复合高斯杂波中MIMO雷达DOA估计的克拉美-罗下限

doi: 10.3724/SP.J.1146.2007.01984

计量
- 文章访问数: 3427
- HTML全文浏览量: 97
- PDF下载量: 776
- 被引次数: 0
出版历程
- 收稿日期: 2007-12-28
- 修回日期: 2008-05-20
- 刊出日期: 2009-04-19

Cramer-Rao Bounds of DOA Estimation for MIMO Radars in Compound-Gaussian Clutter

摘要

摘要: 该文研究了复合高斯杂波下MIMO雷达DOA估计的平均克拉美-罗下限(Average CRB, ACRB)。首先，给出了MIMO雷达信号与杂波模型；然后，推导出目标DOA估计ACRB的一般关系式，在此基础上给出当杂波texture分量满足反Gamma分布时，ACRB的闭合表达式；接着，研究了目标DOA估计的中断CRB(Outage CRB)，克服了一个发射单元时ACRB发散的问题；最后进行计算机仿真并给出结论。结果表明MIMO雷达的空间分集能有效地降低其DOA估计ACRB，且ACRB随发射单元数量的提高而减小；另外在相同条件下，MIMO雷达在复合高斯背景下DOA估计的ACRB大于相应高斯背景下的ACRB。
- MIMO雷达;复合高斯杂波;DOA估计;平均克拉美-罗下限
Abstract: This paper studies the Average Cramer-Rao Bounds (ACRB) for estimating Direction Of Arrival (DOA) in compound-Gaussian clutter using Multi-Input Multi-Output (MIMO) radars. Firstly, the MIMO radar signal and compound-Gaussian clutter models are introduced. Secondly, the general ACRB expression is derived. Then, a closed-form ACRB is given for the inverse-Gamma distributed texture component. Thirdly, the Outage CRB is introduced as a supplement to the divergence of ACRB when there is only one transmit radar element. Finally, the DOA estimation performances of MIMO radars are simulated through computer simulations under different conditions. Theoretical analyses and computer simulations show that the spatial diversity of MIMO radar can improve the performance of DOA estimation effectively. The ACRB decreases as the number of the transmit radar elements increases. It is also found that the ACRB in compound-Gaussian clutter is inferior to that in Gaussian clutter. The research conducted in this paper reveals the fundamental performances of the MIMO radars.

HTML全文

参考文献(1)

Bekkerman I and Tabrikian J. Target detection andlocalization using MIMO radars and sonars [J].IEEE Trans.on SP.2006, 54(10):3873-3883[2]Li J and Stoica P. MIMO radar with colocated antennasIEEE SP Mag. [J]. 2007, 25(1): 106-114.[3]Fishler E, Haimovich A, and Blum R, et al.. MIMO radar: Anidea whose time has come[C]. Proc. IEEE Radar Conf.,Philadelphia, United States, Apr. 2004: 71-78.[4]Fishler E, Haimovich A, and Blum R, et al.. Spatial diversityin radars-Models and detection performance[J].IEEE Trans.on SP.2006, 54(3):823-838[5]Haimovich A M, Blum R S, and Cimini L J. MIMO radarwith widely separated antennas[J]. IEEE SP Mag., 2008,25(1): 116-129.[6]Sammartino P F, Baker C J, and Griffiths H D. Target modeleffects on MIMO radar performance[C]. Conference records ofICASSP 2006, Toulouse, France, May 2006: 14-19.[7]Sammartino P F, Baker C J, and Griffiths H D. MIMO radarperformance in clutter environment[C]. Proc. IEEE RadarConf., Shanghai, China, Oct. 2006: 16-19.[8]Sammartino P F, Baker C J, and Griffiths. H D. AdaptiveMIMO radar system in clutter [C]. Proc. IEEE Radar Conf.,Waltham, United States, Apr. 2007: 276-281.[9]Lehmann N H, Fishler E, and Haimovich A M, et al..Evaluation of transmit diversity in MIMO-radar directionfinding [J].IEEE Trans. on SP.2007, 55(5):2215-2225[10]Wang J, Dogandzic A, and Nehorai A. Maximum likelihoodestimation of compound-gaussian clutter and targetparameters [J].IEEE Trans. on SP.2006, 54(10):3884-3898[11]Balleri A, Nehorai A, and Wang J. Maximum likelihoodestimation for compound-gaussian clutter with inversegamma texture [J]. IEEE Trans. on AES, 2007, 43(2):775-779.[12]Gini F, Montanari M, and Verrazzani L. Estimation of chirpradar signals in compound-gaussian clutter: A cyclostationaryapproach [J].IEEE Trans. on SP.2000, 48(4):1029-1039[13]Gini F and Reggiannini R. On the use of cramer-rao-likebounds in the presence of random nuisance parameters[J].IEEE Trans. on Comm.2000, 48(12):2120-2126[14]Kay S M. Fundamentals of Statistical Signal Processing:Estimation Theory. Englewood Cliffs, NJ: Prentice-Hall,1993, Chapter 15.

施引文献

资源附件(0)

访问统计