Paper Info
Title
Application of characteristic function to detection in sinusoidal interference plus Gaussian noise
Abstract
In this work, a detector scheme for the detection of signal in a group of non-Gaussian narrowband interferences and white Gaussian noise is developed. Since there exists no closed-form probability distribution for this type of disturbance modeling, the key innovation lies in the use of characteristic function rather than the probability distribution to both design and implement the detector. Parameter estimation is performed at first step to find the unknown disturbance parameters. The utilized detector uses these parameters to form an approximately Gaussian distributed test statistic based on the empirical characteristic function of received data. Performance of the detector is investigated by means of both analytical and Monte Carlo simulations.
Year
DOI
Venue
2009
10.1109/ICASSP.2009.4960269
ICASSP
Keywords
Field
DocType
monte carlo simulation,utilized detector,empirical characteristic function,disturbance modeling,characteristic function,sinusoidal interference,white gaussian noise,unknown disturbance parameter,detector scheme,closed-form probability distribution,probability distribution,gaussian distribution,white noise,statistical analysis,monte carlo methods,approximation theory,probability density function,signal to noise ratio,estimation,detectors,signal detection,gaussian noise,testing,noise,parameter estimation,monte carlo simulations,interference
Computer science,White noise,Artificial intelligence,Gaussian process,Gaussian function,Gaussian filter,Pattern recognition,Gaussian random field,Algorithm,Gaussian,Statistics,Gaussian noise,Additive white Gaussian noise
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
2
3
Name
Order
Citations
PageRank
Mahdi Parchami152.77
hamidreza amindavar221536.34
J. A. Ritcey385884.27