MISSILES AND GUIDANCE TECHNOLOGY

A New Satellite Selection Algorithm for Integrated Navigation

  • CHANG Qiang ,
  • HOU Hongtao ,
  • LI Qun ,
  • ZENG Xianghui ,
  • WANG Weiping
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  • College of Information System and Management, National University of Defense Technology, Changsha 410073, China

Received date: 2013-10-17

  Online published: 2025-05-30

Abstract

The satellite selection algorithm is important when using integrated navigation equipment to estimate position. Selecting part of all visible satellites will limit the number of channels and reduce processing time. By analyzing the principle of quasi-optimal satellite selection algorithm, an improved weighted quasi-optimal satellite selection algorithm was proposed. The main idea of this algorithm is calculating value of all visible satellite using the unit user-satellite vectors and ranging errors. In each iterate, the satellite with the highest importance value is selected to the assistant satellite set. The simulation results show that, the proposed algorithm costs less time with simple calculation by comparision with other satellite selection algorithms. The proposed algorithm satisfies the requirements of integrated navigation receivers.

Cite this article

CHANG Qiang , HOU Hongtao , LI Qun , ZENG Xianghui , WANG Weiping . A New Satellite Selection Algorithm for Integrated Navigation[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2014 , 34(5) : 1 -3,10 . DOI: 10.15892/j.cnki.djzdxb.2014.05.001

References

[1]
张平, 周凤岐, 周军. 一种改进的GPS卫星选择算法研究[J]. 弹箭与制导学报, 2006, 26(2): 781-787.
[2]
KiharaM, Okada T. A satellite selection method and accuracy for the global positioning system[J]. Navigation, 1984, 31(1): 8-20.
[3]
Miaoyan Z, Jun Z. A fast satellite selection algorithm: Beyond four satellites[J]. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(5): 740-747.
[4]
Phatak M S. Recursive method for optimum GPS satellite selection[J]. IEEE Transactions on Aerospace and Electronic Systems, 2001, 37(2): 751-754.
[5]
Saraf M, Mohammadi K, Mosavi MR. GMM-guided gradient descent learning of RBF neural network with its application on robust GPS satellites selection[C] // 1st International Conference on Computer and Knowledge Engineering, 2011:139-443.
[6]
MosaviM R, Sorkhi M. An efficient method for optimum selection of GPS satellites set using recurrent neural network[C] // IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009:245-249.
[7]
Park C W. Precise relative navigation using augmented cdgps[D]. MIT, 2001.
[8]
Miaomiao W, Ju W, Jiaqi L. A new satellite selection algorithm for real-time application[C] // International Conference on Systems and Informatics, 2012:2567-2570.
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