DOA estimation method based on sparse representation and constrained optimization
Meng Cai-yun · Journal of Computer Applications · 2012
For Direction-Of-Arrival(DOA) estimation of signal in additive noise,the traditional Multiple Signal Classification(MUSIC) algorithm cannot process the coherent signal with fewer snapshots.The searching scope of estimated DOA was considered as redundant dictionary.Consequently,the estimated DOA was taken as some elements in the dictionary,and could be represented sparsely by the dictionary.Then,this problem was thrown into the Second Order Cone(SOC) constraints and an efficient estimation algorithm using a single snapshot was developed.This constrained problem could be depicted as a standard SOC form and be solved by the SeDuMi,an optimization toolbox.The simulation results show that the proposed algorithm has a few advantages over the existing subspace method including one single snapshot to be needed,no requirement for the number of source signals,ability to work with coherent and non-coherent signals.