Design of a performance evaluation methodology for data fusion-based multiple target tracking systems

The emphasis of this paper is to design a Performance Evaluation Methodology for Data Fusion-based Multiple Target Tracking Systems. Within this methodology the Performance Evaluation process is treated as a whole new fusion process. This has two major advantages - (1) Facilitates reusability of existing models and algorithms, and (2) Using standard frameworks and norms makes it easier for the tracking community to easily adopt it - thus giving this aspect of tracking a highly needed jumpstart. A case study implementation of this design methodology is presented. Three different Track-Truth Association strategies were implemented to study the effect of Track-Truth Association strategies on the performance metrics. The case study results conclusively show that the selection of the Track-Truth Association strategy should be done with reference to the scenario characteristics, the "mission" goals and the performance metrics to be evaluated.