Robust decentralized direction-of-arrival estimation in the presence of outlier contaminated noise

A novel scheme for direction-of-arrival estimation is presented. In particular, the authors develop a procedure that provides estimates that are robust against outliers and distributional uncertainties. It also employs decentralized processing such that each subarray provides a set of robust estimates of the directions-of-arrival accompanied by some confidence measures of the estimates. At the fusion center, a robust combination technique is used to combine estimates from each subarray site. Simulation results are presented to illustrate the robust properties achievable with the scheme relative to a similar nonrobust approach