Statistical Theory of Signal Detection |
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antenna approximation arrival assumed autocovariance function average risk bandwidth Bayes criterion bias level carrier frequency coefficients complex autocovariance complex envelope components computed covariances decision surface defined detection probabilities detection system determined e-iwt eigenfunctions eigenvalues envelope V(t error false-alarm and detection false-alarm probability Qo filter matched formula Fourier transform frequency modulation given by eq H₁ hypothesis H impulse response input v(t integral equation joint p.d.f. kernel large number least favourable distribution likelihood ratio matched filter maximum maximum-likelihood estimate mean value measured method minimax narrow-band signals Neyman-Pearson criterion observation interval optimum P₁(x peak phase Po(x power spectrum prior p.d.f. prior probabilities probability density function probability of detection problem pulse quadratic detector quantity R₁ radar Section signal amplitudes signal s(t signal-to-noise ratio solution statistically independent stochastic process strategy t₁ target theory transfer function variance vectors white noise zero