Approximately optimum detection of deterministic signals in Gaussian and compound Poisson noise.
01 January 1988
An approximate but explicit likelihood ratio is derived for detecting deterministic signals in Gaussian and compound Poisson noise. Difficulty of such a derivation lies in the simultaneous presence of two distinctly different noises where the compound Poisson noise consists of a random number of localized noise elements modeled as nonstationary Gaussian processes scattered according to a Poisson point process. Lightning in radio transmission may be a natural example of such noise. The approximation in the derivation is based on the assumption that the localized noise elements rarely overlap with each other. It is this feature, namely, being distinct, large and infrequently occurring that makes the localized noise very different from the usual noise encountered in detection theory.