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• W3211745316 abstract "Particle filter is commonly used in various indoor positioning schemes, but sample impoverishment and weight degradation generally exist in particle filter. To solve this problem, this article uses the firefly algorithm to optimize particle filter. Using the global optimal value in the particle swarm to guide the remaining particles to update their positions, the particles tend to move to the high likelihood area, which can more accurately describe the true state of the target observation. At the same time, to avoid particles falling into local optimum and oscillating repeatedly at the extreme point, the mathematical model of the firefly algorithm is reconstructed in this article, which is named as adaptive optimization firefly algorithm (AOFA). The experimental results show that the positioning scheme can provide the positioning accuracy with an average error of less than 0.5 m. Compared with the traditional particle filter, the positioning accuracy is improved by 120%." @default.
• W3211745316 created "2021-11-22" @default.
• W3211745316 creator A5004388792 @default.
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• W3211745316 date "2022-01-01" @default.
• W3211745316 modified "2023-10-16" @default.
• W3211745316 title "PDR/Geomagnetic Fusion Localization Method Based on AOFA-Improved Particle Filter" @default.
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• W3211745316 doi "https://doi.org/10.1109/tim.2021.3128706" @default.
• W3211745316 hasPublicationYear "2022" @default.
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