Target Recognition Based on Fuzzy Dempster Data Fusion Method
Data fusion technology is widely used in automatic target recognition system. Problems in data fusion system are complex by nature and can often be characterised by not only randomness but also by fuzziness. To accommodate complex natural problems with both types of uncertainties, it is profitable to construct a data fusion structure based on fuzzy set theory and Dempster Shafer evidence theory. In this paper, after representing both, the individual attribute of target in the model database and the sensor observation or report as fuzzy membership function, a likelihood function was constructed to deal with fuzzy data collected by each sensor. The method to determine basic probability assignments of each sensor report is proposed. Sensor reports are fused through classical Dempster combination rule. A numerical example is illustrated to show the target recognition application of the fuzzy-Dempster approach.
Defence Science Journal, 2010, 60(5), pp.525-530, DOI:http://dx.doi.org/10.14429/dsj.60.576
Where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India