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ISPRS Int. J. Geo-Inf. 2018, 7(8), 324; https://doi.org/10.3390/ijgi7080324

An INS/Floor-Plan Indoor Localization System Using the Firefly Particle Filter

School of Information Science and Engineering, Xiamen University, Xiamen 361001, China
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Received: 26 June 2018 / Revised: 28 July 2018 / Accepted: 28 July 2018 / Published: 10 August 2018
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Abstract

Location-based services for smartphones are becoming more and more popular. The core of location-based services is how to estimate a user’s location. An INS/floor-plan indoor localization system, using the Firefly Particle Filter (FPF), is proposed to estimate a user’s location. INS includes an attitude angle module, a step length module and a step counting module. In the step length module, we propose a hybrid step length model. The proposed step length algorithm reasonably calculates a user’s step length. Because of sensor deviation, non-orthogonality and the user’s jitter, the main bottleneck for INS is that the error grows over time. To reduce the cumulative error, we design cascade filters including the Kalman Filter (KF) and FPF. To a certain extent, KF reduces velocity error and heading drift. On the other hand, the firefly algorithm is used to solve the particle impoverishment problem. Considering that a user may not cross an obstacle, the proposed particle filter is proposed to improve positioning performance. Results show that the average positioning error in walking experiments is 2.14 m. View Full-Text
Keywords: indoor localization system; INS; floor plan; KF; FPF indoor localization system; INS; floor plan; KF; FPF
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Chen, J.; Ou, G.; Peng, A.; Zheng, L.; Shi, J. An INS/Floor-Plan Indoor Localization System Using the Firefly Particle Filter. ISPRS Int. J. Geo-Inf. 2018, 7, 324.

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