Application of the Levenberg-Marquardt Scheme to the MUSIC Algorithm for AOA Estimation | Zendy

JoonHo Lee | Zendy; SungWoo Cho | Zendy; SoHee Jeong | Zendy

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Application of the Levenberg-Marquardt Scheme to the MUSIC Algorithm for AOA Estimation

Author(s) -

JoonHo Lee,

SungWoo Cho,

SoHee Jeong

Publication year - 2013

Publication title -

international journal of antennas and propagation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.282

H-Index - 37

eISSN - 1687-5877

pISSN - 1687-5869

DOI - 10.1155/2013/402842

Subject(s) - levenberg–marquardt algorithm , algorithm , capon , azimuth , convergence (economics) , computer science , multiple signal classification , monte carlo method , function (biology) , signal (programming language) , mathematics , artificial intelligence , artificial neural network , telecommunications , statistics , beamforming , geometry , antenna (radio) , economics , programming language , economic growth , evolutionary biology , biology

We note that the cost function of the MUSIC (multiple signal classification) algorithm is quadratic in an array vector and that itcan be expressed in a least squares form. Based on this observation, we present a rigorous Levenberg-Marquardt (LM) formulation of the MUSIC algorithm for simultaneous estimation of an azimuth and an elevation. We show a convergence property and compare the performance of the LM-based MUSIC algorithm with that of the standard MUSIC algorithm via Monte-Carlo simulation. We also compare the performance of the MUSIC algorithm with that of the Capon algorithm both for the standard implementation and for the LM-based implementation

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