Title :
Reconstruction of eigenvalues in noise subspace for uneuqual power sources DOA estimation
Author :
Qingyuan Fang ; Bingxia Cao ; Ming Jin ; Yong Han ; Xiaolin Qiao
Author_Institution :
Sch. of Electron. & Inf. Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
Conventional subspace-based methods for solving the narrow-band multiple sources location problems show high resolution, provided that the power of each source is identical. However this assumption may be not suitable for targets in electronic warfare. To deal with sources with unequal power, in this paper, we propose a method that reconstructs the eigenvalues of the noise subspace in covariance matrix to improve the resolution ability of the subspace-based method. The reconstruction of the eigenvalues in noise subspace has changed the proportion of the signal to noise in covariance matrix. Then, the signal ingredient existing in the noise subspace which is caused by finite snapshots is reduced by applying another eigenvalue decomposition (EVD) in the reconstructed covariance matrix. Simulation results indicate that our method has a better performance than MUSIC and subspace method developed by Ali Olfat et al, which prove the effectiveness of our method.
Keywords :
covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; electronic warfare; matrix decomposition; signal denoising; signal reconstruction; signal resolution; EVD reconstruction; covariance matrix; direction-of-arrival estimation; eigenvalue decomposition; electronic warfare; finite snapshot reduction; narrow band multiple source location; noise subspace; signal resolution; uneuqual power source DOA estimation; Covariance matrices; Direction-of-arrival estimation; Eigenvalues and eigenfunctions; Estimation; Multiple signal classification; Signal to noise ratio;
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
DOI :
10.1109/RADAR.2014.6875660