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Volume 31 Issue 4
Dec.  2010
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Hongyan LUO, Ziyan ZHU, Rui LIN, Zhen LIN, Yanjian LIAO. Improved No-reference Noisy Image Quality Assessment Based on Masking Effect and Gradient Information[J]. Journal of Electronics & Information Technology, 2019, 41(1): 210-218. doi: 10.11999/JEIT180195
Citation: Wang Ju-ting, Jiang Sheng-li, Liu Zhong. Cramer-Rao Bounds of DOA Estimation for MIMO Radars in Compound-Gaussian Clutter[J]. Journal of Electronics & Information Technology, 2009, 31(4): 786-789. doi: 10.3724/SP.J.1146.2007.01984

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

doi: 10.3724/SP.J.1146.2007.01984
  • Received Date: 2007-12-28
  • Rev Recd Date: 2008-05-20
  • Publish Date: 2009-04-19
  • 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.
  • 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.
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