Tracking Radar (Using the Dempster–Shafer Theory)
Malek Benslama, Hadj Batatia, Abderraouf Messai · 2016
Multi-target tracking is a very important domain for aviation safety that requires great precision and continuity, so the quality of the tracking lies in good data combining. This chapter begins by introducing evidence theory and its different mass functions, then tackles evidence combination in the theory and describes the decision rule for taking a good combination. Then it presents work in order to see how method performs in multi-target tracking and data combination. In the Bayesian approach, the uncertainty concerning an event is measured by a single value: the probability and imprecision on the uncertainty measurement are assumed to be null. The Dempster–Shafer theory enables information taken from different sources to be combined, according to Shafer, if two belief functions are defined on a single frame of discernment such that this frame of discernment distinguishes the pertinent interaction between two pieces of information.