Signal detection in the presence of weakly dependent noise. Part 2: Robust detection
Abstract
The problem of designing robust systems for detecting constant signals in the presence of weakly dependent noise with uncertain statistics is considered. A movingaverage representation is used to model the dependence structure of the noise process, with the degree of dependence being parameterized by the averaging weights. Weak dependence is then modeled as the situation in which quantities depending to second or higher order on the averaging weights can be considered to be negligible. Uncertainty in the noise statistics is introduced within this framework by allowing a general type of uncertainty in the univariate statistics of the independent sequence that drives the moving average. To find robust detectors for signals in this type of weakly dependent noise environment, related results concerning robust location estimation in an analogous dependent situation are applied to modify a robust detection system for the corresponding independentnoise case.
 Publication:

NASA STI/Recon Technical Report N
 Pub Date:
 December 1981
 Bibcode:
 1981STIN...8325942P
 Keywords:

 Low Noise;
 Mathematical Models;
 Maximum Likelihood Estimates;
 Noise Generators;
 Random Noise;
 Signal Detection;
 Signal Processing;
 Distribution Functions;
 Error Functions;
 Independent Variables;
 Robustness (Mathematics);
 Signal To Noise Ratios;
 Statistical Analysis;
 Communications and Radar