Contributions to Proceedings:
O. Hlinka, P. Djuric, F. Hlawatsch:
"Time-space-sequential Distributed Particle Filtering with Low-rate Communications";
in: "Proc. 43rd Asilomar Conf. Signals, Systems, Computers",
IEEE Conference Proceedings,
We present a distributed particle filtering scheme for time-space-sequential Bayesian state estimation in wireless sensor networks. Low-rate inter-sensor communications between neighboring sensors are achieved by transmitting Gaussian mixture (GM) representations instead of particles. The GM representations are calculated using a clustering algorithm. We also propose a "look-ahead" technique for designing the proposal density used for importance sampling. Simulation results for a target tracking application demonstrate the performance of our distributed particle filter and, specifically, the advantage of the look-ahead proposal design over a conventional design.
wireless sensor network, distributed particle filter, Bayesian state estimation, Gaussian mixture, target tracking
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.