Estimation of the number of sources via minimal redundancy fitting
Qing Xu · Journal of Xidian University · 2012
To alleviate the performance deterioration in the estimation of the number of sources with a low signal-to-noise ratio and/or secondary data deficient scenario,a new method based on the minimum redundancy fitting test is presented.The approach is performed in three stages.First,we employ a subspace tracking algorithm to calculate the one-dimensional noise subspace,and then a redundant array steer matrix is obtained based on the spatial spectrum which corresponds to the noise subspace.Redundant steer vectors are removed via minimum redundancy fitting and the number of sources is obtained.The effectiveness of the presented algorithm is verified by numerical simulation.