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The problem of distributed fusion for estimation when the cross-correlation of errors of local estimates is unavailable is addressed. We discuss a general estimation fusion approach for this problemgeneralized convex combination (GCC)and classify various GCC fusion approaches in three categories. We develop three GCC fusion algorithms for the problem under consideration. First, based on a set-theoretic...
We develop an analytic center approach to distributed estimation fusion when the cross-correlation of errors between local estimates is unknown. Based on a set-theoretic formulation of the problem, we seek an estimate that maximizes the complementary squared Mahalanobis “distance” between the local and the desired estimates in a logarithmic average form, and the optimal value turns out to be the analytic...
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