Windowing Effects of Short Time Fourier Transform on Wideband Array Signal Processing Using Maximum Likelihood Estimation

نویسندگان

  • S. Gazor and A. M. Doosthoseini
  • S. Sadri
چکیده مقاله:

During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier transform together with ML, to estimate DOA's and the signals. The effect of window parameters (i.e, type, length and decimation factor) on the bias and variance of estimation of DOA's and signals is investigated. The algorithm robustness and convergence in presence of low SNR and coherent signals is illustrated. It is also shown that the local optimal problem encountered in the narrowband case is resolved for the wideband signals.

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windowing effects of short time fourier transform on wideband array signal processing using maximum likelihood estimation

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عنوان ژورنال

دوره 17  شماره 2

صفحات  29- 42

تاریخ انتشار 1998-04

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