Asymptotically Minimum Variance Second-Order Estimation for Noncircular Signals with Application to DOA Estimation

Jean-Pierre Delmas (1, 2)

1 TSP - CITI - Communications, Images et Traitement de l'Information
2 TIPIC-SAMOVAR - Traitement de l'Information Pour Images et Communications

This paper addresses asymptotically minimum variance (AMV) algorithms within the class of algorithms based on second-order statistics for estimating direction-of-arrival (DOA) parameters of possibly spatially correlated (even coherent) narrowband noncircular sources impinging on arbitrary array structures. To reduce the computational complexity due to the nonlinear minimization required by the matching approach, the covariance matching estimation technique (COMET) is included in the algorithm. Numerical examples illustrate the performance of the AMV algorithm

Mots clés: second-order statistics-based algorithms; DOA estimation; complex non-circular; asymptotically minimum variance

Domaines: Traitement du signal et de l'image [eess.SP]; Statistiques [math.ST]; Théorie [stat.TH]

Jean-Pierre Delmas. Asymptotically Minimum Variance Second-Order Estimation for Noncircular Signals with Application to DOA Estimation. IEEE Transactions on Signal Processing, 2004, 52 (5), pp.1235-1241. ⟨10.1109/TSP.2004.826170⟩. ⟨hal-03399889⟩