Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology


An Improved Optimal Measurement Data Correlation Algorithm Based on Multi-Source Information

1Zhaofeng Su, 2Yifan Wang, 1Yuanyuan Duan and 1Li Zhou
1School of Information and Electrical Engineering, Ludong University, Yantai 264025, China
2Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
Research Journal of Applied Sciences, Engineering and Technology  2014  7:1432-1437
http://dx.doi.org/10.19026/rjaset.7.413  |  © The Author(s) 2014
Received: May 16, 2013  |  Accepted: June 11, 2013  |  Published: February 20, 2014

Abstract

An improved optimal 3-Dimensional (3-D) assignment algorithm based on Multi-source Information (IMFOA) is proposed. The algorithm firstly gets the correlation degree between multi-source measurements of single-sensor and target track through fusing multi-source information by using grey relational analysis algorithm and then a 3-D assignment model based on multi-source information fusion can be got. Further, an improved point-track optimal assignment algorithm is used to complete point-track correlations. In comparison with the Optimal 3-D Assignment (OA) algorithm based on dynamic information and the Improved Optimal Assignment (IOA) algorithm which implements point-track correlation through using marginal correlation probability on the basis of OA algorithm, IMFOA algorithm improves the tracking accuracy of multi-target in varying degrees under different detection scenarios and is an optimal measurement data correlation algorithm with stronger anti-interference.

Keywords:

Data correlation, grey relational analysis algorithm, multi-source information,


References

  1. Han, C.Z., H.Y. Zhu and Z.S. Duan, 2010. Multi-Source Information Fusion. Tsinghua University Press, Beijing.
  2. Pan, Q., X.N. Ye and H.C. Zhang, 2005. Generalized probability sata association algorithm. Acta Electron. Sinica, 33(3): 467-472.
  3. Pan, Q., Y. Liang, F. Yang and Y.M. Cheng, 2009. Modern Target Tracking and Information Fusion. National Defense Industry Press, Beijing.
  4. Popp, R., K. Pattipati and Y. Bar-Shalom, 1999. Dynamically adaptable m-Best 2D assignment algorithm and multi-level parallization. IEEE T. Aerospace Electron. Syst., 35(4): 1145-1160.
    CrossRef    
  5. Popp, R., K. Pattipati and Y. Bar-Shalom, 2001. M-best S-D assignment algorithm with application to multitarget tacking. IEEE T. Aerospace Electron. Syst., 37(1): 22-39.
    CrossRef    
  6. Wang, J.G. and J.Q. Luo, 2004. Passive tracking based on data association with information fusion of multi-feature and multi-target. Acta Electron. Sinica, 32(6): 1013-1016.
  7. Wang, J.G., J.Q. Luo and X.M. Jin, 2006. Probabilistic data association algorithm of passive tracking based on information fusion with gray correlation analysis. Acta Electron. Sinica, 34(3): 391-395.
  8. Xu, Y., F. Yang and Q. Pan, 2005. Generalized probability data association algorithm. Comput. Measur. Control, 13(11): 1263-1265.
  9. Zhang, J.W., Y. He and W. Xiong, 2007. Centralized multisensor fuzzy joint probabilistic data association algorithm. J. Tsinghua University, 47(7): 1188-1192.

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved