Adaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian Noise
Data Analysis, Statistics and Probability
2016-07-29 v1 Information Theory
math.IT
Abstract
This paper considers the general signal detection and parameter estimation problem in the presence of colored Gaussian noise disturbance. By modeling the disturbance with an autoregressive process, we present three signal detectors with different unknown parameters under the general framework of binary hypothesis testing. The closed form of parameter estimates and the asymptotic distributions of these three tests are also given. Given two examples of frequency modulated signal detection problem and time series moving object detection problem, the simulation results demonstrate the effectiveness of three presented detectors.
Cite
@article{arxiv.1607.08259,
title = {Adaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian Noise},
author = {Bo Tang and Haibo He and Steven Kay},
journal= {arXiv preprint arXiv:1607.08259},
year = {2016}
}
Comments
23 pages, 7 figures