DOA Estimation with Nested Arrays in Impulsive Noise Scenario: An Adaptive Order Moment Strategy
Résumé
Most of the existing direction of arrival (DOA)estimation methods in impulsive noise scenario are based onthe fractional low-order moment statistics (FLOSs), such as therobust covariation-based (ROC), fractional low-order moment(FLOM), and phased fractional low-order moment (PFLOM).However, an unknown order moment parameter p needs tobe selected in these approaches, which inevitably increases thecomputational load if the optimal value of the parameter p isdetermined by a large number of Monte Carlo experiments.To address this issue, we propose the adaptive order momentfunction (AOMF) and improved AOMF (IAOMF), which areapplicable to the existing FLOSs-based methods and can also beextended to the case of sparse arrays. Moreover, we analyze theperformance of AOMF and IAOMF, and simulation experimentsverify the effectiveness of proposed methods.