Wavelet beamspace STAP for uniform linear arrays

Space time adaptive processing is implemented in this paper in beamspace using a wavelet based transformation. We show that given a fixed number of beamspace elements, wavelet based STAP outperforms that of DFT based STAP, or sinusoidal tapers based STAP. Wavelet based decomposition divides the uniformly sampled element-space array into nonuniform dyadically distributed orthogonal beamspace elements. Adaptive processing in the wavelet domain improves signal-to-interference plus noise ratio depending on the type of wavelet used.