Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (6): 906-915.doi: 10.23940/ijpe.20.06.p9.906915

Previous Articles     Next Articles

Sequential Finite Horizon H∞ Fusion Filter based Ship Relative Integrated Navigation

Yanping Yanga and Xiaoliang Fengb,c,*   

  1. a Department of Basic, Yellow River Conservancy Technical Institute, Kaifeng, 475003, China;
    b School of Electrical Engineering, Shanghai Dianji University, Shanghai, 200240, China;
    c College of Electrical Engineering, Henan University of Technology, Zhengzhou, 450001, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address:
  • About author:Yanping Yang is a lecturer of Yellow River Conservancy Technical Institute. Her research interests include mathematical modeling, multi-sensor information fusion and its application.
    Xiaoliang Feng is an associate professor of College of Electrical Engineering at Henan University of Technology. His research interests include multi-sensor information fusion and its application.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China under grant no. U1804163, and Foundation for Young Key Teacher by Henan University of Technology (No.21420078).

Abstract: This paper concerns the relative integrated navigation (RIN) problem for the ship navigation systems with finite horizon energy-limited noises. In the ship RIN systems, two kinds of navigation observations can be utilized to obtain more precise navigation information: the ones sampled by inherent navigation devices of the target ship, and the ones broadcasted by the adjacent ships in the near sea area of the target ship. The latter ones are so called relative navigation observations. In this paper, two kinds of novel sequential finite horizon H∞ fusion filtering algorithms are proposed to deal with these observations. Firstly, a centralized fusion performance index is defined and an augmented centralized H∞ fusion filtering algorithm is given to ensure the performance index. Further, this method is extended as a sequential centralized finite horizon H∞ fusion filtering algorithm to sequentially deal with the relative navigation observations in real time. Then, in the distributed fusion framework, a sequential distributed finite horizon H∞ fusion filtering algorithm is also proposed to fuse the local (relative) state estimates of the target ship. Finally, a simulation is employed to illustrate the validity and feasibility of the proposed sequential finite horizon H∞ fusion filter based relative integrated navigation methods.

Key words: finite horizon H∞ fusion filter;, relative integrated navigation, sequential centralized fusion, sequential distributed fusion, unknown statistical noise