Performance of RBF neural networks for array processing in impulsive noise environment
Digital Signal Processing
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We develop an new adaptive beamforming technique based on fractional lower-order moment theory. The proposed adaptive beamformer adjusts the array response to a desired signal while discriminating against impulsive interference modeled as a stable process. Simulation results show that the new technique performs better in localizing a target both in space and Doppler, and thus offers the potential for improved airborne radar performance in space-time adaptive processing (STAP) applications.