Title :
An Empirical Study into the Use of Chernoff Information for Robust, Distributed Fusion of Gaussian Mixture Models
Author :
Julier, Simon J.
Author_Institution :
Naval Res. Lab., ITT AES, Washington, DC
Abstract :
This paper considers the problem of developing algorithms for the distributed fusion of Gaussian mixture models through the use of Chernoff information. We derive a first order approximation and show that, in a distributed tracking problem in which sensor nodes are equipped with only range-only or bearing-only sensors, it yields consistent estimates
Keywords :
Gaussian processes; approximation theory; sensor fusion; Chernoff information; Gaussian mixture model; bearing-only sensor; distributed fusion; first order approximation; Closed-form solution; Context modeling; Cost function; Fuses; Laboratories; Network topology; Probability distribution; Robustness; Sensor fusion; Uncertainty; Chernoff Information; Covariance Intersection; Gaussian Mixture Models;
Conference_Titel :
Information Fusion, 2006 9th International Conference on
Conference_Location :
Florence
Print_ISBN :
1-4244-0953-5
Electronic_ISBN :
0-9721844-6-5
DOI :
10.1109/ICIF.2006.301755
