Tightly Coupled Integration of INS and UWB Using Fixed-Lag Extended UFIR Smoothing for Quadrotor Localization

被引:51
|
作者
Xu, Yuan [1 ]
Shmaliy, Yuriy S. [2 ]
Ahn, Choon Ki [3 ]
Shen, Tao [1 ]
Zhuang, Yuan [4 ]
机构
[1] Univ Jinan, Sch Elect Engn, Jinan 250022, Peoples R China
[2] Univ Guanajuato, Dept Elect Engn, Salamanca 36885, Spain
[3] Korea Univ, Sch Elect Engn, Seoul 08241, South Korea
[4] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
来源
IEEE INTERNET OF THINGS JOURNAL | 2021年 / 8卷 / 03期
基金
新加坡国家研究基金会; 中国国家自然科学基金;
关键词
Smoothing methods; Internet of Things; Robustness; Navigation; Zirconium; Mathematical model; Estimation; Finite impulse response smoothing; fixed-lag smoothing; quadrotor localization; tightly integrated navigation;
D O I
10.1109/JIOT.2020.3015351
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1716 / 1727
页数:12
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