Title :
Hybrid Cramér-Rao bound for joint estimation of target and ionospheric parameters using MIMO-OTH radar
Author :
Mao Li ; Qian He ; Zishu He ; Blum, Rick S.
Author_Institution :
EE Dept., Univ. of Electron. Sci. & Tech. of China, Chengdu, China
Abstract :
Exploiting the received signals, which are usually not employed in the traditional OTH radar for ionospheric parameter estimation, we study joint estimation of target and ionospheric parameters for multiple-input multiple-output skywave OTH (MIMO-OTH) radar. We employ a parabolic layer model to characterize the ionospheric distortions. We model the target and ionospheric parameters as deterministic and random unknowns, respectively, and carry out the joint estimation using a hybrid maximum likelihood and maximum a posterior (ML/MAP) method. The corresponding hybrid Cramér-Rao bound (HCRB) is derived. We show that the proposed joint estimation approach leads to an improved accuracy for the target and ionospheric parameter estimation compared with the traditional methods.
Keywords :
MIMO radar; maximum likelihood estimation; parameter estimation; HCRB; MIMO-OTH radar; ML-MAP method; deterministic unknowns; hybrid Cramér-Rao bound; hybrid maximum likelihood method; ionospheric distortions; ionospheric parameter estimation; joint estimation approach; maximum a posterior method; multiple-input multiple-output skywave OTH radar; parabolic layer model; random unknowns; target parameter estimation; Joints; MIMO; Manganese; Maximum likelihood estimation; Radar; Signal to noise ratio; Hybrid Cramér-Rao bound; MIMO-OTH radar; hybrid ML/MAP estimation; joint estimation;
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
Conference_Location :
Beijing
DOI :
10.1109/ChinaSIP.2013.6625286