A neural structure for direction finding with sensor array uncertainties
The authors present an auto-calibration technique to estimate the directions-of-arrival (DOAs) of unknown signals in the presence of sensor gain and phase errors. Compared with other autocalibration algorithms, this algorithm is computationally more efficient and has a unique solution for a linear array with the imposed constraints. Furthermore, the complex computation in the objective likelihood gradients is performed by neural networks. An analog scheme encompassing neural networks has been proposed for the algorithm's implementation.<<ETX>>