کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1760054 1019318 2008 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Normalized split-spectrum: A detection approach
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم آکوستیک و فرا صوت
پیش نمایش صفحه اول مقاله
Normalized split-spectrum: A detection approach
چکیده انگلیسی

We consider in this paper the problem of automatic detection of ultrasonic echo pulses in a grain noise background. We start by assuming a reference model for grain noise: multivariate correlated Gaussian model having, in general, different variances under every hypothesis. We show that, even for this simple model, there is not practical optimum solution, except if the variances are equal under every hypothesis and the echo pulse satisfies a spectral constraint. Then we consider split-spectrum (SS) suboptimum solutions. Firstly, SS algorithms are formulated following an algebraic approach which is appropriate in an automatic detection framework. Popular minimization and polarity thresholding algorithms are considered under this framework. Then a new detector called normalized SS (NSS) is proposed. The underlying idea is to actually exploit the tuning frequency sensitivity (i.e., variability of the output magnitudes from one SS channel to another), making this measurement independent of the absolute magnitudes. Different experiments with simulated and real data show evidences of the interest of the new method in an automatic detection framework. Derivations of the formulas for fitting the probability of false alarm in every detector are included in the paper.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ultrasonics - Volume 48, Issue 1, March 2008, Pages 56–65
نویسندگان
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