کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
564417 875598 2010 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
DOA estimator performance assessment in the pre-asymptotic domain using the likelihood principle
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
DOA estimator performance assessment in the pre-asymptotic domain using the likelihood principle
چکیده انگلیسی

Performance assessment of algorithms for direction of arrival (DOA) estimation are typically done using large-sample justified asymptotic constructs such as consistency, efficiency, and the Cramér–Rao lower bound. The performance in parameter accuracy (usually the mean square error of the DOA estimate) of the algorithm relative to the true parameters of the sources is evaluated to determine if the algorithm is accurate, robust, computationally efficient, etc. However, performance assessment of the algorithm in practical circumstances with limited data sample volume cannot use these methods, because asymptotic statistical behavior is no longer met and the true location of the sources is in general unknown. This paper reviews the application of an performance assessment technique referred to as expected likelihood in such practical small-sample circumstances, and provides simulation and real-world examples of the capabilities provided by expected likelihood which does not rely on knowledge of the true source locations. Uses of the approach in other areas such aiding of numerical optimization, model order determination, and determination of appropriate diagonal loading in LSMI applications is also reviewed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 90, Issue 5, May 2010, Pages 1392–1401
نویسندگان
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