A study of a target tracking method using Global Nearest Neighbor algorithm

Abstract

This paper compares two algorithm for Multiple Target Tracking using Global Nearest Neighbor (GNN) approach: first by the use standard Kalman filter (SKF-GNN) and second by the use Interacting Multiple Model (IMMGNN) in order to derive final tracking estimation. For both algorithms the observations are divided in clusters to reduce computational efforts. Results of simulations by tracking 20 targets simultaneously reveal that in some cases the IMMGNN approach gives better solution then KF-GNN approach. The computational time for assignment problem solution for maneuvering target tracking using both algorithm is studied and results prove that is IMMGNN suitable for real time implementations. .