SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Particle filtering under communications constraints

Author(s)

Alexander T. Ihler	MIT
John Fisher	MIT
Alan Willsky	MIT

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Abstract

Particle filtering is often applied to problems of object tracking with non-Gaussian uncertainty; however, sensor networks frequently require that the implementation be local to the region of interest, eventually forcing the large, sample-based representation to be moved among power-constrained sensors. We consider the problem of successive approximation (i.e., lossy compression) of each sample-based density estimate, in particular exploring the consequences (both theoretical and empirical) of several possible choices of loss function and their interpretation in terms of future errors in inference, justifying their use for measuring approximations in distributed particle filtering.