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Human Dead Reckoning Using a Particle Filter and Map Constraints, by Joseph Russell and Jeroen H.M. Bergmann, narrated in full by Joseph Russell, as published by Sensors on 2 June 2026, article 3500.
Full article available at: https://doi.org/10.3390/s26113500
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This paper presents an approach for tracking a person’s position by integrating inertial measurement unit (IMU) sensor values, utilising a particle filter with known physical constraints, such as a map of the space. While such approaches are well established, the effect of constraint choice in the absence of observation measurements remains poorly understood. The effect of varying the tolerance of these constraints is investigated with data collected from a Movella DOT held by a human participant walking around a 100 m running track. In particular, the dimensions of the map are varied, along with the shape. Results showed (a) that it is viable to correct particle filter error without external sensor feedback, provided constraints are provided, with a mean error of 1.8 m, and (b) there is a minimum acceptable tolerance of map width around the edge of the true activity zone, in this case approximately 8 m, and that tightening the map boundary further than this can counterintuitively lead to reduced accuracy.
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© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
