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Integrated Navigation in Indoor NLOS Environment Based on Kalman Filter

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EITCE '21: Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering

Pages 586 - 590

https://doi.org/10.1145/3501409.3501516

Published: 31 December 2021 Publication History

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Abstract

In view of the fact that the global satellite navigation system can not be applied to the indoor environment, it is of great practical significance to study the navigation problems in the indoor environment. This paper first introduces the basic principles of inertial navigation and ultra-wideband navigation, then analyzes the practical problems of TOA estimation of UWB signals in indoor NLOS environment, and considers the use of Kalman filter to optimize the integrated navigation error in NLOS environment. The simulation experiment is used to assist the analysis and the optimization results are given. Through the analysis of the results, the NLOS error is reduced by 27.7%.

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Li TDeng ZZhang YDong WYu H(2024)A Tightly Coupled UWB/PDR Fusion Positioning Algorithm for Indoor EnvironmentsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2024.345804073(1-12)Online publication date: 2024
https://doi.org/10.1109/TIM.2024.3458040
You FZhang ZXu Z(2024)A developed residual weighted position estimation algorithm for the power IoT2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)10.1109/IAEAC59436.2024.10503789(462-468)Online publication date: 15-Mar-2024
https://doi.org/10.1109/IAEAC59436.2024.10503789

Index Terms

Integrated Navigation in Indoor NLOS Environment Based on Kalman Filter
1. Information systems
  1. Information systems applications

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EITCE '21: Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering

October 2021

1723 pages

ISBN:9781450384322

DOI:10.1145/3501409

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 31 December 2021

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EITCE 2021

EITCE 2021: 2021 5th International Conference on Electronic Information Technology and Computer Engineering

October 22 - 24, 2021

Xiamen, China

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EITCE '21 Paper Acceptance Rate 294 of 531 submissions, 55%;

Overall Acceptance Rate 508 of 972 submissions, 52%

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Li TDeng ZZhang YDong WYu H(2024)A Tightly Coupled UWB/PDR Fusion Positioning Algorithm for Indoor EnvironmentsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2024.345804073(1-12)Online publication date: 2024
https://doi.org/10.1109/TIM.2024.3458040
You FZhang ZXu Z(2024)A developed residual weighted position estimation algorithm for the power IoT2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)10.1109/IAEAC59436.2024.10503789(462-468)Online publication date: 15-Mar-2024
https://doi.org/10.1109/IAEAC59436.2024.10503789

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Seamless outdoor/indoor navigation with WIFI/GPS aided low cost Inertial Navigation System

Optimization of Kalman Filter Indoor Positioning Method Fusing WiFi and PDR

Indoor Tracking and Navigation Using Received Signal Strength and Compressive Sensing on a Mobile Device

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Seamless outdoor/indoor navigation with WIFI/GPS aided low cost Inertial Navigation System

Optimization of Kalman Filter Indoor Positioning Method Fusing WiFi and PDR

Indoor Tracking and Navigation Using Received Signal Strength and Compressive Sensing on a Mobile Device

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