Direction finding with a uniform circular array via single snapshot processing


Koc A., Tanik Y.

SIGNAL PROCESSING, cilt.56, sa.1, ss.17-31, 1997 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 56 Sayı: 1
  • Basım Tarihi: 1997
  • Doi Numarası: 10.1016/s0165-1684(96)00147-8
  • Dergi Adı: SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.17-31
  • Anahtar Kelimeler: direction finding, circular array, single snapshot, linear prediction, MAXIMUM-LIKELIHOOD, PARAMETER-ESTIMATION, FREQUENCY ESTIMATION, LINEAR PREDICTION, SPECTRAL-ANALYSIS, EM ALGORITHM, SIGNALS
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

In this work a new algorithm for multiple emitter direction finding by using a uniform circular array is proposed. The algorithm is based on single snapshot processing, and therefore, it has no restriction on the coherency of the sources. The problem formulation is based on the transformation of the snapshot. The transformed sequence is formed by taking the discrete Fourier transform of the snapshot and weighting it suitably. It contains the so-called distortion terms, which are taken into account by using an iterative correction scheme to improve the estimation accuracy. The convergence is achieved in a few steps, and a significant performance improvement is observed when the distortion terms are taken into account. The proposed bearing estimation algorithm is based on the linear prediction method developed in this study, in which the prediction filter coefficients are found by replacing the weighted data matrix by a specified rank approximation, which is obtained by its singular-value decomposition. The direction of arrival estimates are obtained from the angular locations of the prediction-error filter zeros. It is observed through computer simulations that the algorithm performance is improved as compared to that of the forward-backward linear prediction (FBLP) and the modified FBLP methods by choosing an appropriate rank for the approximating matrix. The root-mean-square errors are close to the Cramer-Rao bounds in most cases, where the aforementioned methods fail to work. (C) 1997 Elsevier Science B.V.