Tightly Coupled Integration of INS and UWB Using Fixed-Lag Extended UFIR Smoothing for Quadrotor Localization
- Authors
- Xu, Yuan; Shmaliy, Yuriy S.; Ahn, Choon Ki; Shen, Tao; Zhuang, Yuan
- Issue Date
- 1-2월-2021
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Smoothing methods; Internet of Things; Robustness; Navigation; Zirconium; Mathematical model; Estimation; Finite impulse response smoothing; fixed-lag smoothing; quadrotor localization; tightly integrated navigation
- Citation
- IEEE INTERNET OF THINGS JOURNAL, v.8, no.3, pp.1716 - 1727
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE INTERNET OF THINGS JOURNAL
- Volume
- 8
- Number
- 3
- Start Page
- 1716
- End Page
- 1727
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/49630
- DOI
- 10.1109/JIOT.2020.3015351
- ISSN
- 2327-4662
- Abstract
- Accurate indoor localization information of the quadrotor plays an important role in many Internet-of-Things applications. To improve the estimation accuracy and robustness, a fixed-lag extended finite impulse response smoother (FEFIRS) algorithm is proposed for fusing the inertial navigation system (INS) and ultra wideband (UWB) data tightly, which employs a distance between the UWB reference nodes and a blind node measured by the INS and UWB. The FEFIRS algorithm consists of an extended unbiased finite impulse response (EFIR) filter and a fixed-lag unbiased FIR (UFIR) smoother. The EFIR filter is employed to improve the robustness, and the fix-lag UFIR smoother is capable of improving the accuracy. Based on extensive test investigations employing real data, the proposed FEFIRS has higher accuracy and robustness than the Kalman-based solutions in the tightly integrated INS/UWB-based indoor quadrotor localization.
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