Cooperative Tracking Using Marginal Diffusion Particle Filters

Marcelo G. S. Bruno; Stiven S. Dias

ICASSP 2018accepted0 citations

Cooperative Tracking Using Marginal Diffusion Particle Filters

Abstract

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 Monte Carlo (SMC) strategy and a hybrid Gaussian/SMC methodology. The proposed algorithms are assessed via simulation in a numerical example of cooperative target tracking with received-signal-strength (RSS) sensors.

BibTeX

@inproceedings{icassp2018_cooperativetrack,
  title = {Cooperative Tracking Using Marginal Diffusion Particle Filters},
  author = {Marcelo G. S. Bruno and Stiven S. Dias},
  booktitle = {ICASSP 2018},
  year = {2018}
}