Title :
Distributed multisensor parameter estimation in dependent noise
Author :
Chau, Yawgeng A. ; Geraniotis, Evaggelos
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA
fDate :
2/1/1992 12:00:00 AM
Abstract :
The problem of distributed estimation of a weak nonrandom location parameter θ in additive stationary dependent noise is addressed. Multisensor configurations with and without a coordinator are considered. Dependence in the sensor observations is described by m -dependent, φ-mixing, and p-mixing models. Two cases of interest are addressed: one in which sensor observations are dependent across time but independent across sensors and one in which sensor observations are dependent across both time and sensors. Numerical results on the performance evaluation of the various estimation schemes derived are presented and the relative performances of the various schemes are compared
Keywords :
noise; parameter estimation; signal processing; additive stationary dependent noise; array processing; distributed estimation; multisensor parameter estimation; sensor dependent; sensor observations; time dependent; weak nonrandom location parameter; Additive noise; Communications Society; Cost function; Integral equations; Maximum likelihood estimation; Mean square error methods; Parameter estimation; Sampling methods; Sensor phenomena and characterization; Statistics;
Journal_Title :
Communications, IEEE Transactions on