Paper
16 August 2001 Scientific performance evaluation for distributed sensor management and adaptive data fusion
Author Affiliations +
Abstract
For the last two years at this conference, we have described the implementation of a unified, scientific approach to performance measurement for data fusion algorithms based on FINITE-SET STATISTICS (FISST). FISST makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems. In previous papers we described application of information Measures of Effectiveness (MoEs) to multisource-multitarget data fusion and to non-distributed sensor management. In this follow-on paper we show how to generalize this work to DISTRIBUTED sensor management and ADAPTIVE DATA FUSION.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Adel I. El-Fallah, Ravi B. Ravichandran, Raman K. Mehra, John R. Hoffman, Tim Zajic, Chad A. Stelzig, Ronald P. S. Mahler, and Mark G. Alford "Scientific performance evaluation for distributed sensor management and adaptive data fusion", Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); https://doi.org/10.1117/12.436960
Lens.org Logo
CITATIONS
Cited by 7 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Molybdenum

Data fusion

Detection and tracking algorithms

Silicon

Monte Carlo methods

Solids

Back to Top