M. K. Tay, K. Mekhnacha, C. Chen, M. Yguel, and C. Laugier, An efficient formulation of the Bayesian occupation filter for target tracking in dynamic environments, International Journal of Vehicle Autonomous Systems, vol.6, issue.1/2, pp.155-171, 2008.
DOI : 10.1504/IJVAS.2008.016483

URL : https://hal.archives-ouvertes.fr/inria-00182089

Y. B. Shalom and T. E. Fortman, Tracking and Data Association, 1988.

C. Coue, . Th, P. Fraichard, E. Bessiere, and . Mazer, Multi-sensor data fusion under Bayesian programming: an automative application, Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and SystemsCH), 2002.

C. Coue, C. Pradalier, C. Laugier, . Th, P. Fraichard et al., Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application, The International Journal of Robotics Research, vol.99, issue.1, pp.19-30, 2006.
DOI : 10.1177/0278364906061158

URL : https://hal.archives-ouvertes.fr/inria-00182004

H. P. Moravec, Sensor Fusion in Certainty Grids for Mobile Robots, 1988.
DOI : 10.1007/978-3-642-74567-6_19

A. H. Jazwinsky, Stochastic Processes and Filtering Theory, 1970.

G. Welch and G. Bishop, An introduction to the Kalman filter

C. M. Bishop, Pattern recognition and machine learning, 2006.