Exact algorithms for track-to-track fusion by multiple UAVs and performance evaluation

Track-to-track fusion is an important topic for cooperative surveillance, reconnaissance and target tracking by multiple unmanned aerial vehicles (UAVs). In this paper, the accurate cross-covariances between the local estimates are obtained from various information feedback configurations, which gives rise to the scalable and consistent algorithms for track-to-track fusion (T2TF) at an arbitrary communication rate. Furthermore, the steady-state error covariance of the fused estimate is obtained by solving the corresponding discrete algebraic Riccati equation for performance analysis. In addition, the theoretical results are compared with those from the extensive Monte Carlo simulation, which validates the effectiveness of the proposed fusion algorithms.