Robust constrained CMA based on quadratic constraint

In practical applications, mismatches between assumed and actual array responses lead to serious degradation of SINR at the array output. In this paper, we propose robust CMA based on the quadratic constraint, which improves the output performance. The quadratic constraint on the weight can provide excellent robustness to signal steering vector mismatches and to random perturbations in sensor parameters. The Lagrange multipliers are updated and added at each step. The proposed algorithm offers faster rate, has better interference suppression and yields higher SINR. Simulation results show that the proposed algorithm achieves a substantially improved performance as compared to the constrained CMA.