Abstract
In this paper, a Bar-Shalom Campo-based algorithm is presented to solve the approximate maximum ellipsoid in the cross region of covariance ellipsoid. An objective function that can be solved by linear matrix inequality is designed based on the rotation transformation of matrix. Compared with the classical covariance intersection fusion algorithm, it is less conservative. Moreover, the unknown cross-covariance is approximated as a linear matrix inequality constraint with Pearson correlation coefficient which is bounded. With the inequality constraint, the accuracy of fusion results can be improved. Finally, two simulation examples are given to verify the effectiveness of the proposed algorithm.
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