Array calibration by Fourier series parameterization: scaled principal components method

  • Authors:

  • M. A. Koerber;D. R. Fuhrmann

  • Affiliations:

  • Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA;Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA

  • Venue:
  • ICASSP '93 Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04
  • Year:
  • 1993

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Abstract

Based on a Fourier series model for an antenna array's response and a typical calibration procedure, a maximum likelihood (ML) solution for the array parameters can be derived. The authors review the Fourier series model of an array's response and introduce a suboptimum method of determining the model parameters. The performance of the suboptimal solution is significantly influenced by the scaling of the principal components (M.A. Koerber, 1992). A method of scaling based on a QR decomposition is presented. This method provides for approximately an order of magnitude reduction in error over previously reported scaling methods. This approach has the significant advantage of requiring no a priori knowledge of the array's response. Simulation results compare the use of QR decomposition based scaling with the ML solution.