An Improved CE-ML Algorithm of 2-D DOA Estimator
Xiaozhong Liu · Electronic Information Warfare Technology · 2011
The array DOA estimator method of maximum likelihood(ML) has high precision and can resolve the coherent signal.The application of maximum likelihood has been restricted by the computation burden.In order to overcome the problem existing in the majority of solution of maximum likelihood estimation,the cross entropy(CE) method is used.Through the optimization of the smooth parameter and the initial sample,a new improved CE-ML algorithm of 2-D DOA estimator is proposed.Comparing with the PSO(Particle Swarm Optimization) algorithm,simulation results show that the improved CE-ML algorithm performs better,and iteration number of CE-ML algorithm is one-third of PSO algorithm.