Accession Number:

ADA170165

Title:

Asymptotically Robust Detection of Stochastic Signals in Contaminated Noise,

Descriptive Note:

Corporate Author:

TEXAS A AND M UNIV COLLEGE STATION DEPT OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

1986-05-22

Pagination or Media Count:

9.0

Abstract:

We consider the discrete time detection of stochastic signals in white noise, where the univariate noise density is known perfectly only on an interval about the origin. We present a method to enhance the asymptotic performance of the detector by exploiting this knowledge, and at the same time preserve robustness properties of the detector to the remaining inexact knowledge of the univariate noise density via a saddlepoint condition. We then provide examples to show that improved performance is indeed obtained. Author

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE