1. A method of automatically establishing operational parameters of a surveillance system and monitoring a process, comprising the steps of: (a) using an automated system for acquiring time dependent data characteristic of a state of interest; (b) using an automated system for performing domain transformation on said time dependent data; (c) using an automated system for constructing a Fourier composite using identified Fourier modes, by iteratively finding the optimal number of modes that are furthest away from the median PSD; (d) using an automated system for filtering serial correlation from time dependent data; (e) using an automated system for performing at least one Gaussian test, at least one whiteness noise test and an autocorrelation test and repeating steps (c) and (d) until these tests are satisfied; (f) using an automated system for storing Fourier coefficients; (g) using an automated system for generating a Fourier composite from said Fourier coefficients; (h) using an automated system for adding pseudorandom noise to said Fourier composite; (i) using an automated system for generating observations of a synthesized signal for Monte Carlo simulation; (j) using an automated system for establishing SPRT missed alarm probabilities; (k) using an automated system for testing said SPRT probabilities with a synthesized signal; (l) using an automated system for evaluating empirically a false alarm rate and if less than desired target values, outputting said SPRT probabilities for use in performing surveillance by said system; (m) if said false alarm rate is greater than said target values, reducing said SPRT probabilities and repeating steps (j) and (k) until obtaining said false alarm rate less than said desired target value; and (n) upon establishing operational parameters in said steps (a)-(m) for the surveillance system, carrying out an automated sequential probability ratio test to monitor a process for alarm conditions.