A Hadamard Product Based Method for DOA Estimation and Gain-Phase Error Calibration

In the work presented here we consider the problem of direction of arrival (DOA) estimation and gain-phase errors calibration. We propose a new method which is based on the eigendecomposition of the Hadamard product of the covariance matrix and its conjugate. This method requires neither the presence of calibration sources nor previous calibration information as initialization. Moreover, it performs independent of the phase errors. Simulation results demonstrate the effectiveness of the proposed method.

[1]  Jungtai Kim,et al.  Blind Calibration for a Linear Array With Gain and Phase Error Using Independent Component Analysis , 2010, IEEE Antennas and Wireless Propagation Letters.

[2]  B. C. Ng,et al.  Sensor-array calibration using a maximum-likelihood approach , 1996 .

[3]  Jian Li,et al.  Extended derivations of MUSIC in the presence of steering vector errors , 2005, IEEE Transactions on Signal Processing.

[4]  Petre Stoica,et al.  MUSIC, maximum likelihood, and Cramer-Rao bound , 1989, IEEE Transactions on Acoustics, Speech, and Signal Processing.

[5]  Thomas Kailath,et al.  Direction of arrival estimation by eigenstructure methods with unknown sensor gain and phase , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  B. Friedlander,et al.  Eigenstructure methods for direction finding with sensor gain and phase uncertainties , 1990 .

[7]  Karl Gerlach,et al.  Robust DOA Estimation: The Reiterative Superresolution (RISR) Algorithm , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Petre Stoica,et al.  Mode, maximum likelihood and Cramer-Rao bound: conditional and unconditional results , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[9]  Anne Ferréol,et al.  Statistical Analysis of the MUSIC Algorithm in the Presence of Modeling Errors, Taking Into Account the Resolution Probability , 2010, IEEE Transactions on Signal Processing.

[10]  Xu Xu,et al.  DOA Estimation for Uniform Linear Array with Mutual Coupling , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[11]  M. Viberg,et al.  Two decades of array signal processing research: the parametric approach , 1996, IEEE Signal Process. Mag..

[12]  Petre Stoica,et al.  Maximum likelihood methods for direction-of-arrival estimation , 1990, IEEE Trans. Acoust. Speech Signal Process..

[13]  Chong Meng Samson See Method for array calibration in high-resolution sensor array processing , 1995 .

[14]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[15]  Bjorn Ottersten,et al.  Performance analysis of the total least squares ESPRIT algorithm , 1991, IEEE Trans. Signal Process..

[16]  Meng Hwa Er,et al.  A Practical Simple Geometry and Gain/Phase Calibration Technique for Antenna Array Processing , 2009, IEEE Transactions on Antennas and Propagation.

[17]  Guisheng Liao,et al.  An Eigenstructure Method for Estimating DOA and Sensor Gain-Phase Errors , 2011, IEEE Transactions on Signal Processing.

[18]  Petre Stoica,et al.  MUSIC, maximum likelihood, and Cramer-Rao bound: further results and comparisons , 1990, IEEE Trans. Acoust. Speech Signal Process..

[19]  M. H. Er,et al.  Theoretical analyses of gain and phase error calibration with optimal implementation for linear equispaced array , 2006, IEEE Transactions on Signal Processing.

[20]  A. Lee Swindlehurst,et al.  Analysis of the combined effects of finite samples and model errors on array processing performance , 1994, IEEE Trans. Signal Process..

[21]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .