Soft Sensor Management for Multisensor Tracking Algorithm
This chapter describes a method and an algorithm for combining symbolic and numerical information for data fusion in a tracking application. In recent years, the synergetic use of multiple sensors has received a great deal of attention. The major benefits of such use are an increase in the ability to analyse complex situations and an improved robustness of the fusion process in a cluttered environment. Military command and control, battlefields management, mobile robot navigation, and multitarget tracking are all typical applications that can benefit from the use of multiple sensors. Therefore, both the integration and the fusion of information, provided by multiple sensors, appear to be fields of growing interest.
KeywordsMembership Function Data Fusion Multiple Sensor Confidence Coefficient Cluttered Environment
Unable to display preview. Download preview PDF.
- 1.Appriou A. (1990) “Perspectives liées à la fusion de données”, Science et défense 90, Dunod, Paris.Google Scholar
- 3.Bar-Shalom Y. (1992) “Multitarget — Multisensor Tracking: Application and Advances”, Artech House.Google Scholar
- 5.Chong C.Y., (1979) “Hierarchical Estimation”, Proc. 2nd MIT/ONR Workshop on Distributed Communication and Decision Problems, Monterey, CA.Google Scholar
- 6.Chong C.Y., Mori S., Tse E, Whisner R.P. (1979) “Distributed Estimation in Distributed Sensor Networks”, Proc IEEE American Control Conference, Arlington, CA.Google Scholar
- 7.Haimovich A.M., “Fusion of Sensors with dissimilar Measurement/tracking accuracies”, IEEEGoogle Scholar