Narrowband Direction Finding Using complex EKF Trained Multilayered Neural Networks

摘要

A technique using multilayered neural network has been developed for narrowband direction finding problem that involves in array processing of non-Gaussian signals. Complex extended Kalman filtering algorithm is derived for training the networks with complex input signals. Two networks were implemented, one with the third order cumulants and the other with the traditional correlations of received signal vector evaluated at different combinations of direction of arrivals(DOA's) as training inputs. Simulation results show that the network trained with cumulants outperforms the network trained with the correlations.