STATISTICAL DESCRIPTION OF INTEGRATED SQUARED GAUSSIAN NOISE.
Abstract
In many practical problems one is concerned with the detection of random signals immersed in additive background noise. Often the signal is band-limited and then in some manner energy-detected, since this is the most direct means of obtaining the information which was sent. The Rayleigh amplitude probability density function describes the output amplitude statistics of a linear envelope detector when the input is a narrow band Gaussian noise. However, when the Gaussian process is passed through a nonlinear device and in turn filtered, the output amplitude probability density function is extremely difficult to specify analytically. In an attempt to solve this problem, Monte Carlo simulation techniques were evaluated while deriving the results of a particular problem. A digital computer was used to simulate the passage of white Gaussian noise through a narrow bandpass filter and in turn through a squarer and integrator. Careful step-by-step statistical estimates (i.e., amplitude probability density, autocorrelation, and power spectral density) of the function within the simulation are presented and compared with theoretical computations. The results presented are of the amplitude probability density, autocorrelation and power spectral density of the integrated squared filtered Gaussian noise.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1966
- Accession Number
- AD0803891
Entities
People
- Edward E. Cossette
Organizations
- Rome Laboratory