9 accepted papers
We propose in this paper two adapt-then-combine (ATC) distributed particle filters for cooperative estimation of 3D orientations. The first algorithm represents rotations as elements of the Special Orthogonal Group and builds Gaussian parametric approximations on a Lie Algebra to fuse posterior prob…
We present in this paper a fully distributed algorithm for simultaneous positioning of cooperative aircraft and distributed tracking of a noncooperative target. We model the probability of connection between the aircraft and the probability of an aircraft detecting the target and implement the simul…
This paper proposes new distributed particle filters for tracking the state of a dynamic system that evolves on the Special Euclidean Group. The algorithms are based on the Random Exchange diffusion technique and build compressed parametric approximations to the particles using Lie algebras. Via num…
This paper introduces a novel distributed diffusion algorithm for tracking the state of a dynamic system that evolves on the Stiefel manifold. To compress information exchanged between nodes, the algorithm builds a Gaussian parametric approximation to the particles that are previously projected onto…
This paper introduces a new distributed Adapt-then-Combine (ATC) diffusion algorithm for cooperative tracking of an un-known state vector that evolves on the unit hypersphere. The adapt step is implemented for a general nonlinear observation model and a dynamic state model defined on the hypersphere…
In this paper, we extend previous particle filtering methods whose states were constrained to the (real) Stiefel manifold to the complex case. The method is then applied to a Bayesian formulation of the subspace tracking problem. To implement the proposed particle filter, we modify a previous MCMC a…
Many problems in statistical signal processing involve tracking the state of a dynamic system that evolves on a Stiefel manifold. To this aim, we introduce in this paper a novel particle filter algorithm that approximates the optimal importance function on the Stiefel manifold and is capable of hand…
This paper formulates the general Adapt-then-Combine (ATC) and Random Exchange (RndEx) diffusion filters for an arbitrary nonlinear state-space model. Subsequently, we propose two novel marginal Particle Filter implementations of the general ATC and RndEx filters using respectively a pure Sequential…
We introduce in this paper the Random Exchange Diffusion Bernoulli Filter (RndEx-BF), which enables joint target detection and tracking by a network of collaborative sensors. RndEx-BF is a fully distributed algorithm that, unlike consensus-based solutions, does not require iterative internode commun…