Abstract
AbstractIn this paper, we propose a method to enhance the maximum spectral peaks of signal components corrupted by noise for one‐ and two‐dimensional (1‐D and 2‐D) signals under the condition that no a priori information is given. This method does not use a conventional filter where the passband is one and the stopband is zero but uses a filter where the spectral characteristics of the signal to be extracted from the input signal are the desired characteristics; that is, the filter is dependent on the input signal. For 1‐D signals, we demonstrate that the signal components can be satisfactorily enhanced by iterative processing using the fast Fourier transform (FFT) given an “autoregressive (AR signal + white noise signal” and a “harmonic signal + white noise signal.” For 2‐D signals, the amount of computation is decreased significantly and good spectral enhancement is possible compared to conventional methods. Furthermore, the possible application of this method to the design of narrowband plane wave detection filters, which are difficult to design using conventional methods, is presented.
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