Initialization of Cost Function for ML-Based DOA Estimation 


Vol. 33,  No. 1, pp. 110-116, Jan.  2008


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  Abstract

Maximum likelihood (ML) diretion-of-arrival (DOA) estimation is essentially optimization of multivariable nonlinear cost function. Since the final estimate is highly dependent on the initial estimate, an initialization is critical in nonlinear optimization. We propose a multi-dimensional (M-D) search scheme of uniform exhaustive search and improved exhaustive search. Improved exhaustive search is superior to uniform exhaustive search in terms of the computational complexity and the accuracy of the estimates.

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  Cite this article

[IEEE Style]

S. Jo and J. Lee, "Initialization of Cost Function for ML-Based DOA Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 1, pp. 110-116, 2008. DOI: .

[ACM Style]

Sang-Ho Jo and Joon-Ho Lee. 2008. Initialization of Cost Function for ML-Based DOA Estimation. The Journal of Korean Institute of Communications and Information Sciences, 33, 1, (2008), 110-116. DOI: .

[KICS Style]

Sang-Ho Jo and Joon-Ho Lee, "Initialization of Cost Function for ML-Based DOA Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 1, pp. 110-116, 1. 2008.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880