INS/UWB-Based Quadrotor Localization Under Colored Measurement Noise

被引:23
作者
Xu, Yuan [1 ]
Shmaliy, Yuriy S. [2 ]
Shen, Tao [1 ]
Chen, Dong [3 ]
Sun, Mingxu [1 ]
Zhuang, Yuan [3 ]
机构
[1] Univ Jinan, Sch Elect Engn, Jinan 250022, Peoples R China
[2] Univ Guanajuato, Dept Elect Engn, Salamanca 36885, Spain
[3] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
Noise measurement; Sensors; Navigation; Indexes; Task analysis; Sun; Global navigation satellite system; Quadrotor localization; inertial navigation system (INS); ultra-wideband (UWB); finite impulse response (FIR) filter; color measurement noise (CMN);
D O I
10.1109/JSEN.2020.3038242
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Data fusion in the quadrotor integrated navigation system combining information from the inertial navigation system (INS) and ultra wide band (UWB)-based system is provided in the presence of the UWB-induced colored measurement noise (CMN). To improve the localization performance under the CMN, we modify the fusion Kalman filter (KF) to be cKF and the unbiased finite impulse response (UFIR) filter to be cUFIR filter. The cKF and cUFIR filter are derived using measurement differencing and by de-correlating noise vectors. The original and modified filters are tested in the best and worst cases of tuning parameters. Based on test measurements without the ground truth, it is shown that the cKF improves the performance in the best case, but loses to the KF in the worst case due to a higher sensitivity to errors in the noise covariances. It is also shown that the cUFIR filter is more robust and thus more suitable than the cKF and KF for quadrotor localization under the industrial conditions.
引用
收藏
页码:6384 / 6392
页数:9
相关论文
共 35 条
  • [1] Brown R.G., 1983, INTRO RANDOM SIGNALS
  • [2] ESTIMATION USING SAMPLED DATA CONTAINING SEQUENTIALLY CORRELATED NOISE
    BRYSON, AE
    HENDRIKS.LJ
    [J]. JOURNAL OF SPACECRAFT AND ROCKETS, 1968, 5 (06) : 662 - &
  • [3] Bunker RobertJ., 2015, TERRORIST INSURGENT
  • [4] Casati G, 2017, IEEE J RADIO FREQ ID, V1, P155, DOI 10.1109/JRFID.2017.2765619
  • [5] Choy S, 2017, GPS SOLUT, V21, P1
  • [6] Improving adaptive Kalman estimation in GPS/INS integration
    Ding, Weidong
    Wang, Jinling
    Rizos, Chris
    Kinlyside, Doug
    [J]. JOURNAL OF NAVIGATION, 2007, 60 (03) : 517 - 529
  • [7] Adaptive Control of Quadrotor UAVs: A Design Trade Study With Flight Evaluations
    Dydek, Zachary T.
    Annaswamy, Anuradha M.
    Lavretsky, Eugene
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (04) : 1400 - 1406
  • [8] Distributed Coverage Control of Quadrotor Multi-UAV Systems for Precision Agriculture
    Elmokadem, Taha
    [J]. IFAC PAPERSONLINE, 2019, 52 (30): : 251 - 256
  • [9] Study on Innovation Adaptive EKF for In-Flight Alignment of Airborne POS
    Fang Jiancheng
    Yang Sheng
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2011, 60 (04) : 1378 - 1388
  • [10] Gibbs B. P, 2011, ADVACTIVE KALMAN FIL