Target Tracking and Data Fusion: How to Get the Most Out of Your Sensors
This talk discusses the issues related to information extraction and data fusion from multiple sensors, in particular, from radars. The goal of extracting the maximum possible amount of information from each sensor requires the use of the appropriate sensor as well as target models. In these models, one has to quantify the corresponding uncertainties. The issues related to data association and multiple target behavior models are discussed together with some practical algorithms and their implementations for Low Observable targets, with an example of the early acquisition of a VLO TBM. The fusion of the information from various sources has to account for their uncertainties as well as the interrelationship -- cross-correlations -- between the uncertainties across sources.
The "Track-to-Track Fusion" and "Centralized Fusion" configurations are discussed