Overlapping Covariance Intersection: Fusion with Partial Structural Knowledge of Correlation from Multiple Sources
The paper introduces Overlapping Covariance Intersection (OCI), a method to fuse estimates from multiple sources when the exact correlation structure is unknown but partial bounds are available. It uses a generalized Covariance Intersection framework and solves the resulting complex optimization problem using semidefinite programming to find a family-optimal solution.