137 citations · 542 across the 31 of their papers we have counts for
39 papers
Revisiting Split Covariance Intersection: Correlated Components and Optimality
Colin Cros, Pierre-Olivier Amblard, Christophe Prieur +1
Linear fusion is a cornerstone of estimation theory. Implementing optimal linear fusion requires knowledge of the covariance of the vector of errors associated with all the estimat…
Split Covariance Intersection with Correlated Components for Distributed Estimation
Colin Cros, Pierre-Olivier Amblard, Christophe Prieur +1
This paper introduces a new conservative fusion method to exploit the correlated components within the estimation errors. Fusion is the process of combining multiple estimates of a…
Random Multi-Type Spanning Forests for Synchronization on Sparse Graphs
Hugo Jaquard, Pierre-Olivier Amblard, Simon Barthelmé +1
Random diffusions are a popular tool in Monte-Carlo estimations, with well established algorithms such as Walk-on-Spheres (WoS) going back several decades. In this work, we introdu…
Pseudorange Rigidity and Solvability of Cooperative GNSS Positioning
Colin Cros, Pierre-Olivier Amblard, Christophe Prieur +1
Global Navigation Satellite Systems (GNSS) are a widely used technology for positioning and navigation. GNSS positioning relies on pseudorange measurements from satellites to recei…
Optimality of Split Covariance Intersection Fusion
Colin Cros, Pierre-Olivier Amblard, Christophe Prieur +1
Linear fusion is a cornerstone of estimation theory. Optimal linear fusion was derived by Bar-Shalom and Campo in the 1980s. It requires knowledge of the cross-covariances between…
Fusion of Distance Measurements between Agents with Unknown Correlations
Colin Cros, Pierre-Olivier Amblard, Christophe Prieur +1
Cooperative localization is a promising solution to improve the accuracy and overcome the shortcomings of GNSS. Cooperation is often achieved by measuring the distance between user…