Multi-target tracking and data association using learning network systems: a conceptual design

The problem of tasking sensors and tracking multiple objects using multiple sensors which are distributed both in space and on the ground is addressed for both commercial and military applications. The data association problem is considered in a broader sense in which the assignment of an asset to an object under consideration has been added as an additional function to a traditional tracking and data association system. Suggested learning network architectures and algorithms for potentially enhancing the performance of traditional techniques are discussed and conceptualized