UWB ranging error estimation and compensation method for relative navigation

被引:0
|
作者
Li R. [1 ]
Wang N. [1 ]
Liu J. [1 ]
Wang Z. [1 ]
机构
[1] Nanvigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing
关键词
Kalman filtering; Ranging measurement; Relative navigation; Ultra-wideband;
D O I
10.19650/j.cnki.cjsi.J1804537
中图分类号
学科分类号
摘要
Intelligent swarm based on unmanned aerial vehicles or robots has become a research hotspot. To achieve collaborative control of dense cluster, the key information is to achieve the precise relative distance among adjacent agent clusters. Ultra-wideband (UWB) wireless transmission technology can transmit information and realize centimeter-level theoretical ranging accuracy. It has broad application prospect in coordinated navigation and control of clusters. In this paper, the UWB ranging scheme for centimeter-level ranging requirement of relative navigation is first described. Then, the reason and characteristics of the ranging error caused by the clock offset of UWB antenna in the actual environment, the relative speed between the nodes and the non-line-of-sight environment is analyzed. The state detection, error compensation and estimation methods of UWB distance measurement are studied. Finally, based on the DW1000 ultra-wideband module, the experimental environment is constructed and the method studied in the paper is evaluated. Experimental results show that the error estimation and elimination method can significantly improve the accuracy of UWB in practical application. Compared with the traditional ranging algorithm, the ranging accuracy of the proposed method is improved under the relatively static scenario and a scene with relative speed between nodes. To be specific, the error is reduced by 70% in the line-of-sight environment state and by 50% in the non-line-of-sight environment state. © 2019, Science Press. All right reserved.
引用
收藏
页码:28 / 35
页数:7
相关论文
共 15 条
  • [1] Leishman R.C., Mclain T.W., Beard R.W., Relative navigation approach for vision-based aerial GPS-denied navigation, Journal of Intelligent & Robotic Systems, 74, 1-2, pp. 97-111, (2014)
  • [2] Xu Z., Liu P.C., Ren S.J., Et al., IQ imbalance estimation and compensation method for ultra-wideband receiver, Chinese Journal of Scientific Instrument, 39, 6, pp. 157-163, (2018)
  • [3] Kim N.S., Rabaey J.M., A 3.1-10.6 GHz 57-Bands CMOS Frequency Synthesizer for UWB-Based Cognitive radios, IEEE Transactions on Microwave Theory and Techniques, 66, 9, pp. 4134-4146, (2018)
  • [4] Kok M., Hol J.D., Schon T.B., Indoor positioning using ultrawideband and inertial measurements, IEEE Transactions on Vehicular Technology, 64, 4, pp. 1293-1303, (2015)
  • [5] Tao C., Research on optimization of SDS-TWR and fusion of location algorithm in indoor position based on UWB, (2016)
  • [6] Zhang T., Xu Y.M., Research on accuracy of UWB ranging and indoor positioning, Gnss World of China, 41, 5, pp. 56-60, (2016)
  • [7] Jing H., Bonenberg L.K., Pinchin J., Et al., Detection of UWB ranging measurement quality for collaborative indoor positioning, Journal of Location Based Services, 9, 4, pp. 296-319, (2015)
  • [8] Wang C.Q., Xu A.G., Sui X., A method of NLOS error inhibition for UWB ranging, Journal of Navigation and Positioning, 5, 3, pp. 24-27, (2017)
  • [9] Hamie J., Denis B., D'Errico R., Et al., Onbody TOA-based ranging error model for motion capture applications within wearable UWB networks, Journal of Ambient Intelligence and Humanized Computing, 6, 5, pp. 603-612, (2015)
  • [10] Yang H., Li W., Zhang H., Et al., Fault tolerant integrated positioning system based on SINS/UWB in complex environment, Chinese Journal of Scientific Instrument, 38, 9, pp. 2177-2185, (2017)