Multi-Sensor PHD by Space Partionning: Computation of a True Reference Density Within The PHD Framework - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2011

Multi-Sensor PHD by Space Partionning: Computation of a True Reference Density Within The PHD Framework

Emmanuel Delande
  • Function : Author
  • PersonId : 873501
Emmanuel Duflos
  • Function : Author
  • PersonId : 844358
Philippe Vanheeghe
  • Function : Author
  • PersonId : 838038

Abstract

In a previous paper, the authors proposed an extension of the Probability Hypothesis Density (PHD), a well-known method for singlesensor multi-target tracking problems in a Bayesian framework, to the multi-sensor case. The true expression of the multi-sensor data update PHD equation was constructed using finite sets statistics (FISST) derivative techniques on functionals defined onmulti-sensor observation and state space named "cross-terms". In this paper, an equivalent expression in a combinational form is provided, which allows an easier interpretation of the data update equation. Then, using the joint partitioning proposed by the authors in the previous paper, an exact multi-sensor multi-target PHD filter is efficiently propagated on a benchmark scenario involving 10 sensors and up to 10 simultaneous targets where the brute force approach would have been extremely burdensome. The availability of a true reference PHD then allows a validation of the classical iterated-corrector approximation method, albeit limited to the scope of the implemented scenario.
Fichier principal
Vignette du fichier
SSP2011.pdf (165.63 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00639710 , version 1 (09-11-2011)

Identifiers

Cite

Emmanuel Delande, Emmanuel Duflos, Philippe Vanheeghe, Dominique Heurguier. Multi-Sensor PHD by Space Partionning: Computation of a True Reference Density Within The PHD Framework. Statistical Signal Processing Workshop (SSP), 2011, IEEE - Signal Processing Society, Jun 2011, Nice, France. pp.333 - 336, ⟨10.1109/SSP.2011.5967695⟩. ⟨hal-00639710⟩
128 View
214 Download

Altmetric

Share

More