Sensor gain and phase estimation
Qi Cheng, Yingbo Hua · 2002
We present three algorithms for joint estimation of source angles and sensor gains and phases. These algorithms are based on the principles of weighted noise subspace fitting (WNSF), conditional maximum likelihood, and unconditional maximum likelihood. We study the statistical performances of the three algorithms assuming the source angles are known. The WNSF algorithm with an optimum weight is shown to be statistically the most efficient among the three and is implementable in an iterative quadratic fashion.