In the direction of arrival (DOA) estimation problem, we encounter both finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multiple signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expressions for the mean square error (MSE) in the DOA estimates. These expressions are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors. When they are further simplified for the case of finite data only and sensor errors only, they reduce to the recent results given previously (1989, 1991). Computer simulations are used to verify the closeness between the predicted and simulated values of the MSE.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Finite data performance of MUSIC and minimum norm methods


    Beteiligte:
    Srinivas, K.R. (Autor:in) / Reddy, V.U. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    1142358 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Finite Data Performance of MUSIC and Minimum Norm Methods

    Srinivas, K.R. | Online Contents | 1994


    Minimum Norm Differential Correction Algorithm

    Junkins, John L. / Kim, Youdan | AIAA | 1993



    Rotational Motion Control by Feedback with Minimum L1-Norm

    Majima, Minoru / Ichikawa, Akira | AIAA | 2009