An efficient decentralized multiradar multitarget tracker for air surveillance

We present an efficient multiradar multitarget tracking (MTT) algorithm for air surveillance. This tracker uses a multisensor track-to-track correlation method called the sequential minimum normalized distance nearest neighbor (SMNDNN) correlation with the majority decision making MDM/OR logic to solve the multisensor assignment problem. A sequential fuser based on the mean square error criterion is then used to fuse the tracks generated by the trackers. Real-life multiradar data collected from an air surveillance radar network located along the coastline of Canada is used to evaluate the effectiveness of this distributed tracker. Analysis shows that this tracker provides a reliable air surveillance picture.