Abstract
Fusion positioning technology requires stable and effective positioning data, but this is often challenging to achieve in complex Non-Line-of-Sight (NLoS) environments. This paper proposes a fusion positioning method that can achieve stable and no hop points by adjusting parameters and predicting trends, even with a one-sided lack of fusion data. The method combines acoustic signal and Inertial Measurement Unit (IMU) data, exploiting their respective advantages. The fusion is achieved using the Kalman filter and Bayesian parameter estimation is performed for tuning IMU parameters and predicting motion trends. The proposed method overcomes the problem of fusion failure caused by long-term unilateral data loss in traditional fusion positioning. The positioning trajectory and error distribution analysis show that the proposed method performs optimally in severe NLoS experiments.
- . 2015. SemanticSLAM: Using environment landmarks for unsupervised indoor localization. IEEE Transactions on Mobile Computing 15, 7 (2015), 1770–1782.Google Scholar
Cross Ref
- . 2020. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access 8 (2020), 90225–90265.Google Scholar
Cross Ref
- . 2020. Estimate the pitch and heading mounting angles of the IMU for land vehicular GNSS/INS integrated system. IEEE Transactions on Intelligent Transportation Systems 22, 10 (2020), 6503–6515.Google Scholar
Digital Library
- . 2019. Efficient locality classification for indoor fingerprint-based systems. IEEE Transactions on Mobile Computing 18, 2 (2019), 290–304.Google Scholar
Digital Library
- . 2022. A survey on indoor positioning systems for IoT-based applications. IEEE Internet of Things Journal 9, 10 (2022), 7680–7699.Google Scholar
Cross Ref
- . 2020. WiFi-RTT indoor positioning. In 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS’20). IEEE, 1029–1035.Google Scholar
- . 2016. Real-time loop closure in 2D LIDAR SLAM. In 2016 IEEE International Conference on Robotics and Automation (ICRA’16). IEEE, 1271–1278.Google Scholar
Digital Library
- . 2017. Localization system based on handheld inertial sensors and UWB. In 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL’17). IEEE, 1–2.Google Scholar
- . 2021. An optimized fingerprinting-based indoor positioning with Kalman filter and Universal Kriging for 5G Internet of Things. Wireless Communications and Mobile Computing 2021 (2021).Google Scholar
Digital Library
- . 2018. BLE beacons for Internet of Things applications: Survey, challenges, and opportunities. IEEE Internet of Things Journal 5, 2 (2018), 811–828.Google Scholar
Cross Ref
- . 2017. 4-1: Invited paper: Mobile AR in your pocket with Google Tango. In SID Symposium Digest of Technical Papers, Vol. 48. Wiley Online Library, 17–18.Google Scholar
- . 2015. Quaternion-based robust attitude control for uncertain robotic quadrotors. IEEE Transactions on Industrial Informatics 11, 2 (2015), 406–415.Google Scholar
Cross Ref
- . 2019. Survey on CSI-based indoor positioning systems and recent advances. In 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN’19). IEEE, 1–8.Google Scholar
Cross Ref
- . 2019. RAMTEL: Robust acoustic motion tracking using extreme learning machine for smart cities. IEEE Internet of Things Journal (2019).Google Scholar
- . 2018. Hybrid navigation method of INS/PDR based on action recognition. IEEE Sensors Journal 18, 20 (2018), 8541–8548.Google Scholar
- . 2017. The Microsoft Indoor Localization Competition: Experiences and lessons learned. IEEE Signal Processing Magazine 34, 5 (2017), 125–140.Google Scholar
Cross Ref
- . 2016. CAT: High-precision acoustic motion tracking. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking. ACM, 69–81.Google Scholar
Digital Library
- . 2018. 2018Competition. https://www.microsoft.com/en-us/research/event/microsoft-indoor-localization-competition-ipsn-2018/. (2018).Google Scholar
- . 2015. Maximum likelihood identification of inertial sensor noise model parameters. IEEE Sensors Journal 16, 1 (2015), 163–176.Google Scholar
Cross Ref
- . 2022. Wi-Fi-based indoor patient location identifier for COVID-19. In Computer Networks and Inventive Communication Technologies: Proceedings of Fourth (ICCNCT’21). Springer, 503–511.Google Scholar
Cross Ref
- . 2012. BeepBeep: A high-accuracy acoustic-based system for ranging and localization using COTS devices. ACM Transactions on Embedded Computing Systems (TECS) 11, 1 (2012), 1–29.Google Scholar
Digital Library
- . 2021. Off-line evaluation of indoor positioning systems in different scenarios: The experiences from IPIN 2020 Competition. IEEE Sensors Journal (2021).Google Scholar
- . 2019. Localization systems repository: A platform for open-source localization systems and datasets. In 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN’19). IEEE, 1–8.Google Scholar
Cross Ref
- . 2018. Enhancing indoor smartphone location acquisition using floor plans. In 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN’18). IEEE, 278–289.Google Scholar
Digital Library
- . 2012. Step length estimation using handheld inertial sensors. Sensors 12, 7 (2012), 8507–8525.Google Scholar
Cross Ref
- . 2018. A real-time UWB multi-channel indoor positioning system for industrial scenarios. In 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN’18). IEEE, 1–5.Google Scholar
Cross Ref
- . 2021. Underground mine positioning: A review. IEEE Sensors Journal (2021).Google Scholar
- . 2019. An improved position determination algorithm based on nonlinear compensation for ground-based positioning systems. IEEE Access 7 (2019), 23675–23689.Google Scholar
Cross Ref
- . 2019. Study on mounting position of IMU for better accuracy of ZUPT-aided pedestrian inertial navigation. In 2019 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL’19). IEEE, 1–4.Google Scholar
- . 2022. A survey on Metaverse: Fundamentals, security, and privacy. IEEE Communications Surveys & Tutorials (2022).Google Scholar
- . 2016. AidLoc: An Accurate Acoustic Indoor Localization System. (2016).Google Scholar
- . 2016. Research on Indoor Positioning System with Acoustic Signal based on Smartphone. Master’s Thesis. Zhejiang University.Google Scholar
- . 2017. Blind speech separation and enhancement with GCC-NMF. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 25, 4 (2017), 745–755.Google Scholar
Digital Library
- . 2022. A full dive into realizing the edge-enabled Metaverse: Visions, enabling technologies, and challenges. arXiv preprint arXiv:2203.05471 (2022).Google Scholar
- . 2019. Leveraging acoustic signals for vehicle steering tracking with smartphones. IEEE Transactions on Mobile Computing (2019).Google Scholar
- . 2016. Smartphone-based indoor localization system using inertial sensor and acoustic transmitter/receiver. IEEE Sensors Journal 16, 22 (2016), 8051–8061.Google Scholar
Cross Ref
- . 2019. A survey of indoor localization systems and technologies. IEEE Communications Surveys & Tutorials 21, 3 (2019), 2568–2599.Google Scholar
Cross Ref
- . 2019. TOA estimation of chirp signal in dense multipath environment for low-cost acoustic ranging. IEEE Transactions on Instrumentation and Measurement99 (2019), 1–13.Google Scholar
- . 2017. Image sensor based visible light positioning system with improved positioning algorithm. IEEE Access 5 (2017), 6087–6094.Google Scholar
- . 2015. Mutual coupling reduction for UWB MIMO antennas with a wideband neutralization line. IEEE Antennas and Wireless Propagation Letters 15 (2015), 166–169.Google Scholar
Cross Ref
- . 2015. Stance-phase detection for ZUPT-aided foot-mounted pedestrian navigation system. IEEE/ASME Transactions On Mechatronics 20, 6 (2015), 3170–3181.Google Scholar
Cross Ref
- . 2017. BatTracker: High precision infrastructure-free mobile device tracking in indoor environments. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. ACM, 13.Google Scholar
Digital Library
Index Terms
A Highly Stable Fusion Positioning System of Smartphone under NLoS Acoustic Indoor Environment
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