Iterative Self-Calibration Algorithm for Near-Field Source Localization

In this paper, we consider the near field source location problem for a nonuniform sparse linear array (non-USA) in the presence of sensor gain and phase errors. We present a minimum variance based iterative self-calibration method to simultaneously estimate the gain and phase error parameters as well as the calibration sources locations including ranges and azimuthes exploiting some imprecise a-priori knowledge of calibration sources. The source locations and the gain/phase errors are obtained iteratively with known range or azimuth, and continue the procedure until they are converged. Finally, at the analysis stage, we evaluate the effectiveness of the proposed technique using some numerical simulations.