Data Fusion with Different Accuracy
Jin Tang, Jason J. Gu, Zixing Cai · 2005
This paper presents criteria to evaluate different data fusion approaches. A new fusion method for two data with different accuracy is also presented. This approach is an extension of weighted average, which can solve some problem that cannot be handled by maximum likelihood approach. Simulation result is compared with other three fusion algorithms. Comparison shows that it is better than all weighted average approaches and it is the best of these four approaches.