Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
447617 | AEU - International Journal of Electronics and Communications | 2006 | 11 Pages |
Abstract
This paper proposes a large-sample approximation of the maximum-likelihood estimator for direction finding in the presence of a spatially spread source. The key idea is to replace the parametric estimate of the four-dimensional nuisance parameter vector with the approximate one that depends on just one parameter of interest, called the nominal angle, thus permitting the use of one-dimensional optimization techniques. The proposed estimator is shown to be strongly consistent and asymptotically efficient, and the Cramér–Rao bound on its standard deviation is derived. Simulations show the estimator to outperform previously proposed estimators, such as the subspace-based estimator and others based on one-dimensional search.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Bamrung Tau Sieskul, Somchai Jitapunkul,