Fuzzy inference based wavelet robust sidelobe canceller

Adaptive Antenna (Smart Antenna) is one of the challenging techniques used to improve the antenna performance. Constrained Least Mean Square (CLMS) algorithms (e.g. sidelobe canceller) are one of the categories used to adapt the antenna weights. CLMS in its simple form fails to capture the Signal Of Interest (SOI) if there is an error in the Direction Of Arrival (DOA) estimation. Moreover it will consider the SOI as an interferer and create null in the desired direction of the SOI. The large gain will be toward the wrong detected direction. Wavelet based sidelobe canceller employs the wavelet properties to build robust beamformer and also contribute in decreasing the computational complexity. Fuzzy inference rules also can be used to build robust beamformer with good behavior in the uncertainty range. The proposed algorithm in this paper mixes the wavelet based and Fuzzy inference based sidelobe canceller to get more robustness and higher Signal to Interference and Noise Ratio (SINR).