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15 April 2010A no-loss covariance intersection algorithm for
track-to-track fusion
Compared to the optimal track-to-track fusion (T2TF) algorithm under linear Gaussian assumption and the
information matrix fusion, the major advantage of the covariance intersection (CI) method for the problem of
T2TF is that it neither needs the crosscovariances between the local tracks, nor does it use local information
increments which are required to be independent. This allows the CI method to be used in scenarios where the
optimal T2TF and the information matrix fusion algorithms are difficult or impractical to implement. However,
a significant drawback of the original CI algorithm is that it is too conservative and will yield unnecessary loss
in its calculated fusion accuracy. Even worse, as shown in this paper, this loss increases with the number of
local tracks for fusion. This greatly degrades the usefulness of the CI algorithm. In this paper, a new "sampling
CI" algorithm is proposed, which is simple to implement and does not have the above problematic feature of the
original CI. Simulation results from various scenarios demonstrate the effectiveness of the proposed algorithm.
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Xin Tian, Yaakov Bar-Shalom, Genshe Chen, "A no-loss covariance intersection algorithm for track-to-track fusion," Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980S (15 April 2010); https://doi.org/10.1117/12.849049