Array calibration by Fourier series parameterization: scaled principal components method
- 1 January 1993
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 4, 340-343 vol.4
- https://doi.org/10.1109/icassp.1993.319664
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.Keywords
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