Array Shape Self-Calibration Using Subspace Fitting Methods

Document Type : Original Article

Authors

1 shiraz university

2 Shiraz University

Abstract

Estimating the direction of arrival and beamforming are among the most important issues in array signal processing for which a variety of methods have been proposed. With few exceptions, these methods require an exact knowledge of array response including the knowledge of sensors’ positions, sensors’ gain/phase responses and mutual coupling coefficients between sensors. There are uncertainties about these array response parameters as we usually have their nominal values which are different from the actual metrics. The performance of DOA estimation and beamforming algorithms degrade severely because of these uncertainties. To solve this problem and reduce the performance degradation, it is necessary to estimate these unknown parameters. In this paper, we use simulations to study and compare the performance of several so-called self-calibration methods in the presence of array shape error. However, before performance investigation, it is attempted to improve the performance of these methods by manipulating their structure. In addition, in this paper, a self-calibration method based on the gradient search is proposed. Various simulations are used to evaluate the performance of this method and compare it with other self-calibration methods.

Keywords


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F. Eskandari, “Array Shape Self-calibration Using Subspace Fitting Methods,” M.Sc Thesis, School of Electrical and Computer Shiraz University.(In Persian)
  • Receive Date: 15 September 2018
  • Revise Date: 01 March 2019
  • Accept Date: 16 April 2019
  • Publish Date: 07 October 2019