| Title |
Two-Stage Multi-radar Data Fusion for Re-entry Target Tracking |
| Authors |
정보영(Boyoung Jung) ; 이찬석(Chan-Seok Lee) ; 서의석(Ui-Suk Suh) ; 나원상(Won-Sang Ra) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.9.1372 |
| Keywords |
Multi-radar target tracking and identification; Track-to-track fusion; decision level data fusion; Bernoulli filter |
| Abstract |
This paper proposes a two-stage track-to-track fusion algorithm for re-entry target tracking using multiple radars. The existing track-to-track fusion strategy relying only on the kinematic information shows unreliable target tracking performance when the target of interest is adjacent with other objects. To prevent tracking performance degradation due to false track fusion, the track paring hypothesis is evaluated using both the feature data and the kinematic data provided by radars. A recursive Bernoulli filter is desinged to discriminate the target identity by fusing binary decision data which correspond to the most probable track pairing hypothesis. Since our approach exploits the statistical property of the available decision data, it can enhance the target tracking and identification performance. Through the computer simulations for a typical re-entry target tracking scenario, the effectiveness of the suggested data fusion scheme is demonstrated. |