Spatial Target Localization Using Fuzzy Square-root Cubature Kalman Filter

Authors

Haoshen Lin, Rocket Force University of Engineering, Xi’an 710025, China;
Xiaojun Yang, Rocket Force University of Engineering, Xi’an 710025, China;
He Bing, Rocket Force University of Engineering, Xi’an 710025, China;

Abstract

Abstract: The tracking of spatial target based on bearing-only measurements belongs to the nonlinear model of serious. Uncertain statistical characteristics of noise, which is caused by complex space environment, leads to reduced accuracy of traditional methods. The fuzzy square-root cubature Kalman filter was presented (FS-CKF) by introducing the thought of fuzzy in square-root cubature Kalman filter (SCKF). The algorithm which uses trapezoid subordinate function to describe noise gets rid of the limitations of traditional methods and broadens the range of SCKF. The result of simulation shows that the convergence speed of FS-CKF was 32.52% and 18.28% faster than SCKF on position and velocity respectively, and the accuracy of FS-CKF was 12.52% and 42.65% higher than SCKF on position and velocity respectively.

Recommended Citation

Lin, Haoshen; Yang, Xiaojun; and Bing, He (2019) "Spatial Target Localization Using Fuzzy Square-root Cubature Kalman Filter," Journal of System Simulation: Vol. 30: Iss. 4, Article 18.
DOI: 10.16182/j.issn1004731x.joss.201804018
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss4/18

First Page

1361

Revised Date

2016-07-22

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201804018

Last Page

1368

CLC

V412.4

Recommended Citation

Lin Haoshen, Yang Xiaojun, He Bing. Spatial Target Localization Using Fuzzy Square-root Cubature Kalman Filter[J]. Journal of System Simulation, 2018, 30(4): 1361-1368.

DOI

10.16182/j.issn1004731x.joss.201804018