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Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm(WLUKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the constant modulus criterion and takes full advantage of the noncircular property of the signal of interest(SOI), significantly increasing the output signal-tointerference-plus-noise ratio(SINR), enhancing the convergence speed and decreasing the steady-state misadjustment. Since it requires no known training data, the proposed algorithm saves a large amount of the available spectrum. Theoretical analysis and simulation results are presented to demonstrate its superiority over the conventional linear least mean square-based CMA(LLMS-CMA), the conventional linear recursive least square-based CMA(L-RLS-CMA), WL-LMS-CMA, WL-RLS-CMA and L-UKFCMA.
Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WLUKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the constant modulus criterion and takes full advantage of the non-circular property of the signal of interest (SOI), significantly increasing the output signal-to-interference-plus-noise ratio (SINR), enhancing the convergence speed and decreasing the steady-state misadjustment. Since it requires no known training data, the proposed algorithm saves a Theoretical analysis and simulation results are presented to demonstrate its superiority over the conventional linear least mean square-based CMA (LLMS-CMA), the conventional linear recursive least square-based CMA (L-RLS- CMA) , WL-LMS-CMA, WL-RLS-CMA and L-UKFCMA.