Development of an AOA location method using covariance estimation

  • Authors:
  • Dong-Hyouk Kim;Sung-Ho Lee;Kyung-Sun Park;Tae-Kyung Sung

  • Affiliations:
  • Chungnam National Univ., Yuseong-gu, Daejeon Korea;Chungnam National Univ., Yuseong-gu, Daejeon Korea;Chungnam National Univ., Yuseong-gu, Daejeon Korea;Chungnam National Univ., Yuseong-gu, Daejeon Korea

  • Venue:
  • AsiaCSN '07 Proceedings of the Fourth IASTED Asian Conference on Communication Systems and Networks
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.