Abstract:

A constrained constant modulus adaptive beamforming method based on cubature Kalman filter is proposed. Firstly, the state space model of the constrained constant modulus criterion is formulated with the pseudoobservation method. Then the cubature Kalman filter is utilized to solve the nonlinear filtering problem. This algorithm avoids the approximation procedure and the high eigenvalue spread effect which exists in conventional methods, and hence it exhibits better interference and noise suppression capacity. Simulation results demonstrate that the proposed method converges faster than both the 〖JP2〗stochastic gradient method and the recursive least square method and possesses higher output signaltointerferenceplusnoise ratio. Additionally, it can adjust its weight to the optimal result quickly under the non-stationary environment.