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Gaussian target tracking with direction-of-arrival von Mises–Fisher measurements

Garcia-Fernandez, Angel F ; Tronarp, Filip LU and Särkkä, Simo (2019) In Transactions on Signal Processing 67(11).
Abstract
This paper proposes a novel algorithm for target tracking with direction-of-arrival measurements, modeled by von Mises-Fisher distributions. The algorithm makes use of the assumed density framework with Gaussian distributions, in which the posterior probability density of the target state is approximated by a Gaussian density. A key component of this algorithm is that the proposed Bayesian model of the measurements takes into account the specific characteristics of angular measurements by using a von Mises-Fisher distribution. We propose two implementations of the algorithm, one based on first-order Taylor series expansion and another one based on sigma points. Simulation results show the benefits of the proposed algorithms in relation to... (More)
This paper proposes a novel algorithm for target tracking with direction-of-arrival measurements, modeled by von Mises-Fisher distributions. The algorithm makes use of the assumed density framework with Gaussian distributions, in which the posterior probability density of the target state is approximated by a Gaussian density. A key component of this algorithm is that the proposed Bayesian model of the measurements takes into account the specific characteristics of angular measurements by using a von Mises-Fisher distribution. We propose two implementations of the algorithm, one based on first-order Taylor series expansion and another one based on sigma points. Simulation results show the benefits of the proposed algorithms in relation to other Gaussian filters in the literature. (Less)
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author
; and
publishing date
type
Contribution to journal
publication status
published
subject
in
Transactions on Signal Processing
volume
67
issue
11
external identifiers
  • scopus:85065446836
DOI
10.1109/TSP.2019.2911258
language
English
LU publication?
no
id
608010fb-bfc6-4707-8bba-87d3a3fa7f03
date added to LUP
2023-08-20 22:44:59
date last changed
2023-11-10 13:34:45
@article{608010fb-bfc6-4707-8bba-87d3a3fa7f03,
  abstract     = {{This paper proposes a novel algorithm for target tracking with direction-of-arrival measurements, modeled by von Mises-Fisher distributions. The algorithm makes use of the assumed density framework with Gaussian distributions, in which the posterior probability density of the target state is approximated by a Gaussian density. A key component of this algorithm is that the proposed Bayesian model of the measurements takes into account the specific characteristics of angular measurements by using a von Mises-Fisher distribution. We propose two implementations of the algorithm, one based on first-order Taylor series expansion and another one based on sigma points. Simulation results show the benefits of the proposed algorithms in relation to other Gaussian filters in the literature.}},
  author       = {{Garcia-Fernandez, Angel F and Tronarp, Filip and Särkkä, Simo}},
  language     = {{eng}},
  number       = {{11}},
  series       = {{Transactions on Signal Processing}},
  title        = {{Gaussian target tracking with direction-of-arrival von Mises–Fisher measurements}},
  url          = {{http://dx.doi.org/10.1109/TSP.2019.2911258}},
  doi          = {{10.1109/TSP.2019.2911258}},
  volume       = {{67}},
  year         = {{2019}},
}