The Application of Conditional Beta Density Functions to Model Time- Delay Measurement Errors

Abstract

A conditional beta probability density function is employed to model time-delay measurement errors associated with sensors used in triangulation ranging applications. This type of density function is less restrictive than the beta density used in previous analyses in that end points can be extended out beyond the imposed range constraints and data editing is allowed before range calculations. The resulting conditional range density function is computed along with the mean and variance. Comparisons are made of the pertinent range statistics associated with the beta and conditional beta density functions. Finally, the conditional beta density function range statistics are compared with those obtained from a gated Gaussian density function for equivalent values of time-delay measurement error standard deviation. The Gaussian statistics are determined via Monte-Carlo simulation.