Particle filters for positioning, navigation, and tracking

By Fredrik K. Gustafsson, Fredrik Gunnarsson, Niclas Bergman, Urban Forssell, Jonas Jansson, Rickard Karlsson, Per-Johan Nordlund. IEEE Transactions on Signal Processing, 2002

1,900 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/3bb41e674eb39ad04d060409f75947b25e1f958c

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Citations in the corpus

Anticipating Human Activities Using Object Affordances for Reactive Robotic Response (2013, methodology): “The remaining parts of the states are solved analytically conditioned on the particles by using Kalman filters [64], [65], [66], [67].”
Towards Mobile Phone Localization without War-Driving (2010, background): “Such cases can be accommodated using particle filters [14], [15] which operate on movement probabilities in multiple directions.”
Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning (2006, methodology): “The weight update equation is given in [6, 7]”
Particle Filter SLAM with High Dimensional Vehicle Model (2009, background): “particular when the observations are complicated nonlinear functions of the position and heading [19].”
Adapting the Sample Size in Particle Filters Through KLD-Sampling (2003, methodology): “Sample-based approachesrepresent beliefs by sets of samples, or particles (Fox et al. 1999a; Dellaeart et al. 1999; Fox et al. 2001; Lenser and Veloso 2000; Jensfelt et al. 2000; Gustafsson et al. 2002).”
Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking (2022, background): “On the other hand, particle filters [23] deal with the non-linear motion by sampling-based posterior estimation but require exponential order of computation.”
Biips: Software for Bayesian Inference with Interacting Particle Systems (2014, background): “They have found numerous applications in signal ﬁltering and robotics (Thrun et al. 2001; Gustafsson et al. 2002; Vermaak et al. 2002; Vo et al. 2003; Ristic et al. 2004; Caron et al. 2007), systems biology (Golightly and Wilkinson 2006, 2011; Bouchard-Côté et al. 2012), economics and…”
Particle gibbs with ancestor sampling (2014, background): “…many models for which the transition is implicitly given by a simulator (Gander and Stephens, 2007; Fearnhead et al., 2008; Golightly and Wilkinson, 2008; Murray et al., 2013) or degenerate models where the transition density does not even exist (Ristic et al., 2004; Gustafsson et al., 2002).”
In-Car Positioning and Navigation Technologies—A Survey (2009, background): “Indeed, in [27], for example, a vehicle navigation system solely based on wheel speed sensors and a probabilistic map-matching approach is described.”
Urban traffic signal control with connected and automated vehicles: A survey (2019, methodology): “Other stochastic filtering techniques such as Kalman filter (Guo et al., 2014; Tampère and Immers, 2007), particle filter (Gustafsson et al., 2002; Marinica et al., 2013), and other machine learning based approaches (Lv et al., 2015; Rompis et al., 2017) have been applied to help estimate queue…”