Particle Gaussian Mixture (PGM) filters

@article{Raihan2016ParticleGM,
  title={Particle Gaussian Mixture (PGM) filters},
  author={D. Raihan and Suman Chakravorty},
  journal={2016 19th International Conference on Information Fusion (FUSION)},
  year={2016},
  pages={1369-1376}
}
Recursive estimation of nonlinear dynamical systems is an important problem that arises in several engineering applications. Consistent and accurate propagation of uncertainties is important to ensuring good estimation performance. It is well known that the posterior state estimates in nonlinear problems may assume non-Gaussian multimodal densities. In the past, Gaussian filters and particle filters were introduced to handle non-Gaussianity and nonlinearity. However, these methods have seen… CONTINUE READING
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