Adaptive array antenna system extracts the target signal from received signals by adaptive signal processing technique, especially the spatiotemporal adaptive array are attracted due to their effectiveness for the phasing problems. The spatiotemporal array construction requires lots of weight parameters to be adaptively controlled, which causes the problem of the large computational cost. To reduce such computational cost, the received signals are first transformed into frequency subband components, and then they are adaptively processed in paralell. Frequency subband decomposition can reduce the computational cost. On the other hand, some adaptive algorithms are recently proposed that can realize fast convergence while preserving low computational cost. It means that the computational cost in FFT and IFFT used for spatiotemporal transformation cannot be ignored. In this report, we employ the wavelet transformation instead of FFT and IFFT for spatiotemporal transformation, and confirm if the wavelet transformation can reduce the computational cost or can improve the convergence property. We develop a spatiotemporal adaptive array antenna system with filterbanks, which implement Haar or Daubechies wavelet decomposition and reconstruction.
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